[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-e2a88542328d5273-teaching-ai-to-hack-moving-beyond-benchmaxxing-summary":3,"summaries-facets-categories":145,"summary-related-e2a88542328d5273-teaching-ai-to-hack-moving-beyond-benchmaxxing-summary":6179},{"id":4,"title":5,"ai":6,"body":13,"categories":99,"created_at":101,"date_modified":101,"description":93,"extension":102,"faq":101,"featured":103,"kicker_label":101,"meta":104,"navigation":124,"path":125,"published_at":126,"question":101,"scraped_at":127,"seo":128,"sitemap":129,"source_id":130,"source_name":131,"source_type":132,"source_url":133,"stem":134,"tags":135,"thumbnail_url":140,"tldr":141,"tweet":142,"unknown_tags":143,"__hash__":144},"summaries\u002Fsummaries\u002Fe2a88542328d5273-teaching-ai-to-hack-moving-beyond-benchmaxxing-summary.md","Teaching AI to Hack: Moving Beyond Benchmaxxing",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",8749,1254,5616,0.00406825,{"type":14,"value":15,"toc":92},"minimark",[16,21,25,29,32,55,59,62,89],[17,18,20],"h2",{"id":19},"the-flaw-of-current-security-benchmarks","The Flaw of Current Security Benchmarks",[22,23,24],"p",{},"Most current AI security benchmarks suffer from 'benchmaxxing'—optimizing for metrics that don't reflect real-world security outcomes. Many existing environments, such as Cybench or Cyber Gym, rely on 'LLM-as-a-judge' or simple crash-detection oracles. These setups often assume a single, known vulnerability per target. This leads to two critical failures: the model learns to 'reward hack' by finding the easiest, most obvious bug repeatedly, and the model's reasoning is stunted because the benchmark often provides a backtrace or specific function pointer, effectively telling the model exactly where to look.",[17,26,28],{"id":27},"the-audit-task-framework","The 'Audit Task' Framework",[22,30,31],{},"To solve this, Brumley proposes an 'audit task' approach that treats security as an open-world problem. Instead of asking an AI to 'find the bug,' the system asks the model to 'find all vulnerabilities.' This shift is significant for three reasons:",[33,34,35,43,49],"ol",{},[36,37,38,42],"li",{},[39,40,41],"strong",{},"Deterministic Oracles:"," Rather than relying on LLM judgment, the system uses deterministic graders that verify exploits via stack backtraces, similar to how OS crash reporting works. This removes LLM bias and hallucination.",[36,44,45,48],{},[39,46,47],{},"Precision and Recall:"," By allowing the model to submit multiple proofs of vulnerability (POV), the system can calculate precision (how many submissions are real) and recall (how many known and unknown bugs were found). This prevents the model from spamming invalid results.",[36,50,51,54],{},[39,52,53],{},"Handling Unknowns:"," Because the system doesn't tell the model how many bugs exist, it can discover 'unintended' vulnerabilities—a common occurrence even in high-budget DARPA challenges—which then become part of the ground truth for future training.",[17,56,58],{"id":57},"climbing-the-ladder-of-exploitation","Climbing the Ladder of Exploitation",[22,60,61],{},"Effective training requires a graduated ladder of difficulty. Hacking is not just crashing a program; it is bending a computer to one's will. Brumley’s team maps this ladder across 16 capability levels, moving from simple crashes to complex chains:",[63,64,65,71,77,83],"ul",{},[36,66,67,70],{},[39,68,69],{},"Level 1:"," Triggering a crash in an in-sandbox object.",[36,72,73,76],{},[39,74,75],{},"Level 2:"," Achieving in-sandbox primitives (arbitrary read\u002Fwrite).",[36,78,79,82],{},[39,80,81],{},"Level 3:"," Chaining vulnerabilities to escape the sandbox.",[36,84,85,88],{},[39,86,87],{},"Level 4:"," Achieving full arbitrary code execution (ACE).",[22,90,91],{},"When testing against V8 (the JavaScript engine in Chrome), Brumley found that while top-tier models could trigger a crash 95% of the time, the real differentiator was their ability to chain vulnerabilities to escape the sandbox. This capability is what separates a model that 'looks' like it can hack from one that can produce a genuine zero-day exploit.",{"title":93,"searchDepth":94,"depth":94,"links":95},"",2,[96,97,98],{"id":19,"depth":94,"text":20},{"id":27,"depth":94,"text":28},{"id":57,"depth":94,"text":58},[100],"AI & LLMs",null,"md",false,{"content_references":105,"triage":119},[106,110,112,115,117],{"type":107,"title":108,"context":109},"tool","picoCTF","mentioned",{"type":107,"title":111,"context":109},"V8 JavaScript Engine",{"type":113,"title":114,"context":109},"event","Pwn2Own",{"type":113,"title":116,"context":109},"DARPA Cyber Grand Challenge",{"type":113,"title":118,"context":109},"AIXCC (AI Cyber Challenge)",{"relevance":120,"novelty":120,"quality":120,"actionability":121,"composite":122,"reasoning":123},4,3,3.8,"Category: AI & LLMs. The article discusses a new framework for evaluating AI security agents, addressing a specific pain point in the effectiveness of current benchmarks. It presents a novel approach to security testing that could be actionable for developers looking to improve their AI models, though it lacks detailed implementation steps.",true,"\u002Fsummaries\u002Fe2a88542328d5273-teaching-ai-to-hack-moving-beyond-benchmaxxing-summary","2026-08-01 00:30:06","2026-08-01 03:11:55",{"title":5,"description":93},{"loc":125},"e2a88542328d5273","AI Engineer","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=ZFxh7sqbUZo","summaries\u002Fe2a88542328d5273-teaching-ai-to-hack-moving-beyond-benchmaxxing-summary",[136,137,138,139],"automation","ai-llms","security","reinforcement-learning","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FZFxh7sqbUZo\u002Fhqdefault.jpg","To build effective AI security agents, developers must move from simple crash-based benchmarks to deterministic, multi-vulnerability 'audit tasks' that measure real exploitation capabilities like arbitrary code execution.","This talk argues that AI security research is currently held back by \"benchmaxxing\"—relying on flawed, LLM-based grading oracles—and proposes instead the use of reproducible, sandboxed reinforcement learning environments with deterministic graders. The speaker, [David Brumley](https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fthedavidbrumley), demonstrates that by grading models on their ability to trigger specific, real-world vulnerabilities (like those found in the V8 engine), researchers can move beyond hallucinated successes to measure genuine exploitation capabilities.",[137,138,139],"7VJBgxxO63jn6s1-zLY_4QAyYKi2JM1Qns3qXgFvpB8",[146,148,151,154,156,159,162,164,166,168,171,173,175,177,179,182,184,186,188,190,193,195,197,199,201,203,205,207,209,211,213,215,217,219,221,223,225,227,229,231,234,237,239,241,243,245,247,249,251,253,255,257,259,262,264,266,268,270,272,274,276,278,280,282,284,286,288,290,292,294,297,299,301,303,305,307,309,311,313,315,317,319,321,323,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,368,370,372,374,376,378,380,382,385,387,389,391,393,395,397,399,401,403,406,408,410,412,414,416,418,420,422,424,426,428,430,433,435,437,439,441,443,445,447,449,452,454,456,458,460,462,464,466,468,470,472,474,476,478,480,482,484,486,488,490,492,494,496,498,500,502,505,507,509,512,514,516,518,520,522,524,526,528,530,532,534,536,538,541,543,545,547,549,551,553,555,557,559,561,564,566,568,570,572,574,576,578,580,582,584,586,588,590,592,594,596,598,600,602,604,606,608,610,612,614,616,618,620,622,624,626,628,630,632,634,636,638,640,642,644,646,648,650,652,654,656,658,660,662,664,666,668,670,672,674,676,678,680,682,684,686,688,690,692,694,696,698,700,702,704,706,708,710,712,714,716,718,720,722,724,726,728,730,732,734,736,738,740,742,744,746,748,750,752,754,756,758,760,762,764,766,768,770,772,774,776,778,780,782,784,786,788,790,792,794,796,798,800,802,804,806,808,810,812,815,817,819,821,823,826,828,830,832,834,836,838,840,842,844,846,849,851,853,855,857,859,861,863,865,867,869,871,873,875,877,879,881,883,885,887,889,891,893,895,897,899,901,903,905,907,909,911,913,915,917,919,921,923,925,927,929,931,933,935,937,939,941,943,945,947,949,951,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1126,1128,1130,1132,1134,1136,1138,1140,1142,1144,1146,1148,1150,1152,1154,1156,1158,1160,1162,1164,1166,1168,1170,1172,1174,1176,1178,1180,1182,1184,1186,1188,1190,1192,1194,1196,1198,1200,1202,1204,1206,1208,1210,1212,1214,1216,1218,1220,1222,1224,1226,1228,1230,1232,1234,1236,1238,1240,1242,1244,1246,1248,1250,1252,1254,1256,1258,1260,1262,1264,1266,1268,1270,1272,1274,1276,1278,1280,1282,1284,1286,1288,1290,1292,1294,1296,1299,1301,1303,1305,1307,1309,1311,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1430,1432,1434,1436,1438,1440,1442,1444,1446,1448,1450,1452,1454,1456,1458,1460,1462,1464,1466,1468,1470,1472,1474,1476,1478,1480,1482,1484,1486,1488,1490,1492,1494,1496,1498,1500,1502,1504,1506,1508,1510,1512,1514,1516,1518,1520,1522,1524,1526,1528,1530,1532,1534,1536,1538,1540,1542,1544,1546,1548,1550,1552,1554,1556,1558,1560,1562,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1622,1624,1626,1628,1630,1632,1634,1636,1638,1640,1642,1644,1646,1648,1650,1652,1654,1656,1658,1660,1662,1664,1666,1668,1670,1672,1674,1676,1678,1680,1682,1684,1686,1688,1690,1692,1694,1696,1698,1700,1702,1704,1706,1708,1710,1712,1714,1716,1718,1720,1722,1724,1726,1728,1730,1732,1734,1736,1738,1740,1742,1744,1746,1748,1750,1752,1754,1756,1758,1760,1762,1764,1766,1768,1770,1772,1774,1776,1778,1780,1782,1784,1786,1788,1790,1792,1794,1796,1798,1800,1802,1804,1806,1808,1810,1812,1814,1816,1818,1820,1822,1824,1826,1828,1830,1832,1834,1836,1838,1840,1842,1844,1846,1848,1850,1852,1854,1856,1858,1860,1862,1864,1866,1868,1870,1872,1874,1876,1878,1880,1882,1884,1886,1888,1890,1892,1894,1896,1898,1900,1902,1904,1906,1908,1910,1912,1914,1916,1918,1920,1922,1924,1926,1928,1930,1932,1934,1936,1938,1940,1942,1944,1946,1948,1950,1952,1954,1956,1958,1960,1962,1964,1966,1968,1970,1972,1974,1976,1978,1980,1982,1984,1986,1988,1990,1992,1995,1997,1999,2001,2003,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2074,2076,2078,2080,2082,2084,2086,2088,2090,2092,2094,2096,2098,2100,2102,2104,2106,2108,2110,2112,2114,2116,2118,2120,2122,2124,2126,2128,2130,2132,2134,2136,2138,2140,2142,2144,2146,2148,2150,2152,2154,2156,2158,2160,2162,2164,2166,2168,2170,2172,2174,2176,2178,2180,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2224,2226,2228,2230,2232,2234,2236,2238,2240,2242,2244,2246,2248,2250,2252,2254,2256,2258,2260,2262,2264,2266,2268,2270,2272,2274,2276,2278,2280,2282,2284,2286,2288,2290,2292,2294,2296,2298,2300,2302,2304,2306,2308,2310,2312,2314,2316,2318,2320,2322,2324,2326,2328,2330,2332,2334,2336,2338,2340,2342,2344,2346,2348,2350,2352,2354,2356,2358,2360,2362,2364,2366,2368,2370,2372,2374,2376,2378,2380,2382,2384,2386,2388,2390,2392,2394,2396,2398,2400,2402,2404,2406,2408,2410,2412,2414,2416,2418,2420,2422,2424,2426,2428,2430,2432,2434,2436,2438,2440,2442,2444,2446,2448,2450,2452,2454,2456,2458,2460,2462,2464,2466,2468,2470,2472,2474,2476,2478,2480,2482,2484,2486,2488,2490,2492,2494,2496,2498,2500,2502,2504,2506,2508,2510,2512,2514,2516,2518,2520,2522,2524,2526,2528,2530,2532,2534,2536,2538,2540,2542,2544,2546,2548,2550,2552,2554,2556,2558,2560,2562,2564,2566,2568,2570,2572,2574,2576,2578,2580,2582,2584,2586,2588,2590,2592,2594,2596,2598,2600,2602,2604,2606,2608,2610,2612,2614,2616,2618,2620,2622,2624,2626,2628,2630,2632,2634,2636,2638,2640,2642,2644,2646,2648,2650,2652,2654,2656,2658,2660,2662,2664,2666,2668,2670,2672,2674,2676,2678,2680,2682,2684,2686,2688,2690,2692,2694,2696,2698,2700,2702,2704,2706,2708,2710,2712,2714,2716,2718,2720,2722,2724,2726,2728,2730,2732,2734,2736,2738,2740,2742,2744,2746,2748,2750,2752,2754,2756,2758,2760,2762,2764,2766,2768,2770,2772,2774,2776,2778,2780,2782,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2888,2890,2892,2894,2896,2898,2900,2902,2904,2906,2908,2910,2912,2914,2916,2918,2920,2922,2924,2926,2928,2930,2932,2934,2936,2938,2940,2942,2944,2946,2948,2950,2952,2954,2956,2958,2960,2962,2964,2966,2968,2970,2972,2974,2976,2978,2980,2982,2984,2986,2988,2990,2992,2994,2996,2998,3000,3002,3004,3006,3008,3010,3012,3014,3016,3018,3020,3022,3024,3026,3028,3030,3032,3034,3036,3038,3040,3042,3044,3046,3048,3050,3052,3054,3056,3058,3060,3062,3064,3066,3068,3070,3072,3074,3076,3078,3080,3082,3084,3086,3088,3090,3092,3094,3096,3098,3100,3102,3104,3106,3108,3110,3112,3114,3116,3118,3120,3122,3124,3126,3128,3130,3132,3134,3136,3138,3140,3142,3144,3146,3148,3150,3152,3154,3156,3158,3160,3162,3164,3166,3168,3170,3172,3174,3176,3178,3180,3182,3184,3186,3188,3190,3192,3194,3196,3198,3200,3202,3204,3206,3208,3210,3212,3214,3216,3218,3220,3222,3224,3226,3228,3230,3232,3234,3236,3238,3240,3242,3244,3246,3248,3250,3252,3254,3256,3258,3260,3262,3264,3266,3268,3270,3272,3274,3276,3278,3280,3282,3284,3286,3288,3290,3292,3294,3296,3298,3300,3302,3304,3306,3308,3310,3312,3314,3316,3318,3320,3322,3324,3326,3328,3330,3332,3334,3336,3338,3340,3342,3344,3346,3348,3350,3352,3354,3356,3358,3360,3362,3364,3366,3368,3370,3372,3374,3376,3378,3380,3382,3384,3386,3388,3390,3392,3394,3396,3398,3400,3402,3404,3406,3408,3410,3412,3414,3416,3418,3420,3422,3424,3426,3428,3430,3432,3434,3436,3438,3440,3442,3444,3446,3448,3450,3452,3454,3456,3458,3460,3462,3464,3466,3468,3470,3472,3474,3476,3478,3480,3482,3484,3486,3488,3490,3492,3494,3496,3498,3500,3502,3504,3506,3508,3510,3512,3514,3516,3518,3520,3522,3524,3526,3528,3530,3532,3534,3536,3538,3540,3542,3544,3546,3548,3550,3552,3554,3556,3558,3560,3562,3564,3566,3568,3570,3572,3574,3576,3578,3580,3582,3584,3586,3588,3590,3592,3594,3596,3598,3600,3602,3604,3606,3608,3610,3612,3614,3616,3618,3620,3622,3624,3626,3628,3630,3632,3634,3636,3638,3640,3642,3644,3646,3648,3650,3652,3654,3656,3658,3660,3662,3664,3666,3668,3670,3672,3674,3676,3678,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700,3702,3704,3706,3708,3710,3712,3714,3716,3718,3720,3722,3724,3726,3728,3730,3732,3734,3736,3738,3740,3742,3744,3746,3748,3750,3752,3754,3756,3758,3760,3762,3764,3766,3768,3770,3772,3774,3776,3778,3780,3782,3784,3786,3788,3790,3792,3794,3796,3798,3800,3802,3804,3806,3808,3810,3812,3814,3816,3818,3820,3822,3824,3826,3828,3830,3832,3834,3836,3838,3840,3842,3844,3846,3848,3850,3852,3854,3856,3858,3860,3862,3864,3866,3868,3870,3872,3874,3876,3878,3880,3882,3884,3886,3888,3890,3892,3894,3896,3898,3900,3902,3904,3906,3908,3910,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4011,4013,4015,4017,4019,4021,4023,4025,4027,4029,4031,4033,4035,4037,4039,4041,4043,4045,4047,4049,4051,4053,4055,4057,4059,4061,4063,4065,4067,4069,4071,4073,4075,4077,4079,4081,4083,4085,4087,4089,4091,4093,4095,4097,4099,4101,4103,4105,4107,4109,4111,4113,4115,4117,4119,4121,4123,4125,4127,4129,4131,4133,4135,4137,4139,4141,4143,4145,4147,4149,4151,4153,4155,4157,4159,4161,4163,4165,4167,4169,4171,4173,4175,4177,4179,4181,4183,4185,4187,4189,4191,4193,4195,4197,4199,4201,4203,4205,4207,4209,4211,4213,4215,4217,4219,4221,4223,4225,4227,4229,4231,4233,4235,4237,4239,4241,4243,4245,4247,4249,4251,4253,4255,4257,4259,4261,4263,4265,4267,4269,4271,4273,4275,4277,4279,4281,4283,4285,4287,4289,4291,4293,4295,4297,4299,4301,4303,4305,4307,4309,4311,4313,4315,4317,4319,4321,4323,4325,4327,4329,4331,4333,4335,4337,4339,4341,4343,4345,4347,4349,4351,4353,4355,4357,4359,4361,4363,4365,4367,4369,4371,4373,4375,4377,4379,4381,4383,4385,4387,4389,4391,4393,4395,4397,4399,4401,4403,4405,4407,4409,4411,4413,4415,4417,4419,4421,4423,4425,4427,4429,4431,4433,4435,4437,4439,4441,4443,4445,4447,4449,4451,4453,4455,4457,4459,4461,4463,4465,4467,4469,4471,4473,4475,4477,4479,4481,4483,4485,4487,4489,4491,4493,4495,4497,4499,4501,4503,4505,4507,4509,4511,4513,4515,4517,4519,4521,4523,4525,4527,4529,4531,4533,4535,4537,4539,4541,4543,4545,4547,4549,4551,4553,4555,4557,4559,4561,4563,4565,4567,4569,4571,4573,4575,4577,4579,4581,4583,4585,4587,4589,4591,4593,4595,4597,4599,4601,4603,4605,4607,4609,4611,4613,4615,4617,4619,4621,4623,4625,4627,4629,4631,4633,4635,4637,4639,4641,4643,4645,4647,4649,4651,4653,4655,4657,4659,4661,4663,4665,4667,4669,4671,4673,4675,4677,4679,4681,4683,4685,4687,4689,4691,4693,4695,4697,4699,4701,4703,4705,4707,4709,4711,4713,4715,4717,4719,4721,4723,4725,4727,4729,4731,4733,4735,4737,4739,4741,4743,4745,4747,4749,4751,4753,4755,4757,4759,4761,4763,4765,4768,4770,4772,4774,4776,4778,4780,4782,4784,4786,4788,4790,4792,4794,4796,4798,4800,4802,4804,4806,4808,4810,4812,4814,4816,4818,4820,4822,4824,4826,4828,4830,4832,4834,4836,4838,4840,4842,4844,4846,4848,4850,4852,4854,4856,4858,4860,4862,4864,4866,4868,4870,4872,4874,4876,4878,4880,4882,4884,4886,4888,4890,4892,4894,4896,4898,4900,4902,4904,4906,4908,4910,4912,4914,4916,4918,4920,4922,4924,4926,4928,4930,4932,4934,4936,4938,4940,4943,4945,4947,4949,4951,4953,4955,4957,4959,4961,4963,4965,4967,4969,4971,4973,4975,4977,4979,4981,4983,4985,4987,4989,4991,4993,4995,4997,4999,5001,5003,5005,5007,5009,5011,5013,5015,5017,5019,5021,5023,5025,5027,5029,5031,5033,5035,5037,5039,5041,5043,5045,5047,5049,5051,5053,5055,5057,5059,5061,5063,5065,5067,5069,5071,5073,5075,5077,5079,5081,5083,5085,5087,5089,5091,5093,5095,5097,5099,5101,5103,5105,5107,5109,5111,5113,5115,5117,5119,5121,5123,5125,5127,5129,5131,5133,5135,5137,5139,5141,5143,5145,5147,5149,5151,5153,5155,5157,5159,5161,5163,5165,5167,5169,5171,5173,5175,5177,5179,5181,5183,5185,5187,5189,5191,5193,5195,5197,5199,5201,5203,5205,5207,5209,5211,5213,5215,5217,5219,5221,5223,5225,5227,5229,5231,5233,5235,5237,5239,5241,5243,5245,5247,5249,5251,5253,5255,5257,5259,5261,5263,5265,5267,5269,5271,5273,5275,5277,5279,5281,5283,5285,5287,5289,5291,5293,5295,5297,5299,5301,5303,5305,5307,5309,5311,5313,5315,5317,5319,5321,5323,5325,5327,5329,5331,5333,5335,5337,5339,5341,5343,5345,5347,5349,5351,5353,5355,5357,5359,5361,5363,5365,5367,5369,5371,5373,5375,5377,5379,5381,5383,5385,5387,5389,5391,5393,5395,5397,5399,5401,5403,5405,5407,5409,5411,5413,5415,5417,5419,5421,5423,5425,5427,5429,5431,5433,5435,5437,5439,5441,5443,5445,5447,5449,5451,5453,5455,5457,5459,5461,5463,5465,5467,5469,5471,5473,5475,5477,5479,5481,5483,5485,5487,5489,5491,5493,5495,5497,5499,5501,5503,5505,5507,5509,5511,5513,5515,5517,5519,5521,5523,5525,5527,5529,5531,5533,5535,5537,5539,5541,5543,5545,5547,5549,5551,5553,5555,5557,5559,5561,5563,5565,5567,5569,5571,5573,5575,5577,5579,5581,5583,5585,5587,5589,5591,5593,5595,5597,5599,5601,5603,5605,5607,5609,5611,5613,5615,5617,5619,5621,5623,5625,5627,5629,5631,5633,5635,5637,5639,5641,5643,5645,5647,5649,5651,5653,5655,5657,5659,5661,5663,5665,5667,5669,5671,5673,5675,5677,5679,5681,5683,5685,5687,5689,5691,5693,5695,5697,5699,5701,5703,5705,5707,5709,5711,5713,5715,5717,5719,5721,5723,5725,5727,5729,5731,5733,5735,5737,5739,5741,5743,5745,5747,5749,5751,5753,5755,5757,5759,5761,5763,5765,5767,5769,5771,5773,5775,5777,5779,5781,5783,5785,5787,5789,5791,5793,5795,5797,5799,5801,5803,5805,5807,5809,5811,5813,5815,5817,5819,5821,5823,5825,5827,5829,5831,5833,5835,5837,5839,5841,5843,5845,5847,5849,5851,5853,5855,5857,5859,5861,5863,5865,5867,5869,5871,5873,5875,5877,5879,5881,5883,5885,5887,5889,5891,5893,5895,5897,5899,5901,5903,5905,5907,5909,5911,5913,5915,5917,5919,5921,5923,5925,5927,5929,5931,5933,5935,5937,5939,5941,5943,5945,5947,5949,5951,5953,5955,5957,5959,5961,5963,5965,5967,5969,5971,5973,5975,5977,5979,5981,5983,5985,5987,5989,5991,5993,5995,5997,5999,6001,6003,6005,6007,6009,6011,6013,6015,6017,6019,6021,6023,6025,6027,6029,6031,6033,6035,6037,6039,6041,6043,6045,6047,6049,6051,6053,6055,6057,6059,6061,6063,6065,6067,6069,6071,6073,6075,6077,6079,6081,6083,6085,6087,6089,6091,6093,6095,6097,6099,6101,6103,6105,6107,6109,6111,6113,6115,6117,6119,6121,6123,6125,6127,6129,6131,6133,6135,6137,6139,6141,6143,6145,6147,6149,6151,6153,6155,6157,6159,6161,6163,6165,6167,6169,6171,6173,6175,6177],{"categories":147},[100],{"categories":149},[150],"Developer Productivity",{"categories":152},[153],"Business & SaaS",{"categories":155},[100],{"categories":157},[158],"AI Automation",{"categories":160},[161],"Product Strategy",{"categories":163},[100],{"categories":165},[150],{"categories":167},[158],{"categories":169},[170],"Software Engineering",{"categories":172},[100],{"categories":174},[153],{"categories":176},[],{"categories":178},[100],{"categories":180},[181],"Inference & Serving",{"categories":183},[100],{"categories":185},[100],{"categories":187},[158],{"categories":189},[],{"categories":191},[192],"AI News & Trends",{"categories":194},[158],{"categories":196},[100],{"categories":198},[153],{"categories":200},[150],{"categories":202},[100],{"categories":204},[158],{"categories":206},[192],{"categories":208},[158],{"categories":210},[158],{"categories":212},[100],{"categories":214},[158],{"categories":216},[100],{"categories":218},[100],{"categories":220},[100],{"categories":222},[192],{"categories":224},[100],{"categories":226},[100],{"categories":228},[100],{"categories":230},[],{"categories":232},[233],"Design & Frontend",{"categories":235},[236],"Data Science & Visualization",{"categories":238},[192],{"categories":240},[100],{"categories":242},[100],{"categories":244},[100],{"categories":246},[],{"categories":248},[100],{"categories":250},[158],{"categories":252},[170],{"categories":254},[100],{"categories":256},[158],{"categories":258},[100],{"categories":260},[261],"Marketing & Growth",{"categories":263},[233],{"categories":265},[100],{"categories":267},[158],{"categories":269},[100],{"categories":271},[170],{"categories":273},[],{"categories":275},[],{"categories":277},[233],{"categories":279},[100],{"categories":281},[158],{"categories":283},[150],{"categories":285},[170],{"categories":287},[233],{"categories":289},[161],{"categories":291},[100],{"categories":293},[170],{"categories":295},[296],"DevOps & Cloud",{"categories":298},[158],{"categories":300},[161],{"categories":302},[192],{"categories":304},[100],{"categories":306},[],{"categories":308},[100],{"categories":310},[100],{"categories":312},[],{"categories":314},[158],{"categories":316},[170],{"categories":318},[],{"categories":320},[170],{"categories":322},[100],{"categories":324},[325],"Governance & Standards",{"categories":327},[153],{"categories":329},[],{"categories":331},[],{"categories":333},[100],{"categories":335},[100],{"categories":337},[158],{"categories":339},[100],{"categories":341},[100],{"categories":343},[158],{"categories":345},[100],{"categories":347},[100],{"categories":349},[100],{"categories":351},[],{"categories":353},[170],{"categories":355},[],{"categories":357},[],{"categories":359},[170],{"categories":361},[],{"categories":363},[170],{"categories":365},[100],{"categories":367},[100],{"categories":369},[261],{"categories":371},[100],{"categories":373},[233],{"categories":375},[233],{"categories":377},[100],{"categories":379},[170],{"categories":381},[158],{"categories":383},[384],"GovTech & Public-Sector Adoption",{"categories":386},[170],{"categories":388},[100],{"categories":390},[100],{"categories":392},[158],{"categories":394},[158],{"categories":396},[236],{"categories":398},[100],{"categories":400},[192],{"categories":402},[158],{"categories":404},[405],"Legal AI Tools",{"categories":407},[158],{"categories":409},[261],{"categories":411},[158],{"categories":413},[161],{"categories":415},[170],{"categories":417},[384],{"categories":419},[],{"categories":421},[158],{"categories":423},[],{"categories":425},[153],{"categories":427},[158],{"categories":429},[158],{"categories":431},[432],"RAG & Retrieval",{"categories":434},[153],{"categories":436},[100],{"categories":438},[170],{"categories":440},[170],{"categories":442},[296],{"categories":444},[233],{"categories":446},[100],{"categories":448},[],{"categories":450},[451],"Agents & Orchestration",{"categories":453},[170],{"categories":455},[100],{"categories":457},[],{"categories":459},[158],{"categories":461},[153],{"categories":463},[],{"categories":465},[100],{"categories":467},[],{"categories":469},[150],{"categories":471},[170],{"categories":473},[153],{"categories":475},[100],{"categories":477},[158],{"categories":479},[100],{"categories":481},[192],{"categories":483},[100],{"categories":485},[],{"categories":487},[100],{"categories":489},[],{"categories":491},[170],{"categories":493},[100],{"categories":495},[236],{"categories":497},[],{"categories":499},[100],{"categories":501},[233],{"categories":503},[504],"Models & Frontier Labs",{"categories":506},[],{"categories":508},[233],{"categories":510},[511],"Regulation & Governance of AI",{"categories":513},[158],{"categories":515},[],{"categories":517},[100],{"categories":519},[100],{"categories":521},[158],{"categories":523},[192],{"categories":525},[153],{"categories":527},[100],{"categories":529},[],{"categories":531},[170],{"categories":533},[158],{"categories":535},[100],{"categories":537},[161],{"categories":539},[540],"AI Policy & Regulation",{"categories":542},[],{"categories":544},[100],{"categories":546},[161],{"categories":548},[158],{"categories":550},[100],{"categories":552},[100],{"categories":554},[100],{"categories":556},[158],{"categories":558},[],{"categories":560},[236],{"categories":562},[563],"Evals & Reliability",{"categories":565},[100],{"categories":567},[],{"categories":569},[150],{"categories":571},[384],{"categories":573},[540],{"categories":575},[100],{"categories":577},[153],{"categories":579},[100],{"categories":581},[158],{"categories":583},[100],{"categories":585},[158],{"categories":587},[451],{"categories":589},[100],{"categories":591},[170],{"categories":593},[100],{"categories":595},[],{"categories":597},[],{"categories":599},[100],{"categories":601},[384],{"categories":603},[100],{"categories":605},[100],{"categories":607},[100],{"categories":609},[],{"categories":611},[233],{"categories":613},[],{"categories":615},[100],{"categories":617},[],{"categories":619},[158],{"categories":621},[100],{"categories":623},[233],{"categories":625},[],{"categories":627},[100],{"categories":629},[158],{"categories":631},[100],{"categories":633},[153],{"categories":635},[158],{"categories":637},[100],{"categories":639},[100],{"categories":641},[170],{"categories":643},[233],{"categories":645},[158],{"categories":647},[],{"categories":649},[170],{"categories":651},[158],{"categories":653},[236],{"categories":655},[],{"categories":657},[192],{"categories":659},[],{"categories":661},[100],{"categories":663},[100],{"categories":665},[100],{"categories":667},[153,261],{"categories":669},[],{"categories":671},[100],{"categories":673},[100],{"categories":675},[158],{"categories":677},[],{"categories":679},[],{"categories":681},[100],{"categories":683},[233],{"categories":685},[100],{"categories":687},[],{"categories":689},[100],{"categories":691},[296],{"categories":693},[],{"categories":695},[158],{"categories":697},[192],{"categories":699},[100],{"categories":701},[100],{"categories":703},[233],{"categories":705},[],{"categories":707},[192],{"categories":709},[100],{"categories":711},[181],{"categories":713},[100],{"categories":715},[158],{"categories":717},[192],{"categories":719},[504],{"categories":721},[100],{"categories":723},[261],{"categories":725},[],{"categories":727},[158],{"categories":729},[153],{"categories":731},[170],{"categories":733},[100],{"categories":735},[158],{"categories":737},[],{"categories":739},[100,296],{"categories":741},[100],{"categories":743},[100],{"categories":745},[100],{"categories":747},[158],{"categories":749},[100,170],{"categories":751},[236],{"categories":753},[100],{"categories":755},[100],{"categories":757},[170],{"categories":759},[158],{"categories":761},[540],{"categories":763},[261],{"categories":765},[100],{"categories":767},[158],{"categories":769},[100],{"categories":771},[100],{"categories":773},[158],{"categories":775},[],{"categories":777},[158],{"categories":779},[100],{"categories":781},[100],{"categories":783},[158],{"categories":785},[100],{"categories":787},[100,153],{"categories":789},[153],{"categories":791},[],{"categories":793},[233],{"categories":795},[233],{"categories":797},[100],{"categories":799},[],{"categories":801},[],{"categories":803},[192],{"categories":805},[],{"categories":807},[150],{"categories":809},[100],{"categories":811},[170],{"categories":813},[814],"Generative UI & Design-to-Code",{"categories":816},[100],{"categories":818},[100],{"categories":820},[233],{"categories":822},[100],{"categories":824},[825],"Algorithmic Accountability",{"categories":827},[158],{"categories":829},[170],{"categories":831},[192],{"categories":833},[233],{"categories":835},[],{"categories":837},[161],{"categories":839},[100],{"categories":841},[100],{"categories":843},[100],{"categories":845},[158],{"categories":847},[848],"MLOps & Infrastructure",{"categories":850},[100],{"categories":852},[100],{"categories":854},[100],{"categories":856},[100],{"categories":858},[100],{"categories":860},[192],{"categories":862},[150],{"categories":864},[100],{"categories":866},[158],{"categories":868},[296],{"categories":870},[100],{"categories":872},[153],{"categories":874},[100],{"categories":876},[233],{"categories":878},[100],{"categories":880},[100],{"categories":882},[158],{"categories":884},[],{"categories":886},[],{"categories":888},[100],{"categories":890},[181],{"categories":892},[233],{"categories":894},[192],{"categories":896},[236],{"categories":898},[],{"categories":900},[100],{"categories":902},[100],{"categories":904},[153],{"categories":906},[158],{"categories":908},[100],{"categories":910},[100],{"categories":912},[100],{"categories":914},[192],{"categories":916},[181],{"categories":918},[100],{"categories":920},[233],{"categories":922},[100],{"categories":924},[],{"categories":926},[158],{"categories":928},[170],{"categories":930},[],{"categories":932},[100],{"categories":934},[100],{"categories":936},[158],{"categories":938},[170],{"categories":940},[100],{"categories":942},[236],{"categories":944},[],{"categories":946},[100],{"categories":948},[],{"categories":950},[100],{"categories":952},[],{"categories":954},[161],{"categories":956},[153],{"categories":958},[158],{"categories":960},[158],{"categories":962},[],{"categories":964},[150],{"categories":966},[100],{"categories":968},[100],{"categories":970},[153],{"categories":972},[192],{"categories":974},[150],{"categories":976},[],{"categories":978},[100],{"categories":980},[],{"categories":982},[],{"categories":984},[192],{"categories":986},[192],{"categories":988},[],{"categories":990},[451],{"categories":992},[100],{"categories":994},[233],{"categories":996},[170],{"categories":998},[],{"categories":1000},[405],{"categories":1002},[153],{"categories":1004},[],{"categories":1006},[],{"categories":1008},[150],{"categories":1010},[236],{"categories":1012},[],{"categories":1014},[261],{"categories":1016},[158],{"categories":1018},[153],{"categories":1020},[158],{"categories":1022},[153],{"categories":1024},[170],{"categories":1026},[],{"categories":1028},[181],{"categories":1030},[161],{"categories":1032},[100],{"categories":1034},[233],{"categories":1036},[170],{"categories":1038},[153],{"categories":1040},[100],{"categories":1042},[158],{"categories":1044},[153],{"categories":1046},[100],{"categories":1048},[100],{"categories":1050},[100],{"categories":1052},[100],{"categories":1054},[],{"categories":1056},[],{"categories":1058},[170],{"categories":1060},[236],{"categories":1062},[161],{"categories":1064},[100],{"categories":1066},[158],{"categories":1068},[170],{"categories":1070},[100],{"categories":1072},[],{"categories":1074},[192],{"categories":1076},[161],{"categories":1078},[100],{"categories":1080},[563],{"categories":1082},[296],{"categories":1084},[],{"categories":1086},[158],{"categories":1088},[],{"categories":1090},[150],{"categories":1092},[],{"categories":1094},[100],{"categories":1096},[100],{"categories":1098},[233],{"categories":1100},[261],{"categories":1102},[170],{"categories":1104},[158],{"categories":1106},[],{"categories":1108},[170],{"categories":1110},[100],{"categories":1112},[150],{"categories":1114},[],{"categories":1116},[153],{"categories":1118},[100],{"categories":1120},[192],{"categories":1122},[100,296],{"categories":1124},[1125],"Design Systems for AI",{"categories":1127},[100],{"categories":1129},[100],{"categories":1131},[192],{"categories":1133},[100],{"categories":1135},[100],{"categories":1137},[153],{"categories":1139},[100],{"categories":1141},[100],{"categories":1143},[],{"categories":1145},[100],{"categories":1147},[100],{"categories":1149},[153],{"categories":1151},[100],{"categories":1153},[],{"categories":1155},[158],{"categories":1157},[170],{"categories":1159},[192],{"categories":1161},[170],{"categories":1163},[233],{"categories":1165},[192],{"categories":1167},[236],{"categories":1169},[100],{"categories":1171},[150],{"categories":1173},[540],{"categories":1175},[100],{"categories":1177},[158],{"categories":1179},[100],{"categories":1181},[170],{"categories":1183},[170],{"categories":1185},[],{"categories":1187},[],{"categories":1189},[158],{"categories":1191},[161],{"categories":1193},[],{"categories":1195},[100],{"categories":1197},[],{"categories":1199},[233],{"categories":1201},[158],{"categories":1203},[170],{"categories":1205},[233],{"categories":1207},[100],{"categories":1209},[100],{"categories":1211},[233],{"categories":1213},[],{"categories":1215},[],{"categories":1217},[192],{"categories":1219},[158],{"categories":1221},[158],{"categories":1223},[100],{"categories":1225},[100],{"categories":1227},[100],{"categories":1229},[100],{"categories":1231},[153],{"categories":1233},[100],{"categories":1235},[100],{"categories":1237},[],{"categories":1239},[170],{"categories":1241},[170],{"categories":1243},[100],{"categories":1245},[170],{"categories":1247},[153],{"categories":1249},[],{"categories":1251},[100],{"categories":1253},[100],{"categories":1255},[100],{"categories":1257},[100],{"categories":1259},[158],{"categories":1261},[150],{"categories":1263},[153],{"categories":1265},[100],{"categories":1267},[192],{"categories":1269},[158],{"categories":1271},[181],{"categories":1273},[261],{"categories":1275},[100],{"categories":1277},[158],{"categories":1279},[100],{"categories":1281},[],{"categories":1283},[233],{"categories":1285},[],{"categories":1287},[100],{"categories":1289},[100],{"categories":1291},[],{"categories":1293},[170],{"categories":1295},[153],{"categories":1297},[1298],"Visual & Generative Media",{"categories":1300},[158],{"categories":1302},[],{"categories":1304},[100],{"categories":1306},[100],{"categories":1308},[170],{"categories":1310},[296],{"categories":1312},[236],{"categories":1314},[540],{"categories":1316},[170],{"categories":1318},[261],{"categories":1320},[100],{"categories":1322},[233],{"categories":1324},[100],{"categories":1326},[100],{"categories":1328},[170],{"categories":1330},[158],{"categories":1332},[100],{"categories":1334},[],{"categories":1336},[],{"categories":1338},[158],{"categories":1340},[170],{"categories":1342},[150],{"categories":1344},[158],{"categories":1346},[504],{"categories":1348},[100],{"categories":1350},[161],{"categories":1352},[100],{"categories":1354},[153],{"categories":1356},[],{"categories":1358},[100],{"categories":1360},[161],{"categories":1362},[100],{"categories":1364},[100],{"categories":1366},[100],{"categories":1368},[161],{"categories":1370},[100],{"categories":1372},[100],{"categories":1374},[261],{"categories":1376},[100],{"categories":1378},[451],{"categories":1380},[100],{"categories":1382},[158],{"categories":1384},[100],{"categories":1386},[100],{"categories":1388},[100],{"categories":1390},[100],{"categories":1392},[233],{"categories":1394},[158],{"categories":1396},[],{"categories":1398},[158],{"categories":1400},[],{"categories":1402},[296],{"categories":1404},[170],{"categories":1406},[],{"categories":1408},[504],{"categories":1410},[100],{"categories":1412},[158],{"categories":1414},[100],{"categories":1416},[233,100],{"categories":1418},[150],{"categories":1420},[100],{"categories":1422},[],{"categories":1424},[100],{"categories":1426},[150],{"categories":1428},[1429],"Medical Imaging & Radiology",{"categories":1431},[100],{"categories":1433},[233],{"categories":1435},[158],{"categories":1437},[170],{"categories":1439},[],{"categories":1441},[100],{"categories":1443},[100],{"categories":1445},[100],{"categories":1447},[],{"categories":1449},[],{"categories":1451},[100],{"categories":1453},[451],{"categories":1455},[100],{"categories":1457},[150],{"categories":1459},[100],{"categories":1461},[100],{"categories":1463},[],{"categories":1465},[158],{"categories":1467},[100],{"categories":1469},[161],{"categories":1471},[170],{"categories":1473},[100],{"categories":1475},[451],{"categories":1477},[100],{"categories":1479},[158],{"categories":1481},[100],{"categories":1483},[233],{"categories":1485},[158],{"categories":1487},[296],{"categories":1489},[233],{"categories":1491},[153],{"categories":1493},[158],{"categories":1495},[100],{"categories":1497},[100],{"categories":1499},[161],{"categories":1501},[100],{"categories":1503},[100],{"categories":1505},[100],{"categories":1507},[158],{"categories":1509},[170],{"categories":1511},[170],{"categories":1513},[100],{"categories":1515},[161],{"categories":1517},[],{"categories":1519},[192],{"categories":1521},[],{"categories":1523},[161],{"categories":1525},[158],{"categories":1527},[158],{"categories":1529},[1125],{"categories":1531},[1125],{"categories":1533},[233],{"categories":1535},[100],{"categories":1537},[100],{"categories":1539},[158],{"categories":1541},[170],{"categories":1543},[233],{"categories":1545},[158],{"categories":1547},[192],{"categories":1549},[],{"categories":1551},[100],{"categories":1553},[],{"categories":1555},[100],{"categories":1557},[100],{"categories":1559},[100],{"categories":1561},[158],{"categories":1563},[1564],"Contract Review & E-Discovery",{"categories":1566},[233],{"categories":1568},[100],{"categories":1570},[150],{"categories":1572},[192],{"categories":1574},[100],{"categories":1576},[100],{"categories":1578},[261],{"categories":1580},[170],{"categories":1582},[100],{"categories":1584},[100],{"categories":1586},[158],{"categories":1588},[158],{"categories":1590},[825],{"categories":1592},[100],{"categories":1594},[100],{"categories":1596},[158],{"categories":1598},[158],{"categories":1600},[100],{"categories":1602},[100],{"categories":1604},[158],{"categories":1606},[100],{"categories":1608},[100],{"categories":1610},[451],{"categories":1612},[432],{"categories":1614},[100],{"categories":1616},[158],{"categories":1618},[100],{"categories":1620},[1621],"Law-Firm Practice & Adoption",{"categories":1623},[100],{"categories":1625},[158],{"categories":1627},[233],{"categories":1629},[100],{"categories":1631},[100],{"categories":1633},[],{"categories":1635},[],{"categories":1637},[170],{"categories":1639},[],{"categories":1641},[158],{"categories":1643},[150],{"categories":1645},[296],{"categories":1647},[100],{"categories":1649},[],{"categories":1651},[150],{"categories":1653},[153],{"categories":1655},[100],{"categories":1657},[261],{"categories":1659},[],{"categories":1661},[153],{"categories":1663},[153],{"categories":1665},[],{"categories":1667},[100],{"categories":1669},[100],{"categories":1671},[170],{"categories":1673},[],{"categories":1675},[],{"categories":1677},[],{"categories":1679},[],{"categories":1681},[100],{"categories":1683},[158],{"categories":1685},[296],{"categories":1687},[100],{"categories":1689},[150],{"categories":1691},[170],{"categories":1693},[100],{"categories":1695},[100],{"categories":1697},[170],{"categories":1699},[161],{"categories":1701},[100],{"categories":1703},[100],{"categories":1705},[848],{"categories":1707},[100],{"categories":1709},[100],{"categories":1711},[261],{"categories":1713},[170],{"categories":1715},[153],{"categories":1717},[100],{"categories":1719},[100],{"categories":1721},[233],{"categories":1723},[100],{"categories":1725},[100],{"categories":1727},[100],{"categories":1729},[158],{"categories":1731},[100,150],{"categories":1733},[451],{"categories":1735},[100],{"categories":1737},[100],{"categories":1739},[170],{"categories":1741},[170],{"categories":1743},[233],{"categories":1745},[158],{"categories":1747},[170],{"categories":1749},[100],{"categories":1751},[100],{"categories":1753},[],{"categories":1755},[],{"categories":1757},[100],{"categories":1759},[],{"categories":1761},[100],{"categories":1763},[170],{"categories":1765},[236],{"categories":1767},[192],{"categories":1769},[233],{"categories":1771},[100],{"categories":1773},[100],{"categories":1775},[170],{"categories":1777},[],{"categories":1779},[158],{"categories":1781},[100],{"categories":1783},[100],{"categories":1785},[100],{"categories":1787},[100],{"categories":1789},[],{"categories":1791},[158],{"categories":1793},[100],{"categories":1795},[100],{"categories":1797},[],{"categories":1799},[158],{"categories":1801},[100],{"categories":1803},[100],{"categories":1805},[153],{"categories":1807},[100],{"categories":1809},[],{"categories":1811},[150],{"categories":1813},[100],{"categories":1815},[100],{"categories":1817},[233],{"categories":1819},[170],{"categories":1821},[100],{"categories":1823},[150],{"categories":1825},[100],{"categories":1827},[170],{"categories":1829},[261],{"categories":1831},[158],{"categories":1833},[158],{"categories":1835},[100],{"categories":1837},[100],{"categories":1839},[100,233],{"categories":1841},[100],{"categories":1843},[192],{"categories":1845},[100],{"categories":1847},[192],{"categories":1849},[158],{"categories":1851},[233],{"categories":1853},[],{"categories":1855},[170],{"categories":1857},[296],{"categories":1859},[233],{"categories":1861},[170],{"categories":1863},[100],{"categories":1865},[161],{"categories":1867},[100],{"categories":1869},[158],{"categories":1871},[],{"categories":1873},[],{"categories":1875},[100],{"categories":1877},[],{"categories":1879},[],{"categories":1881},[161],{"categories":1883},[170],{"categories":1885},[100],{"categories":1887},[158],{"categories":1889},[158],{"categories":1891},[153],{"categories":1893},[158],{"categories":1895},[296],{"categories":1897},[100],{"categories":1899},[100],{"categories":1901},[181],{"categories":1903},[100],{"categories":1905},[100],{"categories":1907},[158],{"categories":1909},[100],{"categories":1911},[100],{"categories":1913},[405],{"categories":1915},[825],{"categories":1917},[],{"categories":1919},[233],{"categories":1921},[1621],{"categories":1923},[170],{"categories":1925},[],{"categories":1927},[],{"categories":1929},[158],{"categories":1931},[],{"categories":1933},[],{"categories":1935},[261],{"categories":1937},[100],{"categories":1939},[261],{"categories":1941},[158],{"categories":1943},[100],{"categories":1945},[170],{"categories":1947},[161],{"categories":1949},[],{"categories":1951},[100],{"categories":1953},[100],{"categories":1955},[170],{"categories":1957},[1564],{"categories":1959},[233],{"categories":1961},[233],{"categories":1963},[100],{"categories":1965},[158],{"categories":1967},[150],{"categories":1969},[100],{"categories":1971},[100],{"categories":1973},[100],{"categories":1975},[233],{"categories":1977},[233],{"categories":1979},[158],{"categories":1981},[158],{"categories":1983},[100],{"categories":1985},[100],{"categories":1987},[],{"categories":1989},[100],{"categories":1991},[],{"categories":1993},[1994],"Interaction & Product Design",{"categories":1996},[100],{"categories":1998},[158],{"categories":2000},[325],{"categories":2002},[192],{"categories":2004},[170],{"categories":2006},[100],{"categories":2008},[100],{"categories":2010},[170],{"categories":2012},[150],{"categories":2014},[158],{"categories":2016},[100],{"categories":2018},[],{"categories":2020},[158],{"categories":2022},[158],{"categories":2024},[],{"categories":2026},[170],{"categories":2028},[100],{"categories":2030},[150],{"categories":2032},[1994],{"categories":2034},[100],{"categories":2036},[150],{"categories":2038},[150],{"categories":2040},[],{"categories":2042},[170],{"categories":2044},[],{"categories":2046},[158],{"categories":2048},[192],{"categories":2050},[100],{"categories":2052},[158],{"categories":2054},[100],{"categories":2056},[158],{"categories":2058},[100],{"categories":2060},[100],{"categories":2062},[192],{"categories":2064},[236],{"categories":2066},[100],{"categories":2068},[161],{"categories":2070},[170],{"categories":2072},[2073],"Coding Agents & Dev Productivity",{"categories":2075},[192],{"categories":2077},[233],{"categories":2079},[100],{"categories":2081},[],{"categories":2083},[100],{"categories":2085},[825],{"categories":2087},[],{"categories":2089},[100],{"categories":2091},[296],{"categories":2093},[100],{"categories":2095},[192],{"categories":2097},[],{"categories":2099},[],{"categories":2101},[100],{"categories":2103},[],{"categories":2105},[158],{"categories":2107},[100],{"categories":2109},[],{"categories":2111},[170],{"categories":2113},[170],{"categories":2115},[100],{"categories":2117},[236],{"categories":2119},[],{"categories":2121},[100],{"categories":2123},[100],{"categories":2125},[100],{"categories":2127},[236],{"categories":2129},[170],{"categories":2131},[],{"categories":2133},[],{"categories":2135},[100],{"categories":2137},[100],{"categories":2139},[158],{"categories":2141},[158],{"categories":2143},[384],{"categories":2145},[170],{"categories":2147},[170],{"categories":2149},[158],{"categories":2151},[192],{"categories":2153},[192],{"categories":2155},[158],{"categories":2157},[158],{"categories":2159},[100],{"categories":2161},[150],{"categories":2163},[1994],{"categories":2165},[100,296],{"categories":2167},[236],{"categories":2169},[],{"categories":2171},[233],{"categories":2173},[170],{"categories":2175},[150],{"categories":2177},[100],{"categories":2179},[158],{"categories":2181},[2182],"The Designer's Role & Craft",{"categories":2184},[233],{"categories":2186},[],{"categories":2188},[158],{"categories":2190},[100],{"categories":2192},[158],{"categories":2194},[158],{"categories":2196},[100],{"categories":2198},[261],{"categories":2200},[100],{"categories":2202},[170],{"categories":2204},[100],{"categories":2206},[233],{"categories":2208},[100],{"categories":2210},[],{"categories":2212},[158],{"categories":2214},[233],{"categories":2216},[100],{"categories":2218},[100],{"categories":2220},[100],{"categories":2222},[2223],"AI UX Patterns",{"categories":2225},[158],{"categories":2227},[158],{"categories":2229},[158],{"categories":2231},[158],{"categories":2233},[261],{"categories":2235},[236],{"categories":2237},[100],{"categories":2239},[158],{"categories":2241},[100],{"categories":2243},[1125],{"categories":2245},[],{"categories":2247},[261],{"categories":2249},[158],{"categories":2251},[192],{"categories":2253},[170],{"categories":2255},[100],{"categories":2257},[158],{"categories":2259},[],{"categories":2261},[],{"categories":2263},[100],{"categories":2265},[158],{"categories":2267},[100],{"categories":2269},[158],{"categories":2271},[384],{"categories":2273},[233],{"categories":2275},[192],{"categories":2277},[170],{"categories":2279},[100],{"categories":2281},[158],{"categories":2283},[158],{"categories":2285},[],{"categories":2287},[100],{"categories":2289},[],{"categories":2291},[],{"categories":2293},[100],{"categories":2295},[100],{"categories":2297},[100],{"categories":2299},[158],{"categories":2301},[170],{"categories":2303},[],{"categories":2305},[],{"categories":2307},[236],{"categories":2309},[181],{"categories":2311},[100],{"categories":2313},[236],{"categories":2315},[192],{"categories":2317},[100],{"categories":2319},[100],{"categories":2321},[158],{"categories":2323},[100],{"categories":2325},[158],{"categories":2327},[100],{"categories":2329},[100],{"categories":2331},[158],{"categories":2333},[],{"categories":2335},[],{"categories":2337},[100],{"categories":2339},[296],{"categories":2341},[100],{"categories":2343},[],{"categories":2345},[],{"categories":2347},[233],{"categories":2349},[848],{"categories":2351},[158],{"categories":2353},[150],{"categories":2355},[2182],{"categories":2357},[],{"categories":2359},[],{"categories":2361},[100],{"categories":2363},[],{"categories":2365},[],{"categories":2367},[170],{"categories":2369},[192],{"categories":2371},[261],{"categories":2373},[153],{"categories":2375},[100],{"categories":2377},[100],{"categories":2379},[153],{"categories":2381},[],{"categories":2383},[233],{"categories":2385},[161],{"categories":2387},[100],{"categories":2389},[100],{"categories":2391},[158],{"categories":2393},[153],{"categories":2395},[100],{"categories":2397},[100],{"categories":2399},[150],{"categories":2401},[100],{"categories":2403},[],{"categories":2405},[150],{"categories":2407},[100],{"categories":2409},[261],{"categories":2411},[158],{"categories":2413},[192],{"categories":2415},[100],{"categories":2417},[100],{"categories":2419},[100],{"categories":2421},[153],{"categories":2423},[100],{"categories":2425},[100],{"categories":2427},[100],{"categories":2429},[158],{"categories":2431},[],{"categories":2433},[100],{"categories":2435},[170],{"categories":2437},[150],{"categories":2439},[100],{"categories":2441},[100],{"categories":2443},[],{"categories":2445},[100],{"categories":2447},[451],{"categories":2449},[153],{"categories":2451},[192],{"categories":2453},[100],{"categories":2455},[100],{"categories":2457},[],{"categories":2459},[153],{"categories":2461},[153],{"categories":2463},[100],{"categories":2465},[100],{"categories":2467},[161],{"categories":2469},[100],{"categories":2471},[100],{"categories":2473},[100],{"categories":2475},[170],{"categories":2477},[170],{"categories":2479},[100],{"categories":2481},[],{"categories":2483},[170],{"categories":2485},[100],{"categories":2487},[170],{"categories":2489},[540],{"categories":2491},[],{"categories":2493},[],{"categories":2495},[100],{"categories":2497},[192],{"categories":2499},[],{"categories":2501},[296],{"categories":2503},[100],{"categories":2505},[100],{"categories":2507},[233],{"categories":2509},[814],{"categories":2511},[],{"categories":2513},[100],{"categories":2515},[100],{"categories":2517},[100],{"categories":2519},[170],{"categories":2521},[100],{"categories":2523},[100],{"categories":2525},[100,296],{"categories":2527},[100],{"categories":2529},[100],{"categories":2531},[233],{"categories":2533},[158],{"categories":2535},[],{"categories":2537},[158],{"categories":2539},[158],{"categories":2541},[100],{"categories":2543},[100],{"categories":2545},[100],{"categories":2547},[236],{"categories":2549},[100],{"categories":2551},[2223],{"categories":2553},[150],{"categories":2555},[236],{"categories":2557},[150],{"categories":2559},[170],{"categories":2561},[233],{"categories":2563},[158],{"categories":2565},[100],{"categories":2567},[],{"categories":2569},[153],{"categories":2571},[100],{"categories":2573},[100],{"categories":2575},[192],{"categories":2577},[100],{"categories":2579},[100],{"categories":2581},[158],{"categories":2583},[100],{"categories":2585},[100],{"categories":2587},[153],{"categories":2589},[],{"categories":2591},[296],{"categories":2593},[100],{"categories":2595},[384],{"categories":2597},[233],{"categories":2599},[233],{"categories":2601},[170],{"categories":2603},[158],{"categories":2605},[100],{"categories":2607},[153],{"categories":2609},[192],{"categories":2611},[100],{"categories":2613},[233],{"categories":2615},[158],{"categories":2617},[100],{"categories":2619},[100],{"categories":2621},[504],{"categories":2623},[],{"categories":2625},[100],{"categories":2627},[100],{"categories":2629},[100],{"categories":2631},[],{"categories":2633},[],{"categories":2635},[100],{"categories":2637},[100],{"categories":2639},[158],{"categories":2641},[100],{"categories":2643},[100],{"categories":2645},[100],{"categories":2647},[170],{"categories":2649},[100],{"categories":2651},[100],{"categories":2653},[158],{"categories":2655},[100],{"categories":2657},[100],{"categories":2659},[100],{"categories":2661},[100],{"categories":2663},[100],{"categories":2665},[],{"categories":2667},[170],{"categories":2669},[236],{"categories":2671},[100],{"categories":2673},[158],{"categories":2675},[100],{"categories":2677},[],{"categories":2679},[],{"categories":2681},[100],{"categories":2683},[100],{"categories":2685},[100],{"categories":2687},[192],{"categories":2689},[],{"categories":2691},[100],{"categories":2693},[233],{"categories":2695},[100],{"categories":2697},[296],{"categories":2699},[1621],{"categories":2701},[192],{"categories":2703},[170],{"categories":2705},[170],{"categories":2707},[170],{"categories":2709},[192],{"categories":2711},[192],{"categories":2713},[296],{"categories":2715},[],{"categories":2717},[192],{"categories":2719},[100],{"categories":2721},[150],{"categories":2723},[170],{"categories":2725},[100],{"categories":2727},[192],{"categories":2729},[],{"categories":2731},[100],{"categories":2733},[170],{"categories":2735},[170],{"categories":2737},[236],{"categories":2739},[100],{"categories":2741},[192],{"categories":2743},[100],{"categories":2745},[170],{"categories":2747},[158],{"categories":2749},[192],{"categories":2751},[158],{"categories":2753},[296],{"categories":2755},[158],{"categories":2757},[100],{"categories":2759},[100],{"categories":2761},[170],{"categories":2763},[100],{"categories":2765},[],{"categories":2767},[158],{"categories":2769},[153],{"categories":2771},[170],{"categories":2773},[],{"categories":2775},[],{"categories":2777},[100],{"categories":2779},[158],{"categories":2781},[100],{"categories":2783},[2784],"Frameworks & Tooling",{"categories":2786},[100],{"categories":2788},[100],{"categories":2790},[170],{"categories":2792},[100],{"categories":2794},[100],{"categories":2796},[],{"categories":2798},[236],{"categories":2800},[236],{"categories":2802},[150],{"categories":2804},[158],{"categories":2806},[233],{"categories":2808},[],{"categories":2810},[1621],{"categories":2812},[100],{"categories":2814},[170],{"categories":2816},[100],{"categories":2818},[296],{"categories":2820},[296],{"categories":2822},[],{"categories":2824},[158],{"categories":2826},[192],{"categories":2828},[192],{"categories":2830},[100],{"categories":2832},[158],{"categories":2834},[],{"categories":2836},[233],{"categories":2838},[100],{"categories":2840},[100],{"categories":2842},[],{"categories":2844},[100],{"categories":2846},[100],{"categories":2848},[],{"categories":2850},[170],{"categories":2852},[100],{"categories":2854},[170],{"categories":2856},[296],{"categories":2858},[100],{"categories":2860},[100],{"categories":2862},[170],{"categories":2864},[153],{"categories":2866},[100],{"categories":2868},[1621],{"categories":2870},[],{"categories":2872},[158],{"categories":2874},[150],{"categories":2876},[100],{"categories":2878},[150],{"categories":2880},[],{"categories":2882},[158],{"categories":2884},[100],{"categories":2886},[2887],"AI Design Tooling",{"categories":2889},[233],{"categories":2891},[100],{"categories":2893},[100],{"categories":2895},[170],{"categories":2897},[233],{"categories":2899},[100],{"categories":2901},[170],{"categories":2903},[192],{"categories":2905},[161],{"categories":2907},[170],{"categories":2909},[100],{"categories":2911},[158],{"categories":2913},[],{"categories":2915},[100],{"categories":2917},[100],{"categories":2919},[158],{"categories":2921},[100],{"categories":2923},[100],{"categories":2925},[100],{"categories":2927},[],{"categories":2929},[158],{"categories":2931},[2784],{"categories":2933},[100],{"categories":2935},[158],{"categories":2937},[158],{"categories":2939},[170],{"categories":2941},[170],{"categories":2943},[],{"categories":2945},[170],{"categories":2947},[100],{"categories":2949},[100],{"categories":2951},[158],{"categories":2953},[153],{"categories":2955},[100],{"categories":2957},[],{"categories":2959},[100],{"categories":2961},[100],{"categories":2963},[1994],{"categories":2965},[],{"categories":2967},[100],{"categories":2969},[100],{"categories":2971},[100],{"categories":2973},[100],{"categories":2975},[],{"categories":2977},[100],{"categories":2979},[100],{"categories":2981},[100],{"categories":2983},[261],{"categories":2985},[192],{"categories":2987},[100],{"categories":2989},[100],{"categories":2991},[1621],{"categories":2993},[150],{"categories":2995},[100],{"categories":2997},[100],{"categories":2999},[236],{"categories":3001},[100],{"categories":3003},[192],{"categories":3005},[158],{"categories":3007},[],{"categories":3009},[100],{"categories":3011},[100],{"categories":3013},[233],{"categories":3015},[100],{"categories":3017},[261],{"categories":3019},[100],{"categories":3021},[158],{"categories":3023},[],{"categories":3025},[],{"categories":3027},[],{"categories":3029},[150],{"categories":3031},[192],{"categories":3033},[158],{"categories":3035},[100],{"categories":3037},[100],{"categories":3039},[100],{"categories":3041},[405],{"categories":3043},[233],{"categories":3045},[158],{"categories":3047},[100],{"categories":3049},[],{"categories":3051},[158],{"categories":3053},[158],{"categories":3055},[],{"categories":3057},[100],{"categories":3059},[158],{"categories":3061},[100],{"categories":3063},[],{"categories":3065},[100],{"categories":3067},[100],{"categories":3069},[192],{"categories":3071},[233],{"categories":3073},[158],{"categories":3075},[233],{"categories":3077},[158],{"categories":3079},[100],{"categories":3081},[153],{"categories":3083},[],{"categories":3085},[],{"categories":3087},[100],{"categories":3089},[100],{"categories":3091},[150],{"categories":3093},[158],{"categories":3095},[192],{"categories":3097},[],{"categories":3099},[233],{"categories":3101},[],{"categories":3103},[170],{"categories":3105},[100],{"categories":3107},[170],{"categories":3109},[233],{"categories":3111},[170],{"categories":3113},[100],{"categories":3115},[],{"categories":3117},[100],{"categories":3119},[100],{"categories":3121},[],{"categories":3123},[100],{"categories":3125},[261],{"categories":3127},[100],{"categories":3129},[296],{"categories":3131},[170],{"categories":3133},[],{"categories":3135},[158],{"categories":3137},[100],{"categories":3139},[150],{"categories":3141},[504],{"categories":3143},[100],{"categories":3145},[158],{"categories":3147},[158],{"categories":3149},[100],{"categories":3151},[100],{"categories":3153},[],{"categories":3155},[100],{"categories":3157},[150],{"categories":3159},[100],{"categories":3161},[153],{"categories":3163},[170],{"categories":3165},[233],{"categories":3167},[],{"categories":3169},[],{"categories":3171},[],{"categories":3173},[158],{"categories":3175},[170],{"categories":3177},[233],{"categories":3179},[192],{"categories":3181},[100],{"categories":3183},[192],{"categories":3185},[158],{"categories":3187},[233],{"categories":3189},[100],{"categories":3191},[],{"categories":3193},[100],{"categories":3195},[181],{"categories":3197},[158],{"categories":3199},[233],{"categories":3201},[192],{"categories":3203},[153],{"categories":3205},[170],{"categories":3207},[100],{"categories":3209},[100],{"categories":3211},[192],{"categories":3213},[261],{"categories":3215},[],{"categories":3217},[],{"categories":3219},[236],{"categories":3221},[451],{"categories":3223},[100],{"categories":3225},[158],{"categories":3227},[100,170],{"categories":3229},[192],{"categories":3231},[100],{"categories":3233},[100],{"categories":3235},[100],{"categories":3237},[100],{"categories":3239},[158],{"categories":3241},[100],{"categories":3243},[158],{"categories":3245},[100],{"categories":3247},[100],{"categories":3249},[],{"categories":3251},[100],{"categories":3253},[1125],{"categories":3255},[170],{"categories":3257},[233],{"categories":3259},[100],{"categories":3261},[100],{"categories":3263},[100],{"categories":3265},[236],{"categories":3267},[158],{"categories":3269},[261],{"categories":3271},[296],{"categories":3273},[],{"categories":3275},[100],{"categories":3277},[153],{"categories":3279},[158],{"categories":3281},[150],{"categories":3283},[158],{"categories":3285},[100],{"categories":3287},[158],{"categories":3289},[161],{"categories":3291},[170],{"categories":3293},[100],{"categories":3295},[100],{"categories":3297},[],{"categories":3299},[],{"categories":3301},[],{"categories":3303},[296],{"categories":3305},[100],{"categories":3307},[192],{"categories":3309},[100],{"categories":3311},[100],{"categories":3313},[100],{"categories":3315},[100],{"categories":3317},[],{"categories":3319},[236],{"categories":3321},[153],{"categories":3323},[158],{"categories":3325},[100],{"categories":3327},[],{"categories":3329},[100],{"categories":3331},[158],{"categories":3333},[100],{"categories":3335},[296],{"categories":3337},[],{"categories":3339},[233],{"categories":3341},[233],{"categories":3343},[],{"categories":3345},[170],{"categories":3347},[100],{"categories":3349},[233],{"categories":3351},[100],{"categories":3353},[153],{"categories":3355},[158],{"categories":3357},[100],{"categories":3359},[],{"categories":3361},[192],{"categories":3363},[100],{"categories":3365},[100],{"categories":3367},[100],{"categories":3369},[233],{"categories":3371},[158],{"categories":3373},[192],{"categories":3375},[],{"categories":3377},[158],{"categories":3379},[153],{"categories":3381},[158],{"categories":3383},[233],{"categories":3385},[100],{"categories":3387},[100],{"categories":3389},[100],{"categories":3391},[451],{"categories":3393},[100],{"categories":3395},[],{"categories":3397},[100],{"categories":3399},[100],{"categories":3401},[296],{"categories":3403},[192],{"categories":3405},[236],{"categories":3407},[540],{"categories":3409},[236],{"categories":3411},[100],{"categories":3413},[],{"categories":3415},[],{"categories":3417},[],{"categories":3419},[158],{"categories":3421},[158],{"categories":3423},[170],{"categories":3425},[100],{"categories":3427},[432],{"categories":3429},[170],{"categories":3431},[100],{"categories":3433},[100],{"categories":3435},[100],{"categories":3437},[100],{"categories":3439},[158],{"categories":3441},[],{"categories":3443},[],{"categories":3445},[100],{"categories":3447},[],{"categories":3449},[100],{"categories":3451},[158],{"categories":3453},[233],{"categories":3455},[100],{"categories":3457},[100],{"categories":3459},[],{"categories":3461},[158],{"categories":3463},[161],{"categories":3465},[100],{"categories":3467},[233],{"categories":3469},[100],{"categories":3471},[158],{"categories":3473},[153],{"categories":3475},[100],{"categories":3477},[261],{"categories":3479},[158],{"categories":3481},[100],{"categories":3483},[100],{"categories":3485},[814],{"categories":3487},[100],{"categories":3489},[158],{"categories":3491},[100],{"categories":3493},[170],{"categories":3495},[100],{"categories":3497},[504],{"categories":3499},[233],{"categories":3501},[],{"categories":3503},[192],{"categories":3505},[451],{"categories":3507},[158],{"categories":3509},[100],{"categories":3511},[],{"categories":3513},[192],{"categories":3515},[384],{"categories":3517},[158],{"categories":3519},[158],{"categories":3521},[100],{"categories":3523},[100],{"categories":3525},[158],{"categories":3527},[],{"categories":3529},[153],{"categories":3531},[100],{"categories":3533},[153],{"categories":3535},[158],{"categories":3537},[],{"categories":3539},[170],{"categories":3541},[100],{"categories":3543},[100],{"categories":3545},[150],{"categories":3547},[192],{"categories":3549},[296],{"categories":3551},[181],{"categories":3553},[158],{"categories":3555},[158],{"categories":3557},[100],{"categories":3559},[158],{"categories":3561},[100],{"categories":3563},[150],{"categories":3565},[],{"categories":3567},[100],{"categories":3569},[100],{"categories":3571},[100],{"categories":3573},[100],{"categories":3575},[],{"categories":3577},[],{"categories":3579},[233],{"categories":3581},[158],{"categories":3583},[100,153],{"categories":3585},[158],{"categories":3587},[100],{"categories":3589},[],{"categories":3591},[150],{"categories":3593},[236],{"categories":3595},[153],{"categories":3597},[100],{"categories":3599},[170],{"categories":3601},[100],{"categories":3603},[100],{"categories":3605},[158],{"categories":3607},[100],{"categories":3609},[100],{"categories":3611},[100],{"categories":3613},[192],{"categories":3615},[1125],{"categories":3617},[158],{"categories":3619},[100],{"categories":3621},[],{"categories":3623},[],{"categories":3625},[100],{"categories":3627},[158],{"categories":3629},[100],{"categories":3631},[100],{"categories":3633},[296],{"categories":3635},[],{"categories":3637},[100],{"categories":3639},[158],{"categories":3641},[181],{"categories":3643},[158],{"categories":3645},[451],{"categories":3647},[],{"categories":3649},[405],{"categories":3651},[158],{"categories":3653},[100],{"categories":3655},[261],{"categories":3657},[100],{"categories":3659},[236],{"categories":3661},[158],{"categories":3663},[100],{"categories":3665},[451],{"categories":3667},[100],{"categories":3669},[296],{"categories":3671},[],{"categories":3673},[100],{"categories":3675},[261],{"categories":3677},[233],{"categories":3679},[100],{"categories":3681},[100],{"categories":3683},[100],{"categories":3685},[],{"categories":3687},[261],{"categories":3689},[192],{"categories":3691},[100],{"categories":3693},[100],{"categories":3695},[540],{"categories":3697},[150],{"categories":3699},[100],{"categories":3701},[],{"categories":3703},[],{"categories":3705},[233],{"categories":3707},[100],{"categories":3709},[236],{"categories":3711},[261],{"categories":3713},[158],{"categories":3715},[100],{"categories":3717},[261],{"categories":3719},[192],{"categories":3721},[],{"categories":3723},[100],{"categories":3725},[100],{"categories":3727},[],{"categories":3729},[100],{"categories":3731},[100],{"categories":3733},[563],{"categories":3735},[100],{"categories":3737},[100],{"categories":3739},[158],{"categories":3741},[170],{"categories":3743},[451],{"categories":3745},[100],{"categories":3747},[100],{"categories":3749},[100],{"categories":3751},[],{"categories":3753},[100,170],{"categories":3755},[192],{"categories":3757},[158],{"categories":3759},[170],{"categories":3761},[158],{"categories":3763},[848],{"categories":3765},[170],{"categories":3767},[100],{"categories":3769},[150],{"categories":3771},[],{"categories":3773},[],{"categories":3775},[158],{"categories":3777},[100],{"categories":3779},[170],{"categories":3781},[100],{"categories":3783},[150],{"categories":3785},[170],{"categories":3787},[170],{"categories":3789},[100],{"categories":3791},[261],{"categories":3793},[100],{"categories":3795},[170],{"categories":3797},[100],{"categories":3799},[],{"categories":3801},[100],{"categories":3803},[233,100],{"categories":3805},[296],{"categories":3807},[150],{"categories":3809},[],{"categories":3811},[100],{"categories":3813},[100],{"categories":3815},[153],{"categories":3817},[153],{"categories":3819},[100],{"categories":3821},[100],{"categories":3823},[384],{"categories":3825},[100],{"categories":3827},[153],{"categories":3829},[170],{"categories":3831},[236],{"categories":3833},[158],{"categories":3835},[170],{"categories":3837},[100],{"categories":3839},[100],{"categories":3841},[192],{"categories":3843},[261],{"categories":3845},[233],{"categories":3847},[100],{"categories":3849},[100],{"categories":3851},[100],{"categories":3853},[100],{"categories":3855},[150],{"categories":3857},[100],{"categories":3859},[158],{"categories":3861},[158],{"categories":3863},[170],{"categories":3865},[192],{"categories":3867},[170],{"categories":3869},[170],{"categories":3871},[100],{"categories":3873},[],{"categories":3875},[],{"categories":3877},[236],{"categories":3879},[100],{"categories":3881},[170],{"categories":3883},[100],{"categories":3885},[233],{"categories":3887},[451],{"categories":3889},[405],{"categories":3891},[384],{"categories":3893},[100],{"categories":3895},[100],{"categories":3897},[100],{"categories":3899},[236],{"categories":3901},[100],{"categories":3903},[100],{"categories":3905},[100],{"categories":3907},[100],{"categories":3909},[100],{"categories":3911},[100],{"categories":3913},[158],{"categories":3915},[150],{"categories":3917},[158],{"categories":3919},[100,153],{"categories":3921},[],{"categories":3923},[233],{"categories":3925},[],{"categories":3927},[161],{"categories":3929},[100],{"categories":3931},[192],{"categories":3933},[150],{"categories":3935},[150],{"categories":3937},[158],{"categories":3939},[158],{"categories":3941},[158],{"categories":3943},[100],{"categories":3945},[100],{"categories":3947},[153],{"categories":3949},[158],{"categories":3951},[170],{"categories":3953},[261],{"categories":3955},[100],{"categories":3957},[],{"categories":3959},[192],{"categories":3961},[100],{"categories":3963},[100],{"categories":3965},[100],{"categories":3967},[100],{"categories":3969},[100],{"categories":3971},[170],{"categories":3973},[192],{"categories":3975},[170],{"categories":3977},[170],{"categories":3979},[100],{"categories":3981},[100],{"categories":3983},[100],{"categories":3985},[405],{"categories":3987},[100],{"categories":3989},[158],{"categories":3991},[192],{"categories":3993},[100],{"categories":3995},[100],{"categories":3997},[100],{"categories":3999},[158],{"categories":4001},[100],{"categories":4003},[100],{"categories":4005},[100],{"categories":4007},[2784],{"categories":4009},[4010],"Clinical AI",{"categories":4012},[233],{"categories":4014},[100],{"categories":4016},[100],{"categories":4018},[100],{"categories":4020},[296],{"categories":4022},[2223],{"categories":4024},[100],{"categories":4026},[161],{"categories":4028},[100],{"categories":4030},[158],{"categories":4032},[100],{"categories":4034},[100],{"categories":4036},[192],{"categories":4038},[100],{"categories":4040},[158],{"categories":4042},[170],{"categories":4044},[261],{"categories":4046},[100],{"categories":4048},[100],{"categories":4050},[153],{"categories":4052},[100],{"categories":4054},[100],{"categories":4056},[504],{"categories":4058},[100],{"categories":4060},[],{"categories":4062},[100],{"categories":4064},[170],{"categories":4066},[150],{"categories":4068},[100],{"categories":4070},[],{"categories":4072},[],{"categories":4074},[100],{"categories":4076},[],{"categories":4078},[153],{"categories":4080},[100],{"categories":4082},[158],{"categories":4084},[192],{"categories":4086},[192],{"categories":4088},[192],{"categories":4090},[192],{"categories":4092},[],{"categories":4094},[150],{"categories":4096},[158],{"categories":4098},[192],{"categories":4100},[100],{"categories":4102},[563],{"categories":4104},[161],{"categories":4106},[100],{"categories":4108},[150],{"categories":4110},[100],{"categories":4112},[158],{"categories":4114},[100],{"categories":4116},[100],{"categories":4118},[100,158],{"categories":4120},[158],{"categories":4122},[296],{"categories":4124},[192],{"categories":4126},[158],{"categories":4128},[192],{"categories":4130},[158],{"categories":4132},[100],{"categories":4134},[],{"categories":4136},[192],{"categories":4138},[261],{"categories":4140},[150],{"categories":4142},[100],{"categories":4144},[100],{"categories":4146},[],{"categories":4148},[170],{"categories":4150},[],{"categories":4152},[150],{"categories":4154},[158],{"categories":4156},[192],{"categories":4158},[100],{"categories":4160},[192],{"categories":4162},[150],{"categories":4164},[192],{"categories":4166},[192],{"categories":4168},[],{"categories":4170},[153],{"categories":4172},[158],{"categories":4174},[192],{"categories":4176},[192],{"categories":4178},[192],{"categories":4180},[192],{"categories":4182},[192],{"categories":4184},[192],{"categories":4186},[192],{"categories":4188},[192],{"categories":4190},[192],{"categories":4192},[192],{"categories":4194},[236],{"categories":4196},[150],{"categories":4198},[100],{"categories":4200},[100],{"categories":4202},[158],{"categories":4204},[158],{"categories":4206},[],{"categories":4208},[100],{"categories":4210},[100,150],{"categories":4212},[],{"categories":4214},[158],{"categories":4216},[100],{"categories":4218},[192],{"categories":4220},[158],{"categories":4222},[848],{"categories":4224},[100],{"categories":4226},[100],{"categories":4228},[100],{"categories":4230},[100],{"categories":4232},[100],{"categories":4234},[384],{"categories":4236},[100],{"categories":4238},[158],{"categories":4240},[153],{"categories":4242},[158],{"categories":4244},[158],{"categories":4246},[],{"categories":4248},[158],{"categories":4250},[233],{"categories":4252},[192],{"categories":4254},[100],{"categories":4256},[],{"categories":4258},[161],{"categories":4260},[],{"categories":4262},[170],{"categories":4264},[158],{"categories":4266},[233],{"categories":4268},[100],{"categories":4270},[],{"categories":4272},[100],{"categories":4274},[],{"categories":4276},[261],{"categories":4278},[100],{"categories":4280},[],{"categories":4282},[],{"categories":4284},[192],{"categories":4286},[150],{"categories":4288},[100],{"categories":4290},[100],{"categories":4292},[153],{"categories":4294},[100],{"categories":4296},[100],{"categories":4298},[100],{"categories":4300},[153],{"categories":4302},[153],{"categories":4304},[233],{"categories":4306},[],{"categories":4308},[100],{"categories":4310},[192],{"categories":4312},[],{"categories":4314},[100],{"categories":4316},[100],{"categories":4318},[233],{"categories":4320},[100],{"categories":4322},[261],{"categories":4324},[100],{"categories":4326},[296],{"categories":4328},[],{"categories":4330},[158],{"categories":4332},[261],{"categories":4334},[170],{"categories":4336},[],{"categories":4338},[100],{"categories":4340},[],{"categories":4342},[158],{"categories":4344},[233],{"categories":4346},[170],{"categories":4348},[],{"categories":4350},[2784],{"categories":4352},[153],{"categories":4354},[150],{"categories":4356},[100],{"categories":4358},[236],{"categories":4360},[158],{"categories":4362},[233],{"categories":4364},[170],{"categories":4366},[],{"categories":4368},[],{"categories":4370},[100],{"categories":4372},[150],{"categories":4374},[100],{"categories":4376},[261],{"categories":4378},[],{"categories":4380},[158],{"categories":4382},[158],{"categories":4384},[100],{"categories":4386},[158],{"categories":4388},[100],{"categories":4390},[192],{"categories":4392},[170],{"categories":4394},[100],{"categories":4396},[158],{"categories":4398},[161],{"categories":4400},[100],{"categories":4402},[100],{"categories":4404},[158],{"categories":4406},[100],{"categories":4408},[161],{"categories":4410},[261],{"categories":4412},[192],{"categories":4414},[],{"categories":4416},[261],{"categories":4418},[100],{"categories":4420},[],{"categories":4422},[170],{"categories":4424},[158],{"categories":4426},[],{"categories":4428},[100],{"categories":4430},[100],{"categories":4432},[100],{"categories":4434},[100],{"categories":4436},[158],{"categories":4438},[153],{"categories":4440},[150],{"categories":4442},[100],{"categories":4444},[233],{"categories":4446},[170],{"categories":4448},[170],{"categories":4450},[100],{"categories":4452},[236],{"categories":4454},[158],{"categories":4456},[100],{"categories":4458},[100],{"categories":4460},[158],{"categories":4462},[100],{"categories":4464},[153],{"categories":4466},[233],{"categories":4468},[170],{"categories":4470},[158],{"categories":4472},[100],{"categories":4474},[161],{"categories":4476},[100],{"categories":4478},[158],{"categories":4480},[100],{"categories":4482},[192],{"categories":4484},[],{"categories":4486},[150],{"categories":4488},[100],{"categories":4490},[100],{"categories":4492},[100],{"categories":4494},[170],{"categories":4496},[170],{"categories":4498},[100],{"categories":4500},[170],{"categories":4502},[100],{"categories":4504},[158],{"categories":4506},[100],{"categories":4508},[100],{"categories":4510},[100],{"categories":4512},[100],{"categories":4514},[100],{"categories":4516},[],{"categories":4518},[100],{"categories":4520},[233],{"categories":4522},[153],{"categories":4524},[192],{"categories":4526},[100],{"categories":4528},[158],{"categories":4530},[100],{"categories":4532},[100],{"categories":4534},[233],{"categories":4536},[158],{"categories":4538},[100],{"categories":4540},[261],{"categories":4542},[100],{"categories":4544},[236],{"categories":4546},[100],{"categories":4548},[100],{"categories":4550},[192],{"categories":4552},[100],{"categories":4554},[100],{"categories":4556},[100],{"categories":4558},[158],{"categories":4560},[296],{"categories":4562},[100],{"categories":4564},[170],{"categories":4566},[158],{"categories":4568},[236],{"categories":4570},[],{"categories":4572},[158],{"categories":4574},[170],{"categories":4576},[100],{"categories":4578},[100],{"categories":4580},[2073],{"categories":4582},[233],{"categories":4584},[325],{"categories":4586},[100],{"categories":4588},[100],{"categories":4590},[150],{"categories":4592},[100],{"categories":4594},[170],{"categories":4596},[153],{"categories":4598},[170],{"categories":4600},[100],{"categories":4602},[],{"categories":4604},[158],{"categories":4606},[158],{"categories":4608},[100],{"categories":4610},[100],{"categories":4612},[236],{"categories":4614},[],{"categories":4616},[192],{"categories":4618},[],{"categories":4620},[192],{"categories":4622},[100],{"categories":4624},[100],{"categories":4626},[158],{"categories":4628},[100],{"categories":4630},[158],{"categories":4632},[158],{"categories":4634},[],{"categories":4636},[192],{"categories":4638},[100],{"categories":4640},[],{"categories":4642},[100],{"categories":4644},[100],{"categories":4646},[],{"categories":4648},[233],{"categories":4650},[170],{"categories":4652},[158],{"categories":4654},[100],{"categories":4656},[100],{"categories":4658},[261],{"categories":4660},[100],{"categories":4662},[100],{"categories":4664},[100],{"categories":4666},[150],{"categories":4668},[100],{"categories":4670},[],{"categories":4672},[100],{"categories":4674},[100],{"categories":4676},[],{"categories":4678},[150],{"categories":4680},[192],{"categories":4682},[170],{"categories":4684},[161],{"categories":4686},[451],{"categories":4688},[100],{"categories":4690},[100],{"categories":4692},[100],{"categories":4694},[170],{"categories":4696},[192],{"categories":4698},[233],{"categories":4700},[100],{"categories":4702},[100],{"categories":4704},[100],{"categories":4706},[192],{"categories":4708},[233],{"categories":4710},[100],{"categories":4712},[100],{"categories":4714},[192],{"categories":4716},[233],{"categories":4718},[100],{"categories":4720},[192],{"categories":4722},[158],{"categories":4724},[158],{"categories":4726},[158],{"categories":4728},[170],{"categories":4730},[192],{"categories":4732},[158],{"categories":4734},[158],{"categories":4736},[100],{"categories":4738},[170],{"categories":4740},[233],{"categories":4742},[100],{"categories":4744},[100],{"categories":4746},[],{"categories":4748},[158],{"categories":4750},[],{"categories":4752},[100],{"categories":4754},[100],{"categories":4756},[],{"categories":4758},[],{"categories":4760},[158],{"categories":4762},[153],{"categories":4764},[158],{"categories":4766},[4767],"Liability & Ethics",{"categories":4769},[100],{"categories":4771},[158],{"categories":4773},[150],{"categories":4775},[158],{"categories":4777},[153],{"categories":4779},[261],{"categories":4781},[158],{"categories":4783},[100],{"categories":4785},[],{"categories":4787},[540],{"categories":4789},[158],{"categories":4791},[],{"categories":4793},[150],{"categories":4795},[158],{"categories":4797},[],{"categories":4799},[158],{"categories":4801},[100],{"categories":4803},[100],{"categories":4805},[100],{"categories":4807},[192],{"categories":4809},[100],{"categories":4811},[100],{"categories":4813},[158],{"categories":4815},[100],{"categories":4817},[100],{"categories":4819},[100],{"categories":4821},[192],{"categories":4823},[158],{"categories":4825},[170],{"categories":4827},[233],{"categories":4829},[150],{"categories":4831},[100],{"categories":4833},[100],{"categories":4835},[],{"categories":4837},[158],{"categories":4839},[158],{"categories":4841},[158],{"categories":4843},[451],{"categories":4845},[233],{"categories":4847},[158],{"categories":4849},[296],{"categories":4851},[192],{"categories":4853},[100],{"categories":4855},[233],{"categories":4857},[100],{"categories":4859},[150],{"categories":4861},[],{"categories":4863},[158],{"categories":4865},[100],{"categories":4867},[100],{"categories":4869},[158],{"categories":4871},[100],{"categories":4873},[233],{"categories":4875},[],{"categories":4877},[158],{"categories":4879},[161],{"categories":4881},[192],{"categories":4883},[158],{"categories":4885},[153],{"categories":4887},[],{"categories":4889},[100],{"categories":4891},[161],{"categories":4893},[100],{"categories":4895},[158],{"categories":4897},[192],{"categories":4899},[150],{"categories":4901},[296],{"categories":4903},[100],{"categories":4905},[100],{"categories":4907},[100],{"categories":4909},[192],{"categories":4911},[153],{"categories":4913},[100],{"categories":4915},[233],{"categories":4917},[192],{"categories":4919},[296],{"categories":4921},[100],{"categories":4923},[158],{"categories":4925},[],{"categories":4927},[504],{"categories":4929},[],{"categories":4931},[100],{"categories":4933},[296],{"categories":4935},[236],{"categories":4937},[158],{"categories":4939},[158],{"categories":4941},[4942],"Design News & Tools",{"categories":4944},[100],{"categories":4946},[192],{"categories":4948},[100],{"categories":4950},[100],{"categories":4952},[150],{"categories":4954},[100],{"categories":4956},[233],{"categories":4958},[158],{"categories":4960},[158],{"categories":4962},[233],{"categories":4964},[100],{"categories":4966},[451],{"categories":4968},[158],{"categories":4970},[100],{"categories":4972},[100],{"categories":4974},[451],{"categories":4976},[100],{"categories":4978},[261],{"categories":4980},[100],{"categories":4982},[158],{"categories":4984},[],{"categories":4986},[100],{"categories":4988},[100],{"categories":4990},[100],{"categories":4992},[192],{"categories":4994},[150],{"categories":4996},[],{"categories":4998},[100],{"categories":5000},[100],{"categories":5002},[170],{"categories":5004},[563],{"categories":5006},[170],{"categories":5008},[233],{"categories":5010},[100],{"categories":5012},[100,158],{"categories":5014},[261,153],{"categories":5016},[100],{"categories":5018},[100],{"categories":5020},[100],{"categories":5022},[],{"categories":5024},[158],{"categories":5026},[],{"categories":5028},[170],{"categories":5030},[100],{"categories":5032},[170],{"categories":5034},[],{"categories":5036},[158],{"categories":5038},[100],{"categories":5040},[192],{"categories":5042},[100],{"categories":5044},[],{"categories":5046},[158],{"categories":5048},[100],{"categories":5050},[],{"categories":5052},[233],{"categories":5054},[100],{"categories":5056},[100],{"categories":5058},[158],{"categories":5060},[100],{"categories":5062},[100],{"categories":5064},[150],{"categories":5066},[158],{"categories":5068},[100],{"categories":5070},[],{"categories":5072},[296],{"categories":5074},[261],{"categories":5076},[153],{"categories":5078},[153],{"categories":5080},[100],{"categories":5082},[150],{"categories":5084},[150],{"categories":5086},[100],{"categories":5088},[158],{"categories":5090},[100],{"categories":5092},[100],{"categories":5094},[100],{"categories":5096},[170],{"categories":5098},[100],{"categories":5100},[150],{"categories":5102},[100],{"categories":5104},[158],{"categories":5106},[100],{"categories":5108},[261],{"categories":5110},[100],{"categories":5112},[192],{"categories":5114},[100],{"categories":5116},[100],{"categories":5118},[158],{"categories":5120},[100],{"categories":5122},[158],{"categories":5124},[],{"categories":5126},[170],{"categories":5128},[],{"categories":5130},[170],{"categories":5132},[158],{"categories":5134},[150],{"categories":5136},[],{"categories":5138},[236],{"categories":5140},[296],{"categories":5142},[100],{"categories":5144},[170],{"categories":5146},[100],{"categories":5148},[],{"categories":5150},[192],{"categories":5152},[158],{"categories":5154},[170],{"categories":5156},[233],{"categories":5158},[100],{"categories":5160},[100],{"categories":5162},[158],{"categories":5164},[170],{"categories":5166},[158],{"categories":5168},[192],{"categories":5170},[100],{"categories":5172},[161],{"categories":5174},[150],{"categories":5176},[161],{"categories":5178},[192],{"categories":5180},[170],{"categories":5182},[100],{"categories":5184},[233],{"categories":5186},[153],{"categories":5188},[100],{"categories":5190},[100],{"categories":5192},[100],{"categories":5194},[100],{"categories":5196},[100],{"categories":5198},[100],{"categories":5200},[158],{"categories":5202},[100],{"categories":5204},[158],{"categories":5206},[100],{"categories":5208},[100],{"categories":5210},[150],{"categories":5212},[100],{"categories":5214},[158],{"categories":5216},[158],{"categories":5218},[233],{"categories":5220},[158],{"categories":5222},[158],{"categories":5224},[150],{"categories":5226},[158],{"categories":5228},[233],{"categories":5230},[],{"categories":5232},[100],{"categories":5234},[236],{"categories":5236},[451],{"categories":5238},[100],{"categories":5240},[100],{"categories":5242},[100],{"categories":5244},[170],{"categories":5246},[100],{"categories":5248},[],{"categories":5250},[158],{"categories":5252},[261],{"categories":5254},[100],{"categories":5256},[192],{"categories":5258},[158],{"categories":5260},[100],{"categories":5262},[261],{"categories":5264},[158],{"categories":5266},[153],{"categories":5268},[153],{"categories":5270},[100],{"categories":5272},[100],{"categories":5274},[100],{"categories":5276},[150],{"categories":5278},[],{"categories":5280},[100],{"categories":5282},[100],{"categories":5284},[158],{"categories":5286},[158],{"categories":5288},[100],{"categories":5290},[100],{"categories":5292},[100],{"categories":5294},[170],{"categories":5296},[],{"categories":5298},[150],{"categories":5300},[100],{"categories":5302},[100],{"categories":5304},[158],{"categories":5306},[158],{"categories":5308},[],{"categories":5310},[170],{"categories":5312},[170],{"categories":5314},[100],{"categories":5316},[261],{"categories":5318},[153],{"categories":5320},[233],{"categories":5322},[],{"categories":5324},[100],{"categories":5326},[158],{"categories":5328},[150],{"categories":5330},[100],{"categories":5332},[100],{"categories":5334},[170],{"categories":5336},[150],{"categories":5338},[192],{"categories":5340},[236],{"categories":5342},[192],{"categories":5344},[158],{"categories":5346},[],{"categories":5348},[192],{"categories":5350},[158],{"categories":5352},[233],{"categories":5354},[236],{"categories":5356},[100],{"categories":5358},[],{"categories":5360},[158],{"categories":5362},[158],{"categories":5364},[2784],{"categories":5366},[192],{"categories":5368},[170],{"categories":5370},[100],{"categories":5372},[100],{"categories":5374},[100],{"categories":5376},[100],{"categories":5378},[153],{"categories":5380},[100],{"categories":5382},[150],{"categories":5384},[1621],{"categories":5386},[296],{"categories":5388},[150],{"categories":5390},[],{"categories":5392},[],{"categories":5394},[192],{"categories":5396},[158],{"categories":5398},[233],{"categories":5400},[100],{"categories":5402},[192],{"categories":5404},[],{"categories":5406},[158],{"categories":5408},[158],{"categories":5410},[158],{"categories":5412},[],{"categories":5414},[100],{"categories":5416},[],{"categories":5418},[192],{"categories":5420},[150],{"categories":5422},[233],{"categories":5424},[100],{"categories":5426},[158],{"categories":5428},[192],{"categories":5430},[100],{"categories":5432},[192],{"categories":5434},[],{"categories":5436},[192],{"categories":5438},[150],{"categories":5440},[451],{"categories":5442},[158],{"categories":5444},[100],{"categories":5446},[],{"categories":5448},[170],{"categories":5450},[158],{"categories":5452},[161],{"categories":5454},[158],{"categories":5456},[150],{"categories":5458},[],{"categories":5460},[],{"categories":5462},[],{"categories":5464},[233],{"categories":5466},[158],{"categories":5468},[100],{"categories":5470},[100],{"categories":5472},[],{"categories":5474},[],{"categories":5476},[],{"categories":5478},[233],{"categories":5480},[100],{"categories":5482},[],{"categories":5484},[158],{"categories":5486},[100],{"categories":5488},[150],{"categories":5490},[],{"categories":5492},[],{"categories":5494},[100],{"categories":5496},[233],{"categories":5498},[100],{"categories":5500},[192],{"categories":5502},[],{"categories":5504},[100],{"categories":5506},[261],{"categories":5508},[192],{"categories":5510},[261],{"categories":5512},[236],{"categories":5514},[100],{"categories":5516},[100],{"categories":5518},[],{"categories":5520},[],{"categories":5522},[158],{"categories":5524},[],{"categories":5526},[100],{"categories":5528},[451],{"categories":5530},[100],{"categories":5532},[100],{"categories":5534},[100],{"categories":5536},[100],{"categories":5538},[],{"categories":5540},[158],{"categories":5542},[100],{"categories":5544},[100],{"categories":5546},[],{"categories":5548},[158],{"categories":5550},[100],{"categories":5552},[192],{"categories":5554},[100],{"categories":5556},[261],{"categories":5558},[153],{"categories":5560},[100],{"categories":5562},[100],{"categories":5564},[158],{"categories":5566},[236],{"categories":5568},[158],{"categories":5570},[158],{"categories":5572},[],{"categories":5574},[158],{"categories":5576},[],{"categories":5578},[100],{"categories":5580},[],{"categories":5582},[192],{"categories":5584},[153],{"categories":5586},[],{"categories":5588},[100],{"categories":5590},[],{"categories":5592},[233],{"categories":5594},[150],{"categories":5596},[],{"categories":5598},[153],{"categories":5600},[261],{"categories":5602},[100],{"categories":5604},[170],{"categories":5606},[150],{"categories":5608},[236],{"categories":5610},[153],{"categories":5612},[170],{"categories":5614},[158],{"categories":5616},[170],{"categories":5618},[],{"categories":5620},[161],{"categories":5622},[100],{"categories":5624},[],{"categories":5626},[158],{"categories":5628},[150],{"categories":5630},[233],{"categories":5632},[100],{"categories":5634},[150],{"categories":5636},[158],{"categories":5638},[296],{"categories":5640},[100],{"categories":5642},[100],{"categories":5644},[100],{"categories":5646},[150],{"categories":5648},[236],{"categories":5650},[158],{"categories":5652},[],{"categories":5654},[100],{"categories":5656},[100],{"categories":5658},[100],{"categories":5660},[170],{"categories":5662},[158],{"categories":5664},[192],{"categories":5666},[170],{"categories":5668},[100],{"categories":5670},[161],{"categories":5672},[],{"categories":5674},[233],{"categories":5676},[192],{"categories":5678},[150],{"categories":5680},[158],{"categories":5682},[100],{"categories":5684},[100],{"categories":5686},[158],{"categories":5688},[161],{"categories":5690},[100],{"categories":5692},[158],{"categories":5694},[100],{"categories":5696},[153],{"categories":5698},[158],{"categories":5700},[158,296],{"categories":5702},[100],{"categories":5704},[100],{"categories":5706},[158],{"categories":5708},[170],{"categories":5710},[100],{"categories":5712},[100],{"categories":5714},[236],{"categories":5716},[158],{"categories":5718},[261],{"categories":5720},[158],{"categories":5722},[153],{"categories":5724},[],{"categories":5726},[158],{"categories":5728},[100],{"categories":5730},[153],{"categories":5732},[],{"categories":5734},[],{"categories":5736},[170],{"categories":5738},[100],{"categories":5740},[100],{"categories":5742},[158],{"categories":5744},[236],{"categories":5746},[261],{"categories":5748},[100],{"categories":5750},[100],{"categories":5752},[158],{"categories":5754},[],{"categories":5756},[158],{"categories":5758},[192],{"categories":5760},[158],{"categories":5762},[],{"categories":5764},[192],{"categories":5766},[170],{"categories":5768},[2784],{"categories":5770},[150],{"categories":5772},[170],{"categories":5774},[100],{"categories":5776},[158],{"categories":5778},[100],{"categories":5780},[100],{"categories":5782},[261],{"categories":5784},[170],{"categories":5786},[],{"categories":5788},[192],{"categories":5790},[100],{"categories":5792},[],{"categories":5794},[158],{"categories":5796},[100],{"categories":5798},[100],{"categories":5800},[100],{"categories":5802},[100],{"categories":5804},[158],{"categories":5806},[100],{"categories":5808},[100],{"categories":5810},[161],{"categories":5812},[100],{"categories":5814},[158],{"categories":5816},[100],{"categories":5818},[100],{"categories":5820},[100],{"categories":5822},[100],{"categories":5824},[100],{"categories":5826},[100],{"categories":5828},[153],{"categories":5830},[],{"categories":5832},[161],{"categories":5834},[192],{"categories":5836},[158],{"categories":5838},[100],{"categories":5840},[170],{"categories":5842},[],{"categories":5844},[170],{"categories":5846},[170],{"categories":5848},[158],{"categories":5850},[170],{"categories":5852},[100],{"categories":5854},[100],{"categories":5856},[100],{"categories":5858},[158],{"categories":5860},[170],{"categories":5862},[100],{"categories":5864},[100],{"categories":5866},[158],{"categories":5868},[192],{"categories":5870},[100],{"categories":5872},[100],{"categories":5874},[100],{"categories":5876},[153],{"categories":5878},[100],{"categories":5880},[158],{"categories":5882},[233],{"categories":5884},[],{"categories":5886},[100],{"categories":5888},[236],{"categories":5890},[158],{"categories":5892},[100],{"categories":5894},[100],{"categories":5896},[],{"categories":5898},[100],{"categories":5900},[100],{"categories":5902},[192],{"categories":5904},[100],{"categories":5906},[100],{"categories":5908},[158],{"categories":5910},[261],{"categories":5912},[],{"categories":5914},[],{"categories":5916},[170],{"categories":5918},[100],{"categories":5920},[192],{"categories":5922},[170],{"categories":5924},[192],{"categories":5926},[100],{"categories":5928},[261],{"categories":5930},[236],{"categories":5932},[100],{"categories":5934},[150],{"categories":5936},[158],{"categories":5938},[100],{"categories":5940},[158],{"categories":5942},[158],{"categories":5944},[100],{"categories":5946},[153],{"categories":5948},[],{"categories":5950},[236],{"categories":5952},[100],{"categories":5954},[],{"categories":5956},[192],{"categories":5958},[100],{"categories":5960},[236],{"categories":5962},[100],{"categories":5964},[170],{"categories":5966},[170],{"categories":5968},[170],{"categories":5970},[158],{"categories":5972},[158],{"categories":5974},[100],{"categories":5976},[158],{"categories":5978},[100],{"categories":5980},[100],{"categories":5982},[233],{"categories":5984},[236],{"categories":5986},[236],{"categories":5988},[],{"categories":5990},[192],{"categories":5992},[100],{"categories":5994},[100],{"categories":5996},[170],{"categories":5998},[],{"categories":6000},[192],{"categories":6002},[192],{"categories":6004},[192],{"categories":6006},[],{"categories":6008},[158],{"categories":6010},[100],{"categories":6012},[],{"categories":6014},[150],{"categories":6016},[153],{"categories":6018},[],{"categories":6020},[100],{"categories":6022},[100],{"categories":6024},[],{"categories":6026},[170],{"categories":6028},[],{"categories":6030},[],{"categories":6032},[],{"categories":6034},[],{"categories":6036},[100],{"categories":6038},[192],{"categories":6040},[],{"categories":6042},[],{"categories":6044},[100],{"categories":6046},[100],{"categories":6048},[100],{"categories":6050},[236],{"categories":6052},[100],{"categories":6054},[236],{"categories":6056},[],{"categories":6058},[236],{"categories":6060},[236],{"categories":6062},[296],{"categories":6064},[158],{"categories":6066},[170],{"categories":6068},[],{"categories":6070},[],{"categories":6072},[236],{"categories":6074},[170],{"categories":6076},[170],{"categories":6078},[170],{"categories":6080},[],{"categories":6082},[150],{"categories":6084},[170],{"categories":6086},[170],{"categories":6088},[150],{"categories":6090},[170],{"categories":6092},[153],{"categories":6094},[170],{"categories":6096},[170],{"categories":6098},[170],{"categories":6100},[236],{"categories":6102},[192],{"categories":6104},[192],{"categories":6106},[100],{"categories":6108},[170],{"categories":6110},[236],{"categories":6112},[296],{"categories":6114},[236],{"categories":6116},[236],{"categories":6118},[236],{"categories":6120},[],{"categories":6122},[153],{"categories":6124},[],{"categories":6126},[296],{"categories":6128},[170],{"categories":6130},[170],{"categories":6132},[170],{"categories":6134},[158],{"categories":6136},[192,153],{"categories":6138},[236],{"categories":6140},[],{"categories":6142},[],{"categories":6144},[236],{"categories":6146},[],{"categories":6148},[236],{"categories":6150},[192],{"categories":6152},[158],{"categories":6154},[],{"categories":6156},[170],{"categories":6158},[100],{"categories":6160},[233],{"categories":6162},[],{"categories":6164},[100],{"categories":6166},[],{"categories":6168},[192],{"categories":6170},[150],{"categories":6172},[236],{"categories":6174},[],{"categories":6176},[170],{"categories":6178},[192],[6180,6254,6332,6407],{"id":6181,"title":6182,"ai":6183,"body":6188,"categories":6230,"created_at":101,"date_modified":101,"description":93,"extension":102,"faq":101,"featured":103,"kicker_label":101,"meta":6231,"navigation":124,"path":6241,"published_at":6242,"question":101,"scraped_at":6242,"seo":6243,"sitemap":6244,"source_id":6245,"source_name":6246,"source_type":6247,"source_url":6237,"stem":6248,"tags":6249,"thumbnail_url":101,"tldr":6251,"tweet":101,"unknown_tags":6252,"__hash__":6253},"summaries\u002Fsummaries\u002F3202acfb8c7c2435-verbal-reinforcement-learning-closing-the-feedback-summary.md","Verbal Reinforcement Learning: Closing the Feedback Loop",{"provider":7,"model":8,"input_tokens":6184,"output_tokens":6185,"processing_time_ms":6186,"cost_usd":6187},4120,524,2981,0.001816,{"type":14,"value":6189,"toc":6225},[6190,6194,6197,6201,6204,6218,6222],[17,6191,6193],{"id":6192},"from-raw-rewards-to-verbal-insights","From Raw Rewards to Verbal Insights",[22,6195,6196],{},"Traditional Reinforcement Learning (RL) relies heavily on scalar reward signals, which often fail to capture the nuance of complex tasks or human intent. The authors propose 'Verbal Reinforcement Learning' (VRL) as a paradigm shift that treats natural language feedback as the primary signal for policy improvement. By moving beyond simple numerical scores, VRL allows agents to interpret qualitative critiques, enabling more sample-efficient learning and better alignment with human preferences.",[17,6198,6200],{"id":6199},"experience-extraction-and-insight-governance","Experience Extraction and Insight Governance",[22,6202,6203],{},"The framework introduces a two-stage pipeline for managing verbal feedback:",[33,6205,6206,6212],{},[36,6207,6208,6211],{},[39,6209,6210],{},"Experience Extraction",": This stage focuses on distilling raw interaction data into actionable verbal summaries. Instead of treating every interaction as a monolithic event, the system parses the agent's performance into descriptive linguistic tokens that highlight specific successes or failures.",[36,6213,6214,6217],{},[39,6215,6216],{},"Insight Governance",": This is the critical control layer. Rather than blindly incorporating all feedback, 'governance' ensures that the verbal insights are validated, prioritized, and filtered for consistency. This prevents the agent from being misled by noisy, contradictory, or low-quality feedback, effectively creating a 'curated' learning signal that guides policy updates more reliably than traditional gradient-based methods alone.",[17,6219,6221],{"id":6220},"practical-implications-for-ai-alignment","Practical Implications for AI Alignment",[22,6223,6224],{},"The core argument is that by formalizing how verbal feedback is extracted and governed, developers can create AI systems that are more transparent and easier to steer. This approach addresses the 'black box' nature of reward functions by making the feedback loop explicit and readable. By governing the insights, engineers can audit why an agent changed its behavior, providing a clearer path toward robust, human-aligned AI agents.",{"title":93,"searchDepth":94,"depth":94,"links":6226},[6227,6228,6229],{"id":6192,"depth":94,"text":6193},{"id":6199,"depth":94,"text":6200},{"id":6220,"depth":94,"text":6221},[100],{"content_references":6232,"triage":6239},[6233],{"type":6234,"title":6235,"publisher":6236,"url":6237,"context":6238},"paper","Closing the Feedback Loop: From Experience Extraction to Insight Governance in Verbal Reinforcement Learning","arXiv","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.17591","cited",{"relevance":120,"novelty":120,"quality":120,"actionability":121,"composite":122,"reasoning":6240},"Category: AI & LLMs. The article introduces a novel framework for Verbal Reinforcement Learning, addressing a specific pain point in AI alignment by improving how feedback is utilized in training AI systems. It provides insights into a new approach that could be actionable for developers looking to enhance AI interpretability, though it lacks detailed implementation steps.","\u002Fsummaries\u002F3202acfb8c7c2435-verbal-reinforcement-learning-closing-the-feedback-summary","2026-06-17 12:57:00",{"title":6182,"description":93},{"loc":6241},"3202acfb8c7c2435","arXiv cs.AI","article","summaries\u002F3202acfb8c7c2435-verbal-reinforcement-learning-closing-the-feedback-summary",[6250,137,139],"research","The paper introduces a framework for 'Verbal Reinforcement Learning' (VRL), shifting from raw reward signals to structured insight governance by extracting and managing verbal feedback from world interactions.",[137,139],"Y11E4ho43sKowioeZKaa_zEyiuVXgUUbD5alULsZaXg",{"id":6255,"title":6256,"ai":6257,"body":6262,"categories":6310,"created_at":101,"date_modified":101,"description":93,"extension":102,"faq":101,"featured":103,"kicker_label":101,"meta":6311,"navigation":124,"path":6321,"published_at":6322,"question":101,"scraped_at":6322,"seo":6323,"sitemap":6324,"source_id":6325,"source_name":6246,"source_type":6247,"source_url":6317,"stem":6326,"tags":6327,"thumbnail_url":101,"tldr":6329,"tweet":101,"unknown_tags":6330,"__hash__":6331},"summaries\u002Fsummaries\u002F49d2f790ffd8272a-securing-continuous-data-summarization-against-adv-summary.md","Securing Continuous Data Summarization Against Adversarial Attacks",{"provider":7,"model":8,"input_tokens":6258,"output_tokens":6259,"processing_time_ms":6260,"cost_usd":6261},4121,600,3212,0.00193025,{"type":14,"value":6263,"toc":6305},[6264,6268,6271,6275,6278,6282,6285],[17,6265,6267],{"id":6266},"the-vulnerability-of-continuous-summarization","The Vulnerability of Continuous Summarization",[22,6269,6270],{},"Continuous data summarization systems, which process streams of information in real-time, are susceptible to sophisticated adversarial attacks. Unlike static summarization, where the input is fixed, continuous systems are vulnerable to multi-target attacks that exploit the temporal nature of the data. These attacks aim to manipulate the model's output by injecting subtle, malicious perturbations into the data stream, causing the summarizer to produce biased, inaccurate, or harmful summaries without triggering standard anomaly detection systems.",[17,6272,6274],{"id":6273},"multi-target-adversarial-strategies","Multi-Target Adversarial Strategies",[22,6276,6277],{},"The research highlights that attackers can target multiple aspects of the summarization process simultaneously. By leveraging the sequential dependency of these models, adversaries can craft inputs that force the model to prioritize specific malicious information or suppress critical factual data. The paper demonstrates that these attacks are particularly effective because they exploit the model's reliance on historical context, allowing the adversary to 'steer' the summary over time rather than relying on a single, detectable injection point.",[17,6279,6281],{"id":6280},"robust-defense-mechanisms","Robust Defense Mechanisms",[22,6283,6284],{},"To counter these threats, the authors propose a framework for robust defense that focuses on two primary areas: input sanitization and model hardening.",[63,6286,6287,6293,6299],{},[36,6288,6289,6292],{},[39,6290,6291],{},"Temporal Consistency Checking",": By implementing verification layers that monitor the semantic drift of summaries over time, the system can identify when an adversarial input is forcing a deviation from the expected content trajectory.",[36,6294,6295,6298],{},[39,6296,6297],{},"Adversarial Training",": The researchers advocate for training models on synthetic adversarial streams that simulate multi-target attacks. This process forces the model to learn more stable representations of the input data, making it less sensitive to the small, targeted perturbations used in these attacks.",[36,6300,6301,6304],{},[39,6302,6303],{},"Dynamic Thresholding",": Rather than using static sensitivity levels, the proposed defense uses dynamic thresholds that adjust based on the volatility of the incoming data stream, effectively filtering out noise that might otherwise be misinterpreted as adversarial intent.",{"title":93,"searchDepth":94,"depth":94,"links":6306},[6307,6308,6309],{"id":6266,"depth":94,"text":6267},{"id":6273,"depth":94,"text":6274},{"id":6280,"depth":94,"text":6281},[100],{"content_references":6312,"triage":6318},[6313],{"type":6234,"title":6314,"author":6315,"publisher":6316,"url":6317,"context":6238},"Toward Trustworthy AI: Multi-Target Adversarial Attacks and Robust Defenses for Continuous Data Summarization","Not specified","IEEE Transactions on Information Forensics and Security (IEEE TIFS)","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.11804",{"relevance":120,"novelty":121,"quality":120,"actionability":121,"composite":6319,"reasoning":6320},3.6,"Category: AI & LLMs. The article discusses vulnerabilities in continuous data summarization systems and proposes robust defense mechanisms, addressing a specific audience pain point regarding AI trustworthiness. While it presents some new insights into adversarial attacks, the practical application of the proposed defenses could be more detailed.","\u002Fsummaries\u002F49d2f790ffd8272a-securing-continuous-data-summarization-against-adv-summary","2026-06-11 12:57:19",{"title":6256,"description":93},{"loc":6321},"49d2f790ffd8272a","summaries\u002F49d2f790ffd8272a-securing-continuous-data-summarization-against-adv-summary",[6328,137,138],"machine-learning","This paper addresses vulnerabilities in continuous data summarization systems by identifying multi-target adversarial attack vectors and proposing robust defense mechanisms to ensure AI trustworthiness.",[137,138],"jEN37Ri1FlNdqDdTecQl8iY35m6OwEdpr7faRCyOXpY",{"id":6333,"title":6334,"ai":6335,"body":6340,"categories":6383,"created_at":101,"date_modified":101,"description":93,"extension":102,"faq":101,"featured":103,"kicker_label":101,"meta":6384,"navigation":124,"path":6394,"published_at":6395,"question":101,"scraped_at":6395,"seo":6396,"sitemap":6397,"source_id":6398,"source_name":6399,"source_type":6247,"source_url":6400,"stem":6401,"tags":6402,"thumbnail_url":101,"tldr":6404,"tweet":101,"unknown_tags":6405,"__hash__":6406},"summaries\u002Fsummaries\u002F3dd2b79848ef9684-microsoft-s-mai-transcribe-1-5-production-ready-sp-summary.md","Microsoft's MAI-Transcribe-1.5: Production-Ready Speech Recognition",{"provider":7,"model":8,"input_tokens":6336,"output_tokens":6337,"processing_time_ms":6338,"cost_usd":6339},8424,503,3080,0.0028605,{"type":14,"value":6341,"toc":6379},[6342,6346,6349,6352,6356,6359],[17,6343,6345],{"id":6344},"performance-and-efficiency-gains","Performance and Efficiency Gains",[22,6347,6348],{},"Microsoft's MAI-Transcribe-1.5 represents a significant iteration in their in-house speech-to-text stack, focusing on production-grade performance. The model achieves a 2.4% Word-Error-Rate (WER) on the Artificial Analysis leaderboard, positioning it as a competitive option for high-accuracy transcription.",[22,6350,6351],{},"Efficiency is the model's primary differentiator, particularly for long-form audio. Microsoft reports that the model is up to 5x faster than competitors like Gemini 3.1 and GPT-4o-Transcribe, and 5.7x faster than its predecessor, MAI-Transcribe-1. An hour of audio can now be processed in under 15 seconds, a critical improvement for batch-processing large archives.",[17,6353,6355],{"id":6354},"enterprise-focused-features","Enterprise-Focused Features",[22,6357,6358],{},"Beyond raw speed, the model introduces features designed to solve common enterprise transcription failures:",[63,6360,6361,6367,6373],{},[36,6362,6363,6366],{},[39,6364,6365],{},"Entity Biasing:"," Users can provide up to 200 domain-specific keywords (names, medical terms, internal acronyms). The model uses contextual awareness to apply these biases, rather than forcing matches blindly. This has been shown to reduce WER by 30% on the FLEURS benchmark.",[36,6368,6369,6372],{},[39,6370,6371],{},"Expanded Language Support:"," The model now supports 43 languages, up from 25. This includes 10 new South Asian languages and 8 European languages, all integrated into a single system.",[36,6374,6375,6378],{},[39,6376,6377],{},"Automatic Language Identification:"," The model can now detect the input language without requiring manual configuration, simplifying deployment in global contact centers and multi-language meeting environments.",{"title":93,"searchDepth":94,"depth":94,"links":6380},[6381,6382],{"id":6344,"depth":94,"text":6345},{"id":6354,"depth":94,"text":6355},[100],{"content_references":6385,"triage":6390},[6386],{"type":107,"title":6387,"url":6388,"context":6389},"MAI-Transcribe-1.5","https:\u002F\u002Fai.azure.com\u002Fcatalog\u002Fmodels\u002FMAI-Transcribe-1.5","recommended",{"relevance":6391,"novelty":121,"quality":120,"actionability":120,"composite":6392,"reasoning":6393},5,4.15,"Category: AI & LLMs. The article provides in-depth information about Microsoft's MAI-Transcribe-1.5, a production-ready speech recognition tool, which is highly relevant for developers looking to integrate AI-powered transcription features into their products. It discusses specific features like entity biasing and automatic language identification that can be directly applied in real-world applications.","\u002Fsummaries\u002F3dd2b79848ef9684-microsoft-s-mai-transcribe-1-5-production-ready-sp-summary","2026-06-08 12:56:50",{"title":6334,"description":93},{"loc":6394},"3dd2b79848ef9684","MarkTechPost","https:\u002F\u002Fwww.marktechpost.com\u002F2026\u002F06\u002F08\u002Fmicrosoft-ai-introduces-mai-transcribe-1-5-2-4-wer-on-artificial-analysis-best-in-class-fleurs-accuracy-and-up-to-5x-faster-long-audio-transcription\u002F","summaries\u002F3dd2b79848ef9684-microsoft-s-mai-transcribe-1-5-production-ready-sp-summary",[136,137,6403],"speech-recognition","Microsoft's MAI-Transcribe-1.5 improves speech-to-text with 43-language support, 5x faster long-form inference, and entity-aware keyword biasing for enterprise accuracy.",[137,6403],"EzpbPexvXrF0mZ5jmNu6ZPioWBkBMTVSl5bvMf8iCmc",{"id":6408,"title":6409,"ai":6410,"body":6416,"categories":6607,"created_at":101,"date_modified":101,"description":93,"extension":102,"faq":101,"featured":103,"kicker_label":101,"meta":6608,"navigation":124,"path":6623,"published_at":6624,"question":101,"scraped_at":6625,"seo":6626,"sitemap":6627,"source_id":6628,"source_name":6629,"source_type":6247,"source_url":6630,"stem":6631,"tags":6632,"thumbnail_url":101,"tldr":6634,"tweet":101,"unknown_tags":6635,"__hash__":6636},"summaries\u002Fsummaries\u002Fada6c21aa9882eda-t-c-l-d-audit-spot-ai-s-erosion-of-your-role-summary.md","T-C-L-D Audit: Spot AI's Erosion of Your Role",{"provider":7,"model":6411,"input_tokens":6412,"output_tokens":6413,"processing_time_ms":6414,"cost_usd":6415},"x-ai\u002Fgrok-4.1-fast",8626,3137,30288,0.0032712,{"type":14,"value":6417,"toc":6601},[6418,6422,6425,6428,6431,6434,6438,6441,6446,6465,6470,6500,6503,6507,6510,6521,6527,6532,6552,6555,6562,6565,6569],[17,6419,6421],{"id":6420},"hollowing-out-ai-erodes-roles-before-replacing-them","Hollowing Out: AI Erodes Roles Before Replacing Them",[22,6423,6424],{},"Knowledge jobs don't vanish overnight like in hype videos; they get hollowed out gradually. AI targets routine pieces—info gathering, writing, summarizing—leaving a shell that looks productive until economic shocks (recessions, reorgs) force cuts. Travel agents illustrate: Online booking commoditized routine reservations first, without immediate job losses. Downturns later exposed the change, shifting survivors to complex planning, emergencies, and human judgment.",[22,6426,6427],{},"Data backs this: OpenAI\u002FUPenn estimate 80% of US workers have 10%+ tasks AI-affected; 20% see half impacted. Anthropic's index shows 49% of jobs with 25%+ tasks using LLMs. Microsoft Bing Copilot analysis of 200k sessions reveals top uses: writing, info provision—core to 'visible throughput' rewarded by old performance systems.",[22,6429,6430],{},"\"AI doesn't have to replace your whole job to put you on thin ice. It only has to pick away at enough of the pieces inside the job that when the next shock comes, the rest of the story stops holding together.\"",[22,6432,6433],{},"Performance reviews lag because they measure output volume ('Did the deck get made?'), not necessity ('Did it need a human?'). This creates a 'dangerous window' where calendars fill with low-value work, masking erosion. Theater (performative rituals) collapses first since it was already low-attention; commodity follows as AI scales without human limits.",[17,6435,6437],{"id":6436},"run-the-t-c-l-d-audit-on-your-work","Run the T-C-L-D Audit on Your Work",[22,6439,6440],{},"This 30-60 minute exercise dissects your last 10 business days into four buckets, forcing honesty about value. Prerequisites: Access to calendar, sent emails, Slack\u002FDMs, docs\u002Ftickets. Assumes knowledge worker role (emails\u002Fmeetings heavy); do it manually first for calibration, then AI-assist.",[22,6442,6443],{},[39,6444,6445],{},"Steps:",[33,6447,6448,6451,6459,6462],{},[36,6449,6450],{},"Open all sources side-by-side.",[36,6452,6453,6454,6458],{},"Tag ",[6455,6456,6457],"em",{},"each item"," (meeting, email, doc, message)—not projects\u002Froles—with T, C, L, or D. Use first instinct; agonize = L.",[36,6460,6461],{},"Count totals by time (hours) or items for proportions.",[36,6463,6464],{},"AI acceleration (optional, via Claude\u002Fcomputer use): Chunk by tool (e.g., one agent per email\u002Fcalendar). Provide clear definitions\u002Fprompts: \"Tag as T if performative with no examined value.\" Expect iteration; full automation needs your judgment input.",[22,6466,6467],{},[39,6468,6469],{},"Bucket Definitions & Tests:",[63,6471,6472,6478,6484,6490],{},[36,6473,6474,6477],{},[39,6475,6476],{},"T (Theater):"," Organizational performance, not value. Disappears without admitting waste. Examples: Unblocking status meetings, unread decks for flipping, ritual check-ins\u002Ffeedback post-decision, legacy reviews. Test: Main fallout is exposing fiction? >\"Tagging T means admitting you spent professional time on something that did not need to happen.\"",[36,6479,6480,6483],{},[39,6481,6482],{},"C (Commodity):"," Real value, but not you-specific. Examples: Summarizing known inputs, routing decisions, status reports anyone competent writes, first-draft docs in fixed formats. Test: Spec it out—could junior\u002Fvendor match output? Valuable but scarce no more; AI compresses throughput.",[36,6485,6486,6489],{},[39,6487,6488],{},"L (On the Line):"," Gray zone, vulnerable soon. Examples: Structured pattern recognition, history-based relationships, repeatable synthesis, junior-doable + your 'judgment' (hard to articulate). Feels expert but commoditizing.",[36,6491,6492,6495,6496,6499],{},[39,6493,6494],{},"D (Durable):"," You irreplaceably alter outcomes. Examples: Reading rooms to reframe problems, presence shifting decisions via taste\u002Fcontext\u002Fcourage. Test: Output relies on indescribable judgment; you changed the ",[6455,6497,6498],{},"question",", not just answered it. Rare, power-law distributed (few high-impact hours define careers).",[22,6501,6502],{},"Common pitfalls: Undercount T (confuse 'expected' with 'valuable'); overclaim D (self-image vs. hours logged); ignore L's migration to C.",[17,6504,6506],{"id":6505},"redirect-to-durable-work-results-pitfalls-and-six-moves","Redirect to Durable Work: Results, Pitfalls, and Six Moves",[22,6508,6509],{},"Expect: High T\u002FC (invisible erosion), low D (under-allocated), L signaling shifts. Reveals mismatch: Identity clings to imagined uniqueness, but weeks prioritize defensible routines.",[22,6511,6512,6515,6516,6520],{},[39,6513,6514],{},"Core Principle: Question-Holding vs. Answering."," Durable = holding ambiguity (diagnose real issues, evolve questions via context\u002Fjudgment). Commodity\u002Ftheater = answering knowns. AI excels at latter; humans at former. \"Durable work ",[6517,6518,6519],"span",{},"is"," question-holding instead of question-answering.\"",[22,6522,6523,6526],{},[39,6524,6525],{},"Legibility Paradox:"," Visible busyness (T\u002FC) props up reviews; durable often invisible (e.g., quiet reframing). Cutting T\u002FC exposes you short-term but frees capacity.",[22,6528,6529],{},[39,6530,6531],{},"Post-Audit Moves (Prioritize by Impact):",[33,6533,6534,6537,6540,6543,6546,6549],{},[36,6535,6536],{},"Stop defending T: Delegate\u002Fasync\u002FAI (e.g., bot summaries).",[36,6538,6539],{},"Automate C: Prompt LLMs for drafts\u002Froutings; spec for juniors.",[36,6541,6542],{},"Probe L: Articulate judgment— if specifiable, shift to C; else build toward D.",[36,6544,6545],{},"Amplify D: Propose projects centering it; track\u002Fquantify impact.",[36,6547,6548],{},"Update identity: Self-image as 'question-holder' before reorgs force it. Pour saved time into durable, not more C (trap: 2x productive at collapsing value).",[36,6550,6551],{},"Re-audit biweekly; share anonymized with peers for calibration.",[22,6553,6554],{},"\"The first sign that your job is on thin ice is often a full calendar and no clue what's happening.\"",[22,6556,6557,6558,6561],{},"\"Your week is not organized around ",[6517,6559,6560],{},"durable work",".\"",[22,6563,6564],{},"Practice: After tagging, journal one D item—why durable? Prototype AI for top C. Fits early\u002Fmid-career pivot in AI era; scales to teams (aggregate audits for reorg prep).",[17,6566,6568],{"id":6567},"key-takeaways","Key Takeaways",[63,6570,6571,6574,6577,6580,6583,6586,6589,6592,6595,6598],{},[36,6572,6573],{},"Tag last 10 days' items as T\u002FC\u002FL\u002FD to quantify vulnerability—aim \u003C20% T, minimize C\u002FL.",[36,6575,6576],{},"Eliminate theater first: If no one examines output, AI it now.",[36,6578,6579],{},"Test commodity: 'Could I spec this for anyone?' → Automate\u002Foffload.",[36,6581,6582],{},"Seek durable: Did you reframe the question? Double down there.",[36,6584,6585],{},"Avoid identity trap: Audit hours, not self-image; redirect saved time to D.",[36,6587,6588],{},"Use AI for audit (chunked prompts) but supply your definitions.",[36,6590,6591],{},"Re-run biweekly; downturns accelerate shifts—act pre-shock.",[36,6593,6594],{},"Power-law careers: Few D moments define you; organize week around them.",[36,6596,6597],{},"Question-holding wins: AI answers; you evolve problems.",[36,6599,6600],{},"Leaders doubling C productivity lose—shift before systems update.",{"title":93,"searchDepth":94,"depth":94,"links":6602},[6603,6604,6605,6606],{"id":6420,"depth":94,"text":6421},{"id":6436,"depth":94,"text":6437},{"id":6505,"depth":94,"text":6506},{"id":6567,"depth":94,"text":6568},[],{"content_references":6609,"triage":6621},[6610,6614,6619],{"type":6611,"title":6612,"url":6613,"context":6389},"other","Job at Risk AI Audit","https:\u002F\u002Fnatesnewsletter.substack.com\u002Fp\u002Fjob-at-risk-ai-audit?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true",{"type":6615,"title":6616,"author":6617,"url":6618,"context":109},"podcast","AI News & Strategy Daily with Nate B Jones","Nate B Jones","https:\u002F\u002Fopen.spotify.com\u002Fshow\u002F0gkFdjd1wptEKJKLu9LbZ4",{"type":6615,"title":6616,"author":6617,"url":6620,"context":109},"https:\u002F\u002Fpodcasts.apple.com\u002Fus\u002Fpodcast\u002Fai-news-strategy-daily-with-nate-b-jones\u002Fid1877109372",{"relevance":120,"novelty":121,"quality":120,"actionability":120,"composite":122,"reasoning":6622},"Category: AI Automation. The article provides a practical framework (T-C-L-D Audit) for assessing tasks vulnerable to AI, addressing a specific pain point for builders concerned about AI's impact on productivity. It offers actionable steps for categorizing work, which can help users redirect their focus to more irreplaceable tasks.","\u002Fsummaries\u002Fada6c21aa9882eda-t-c-l-d-audit-spot-ai-s-erosion-of-your-role-summary","2026-05-04 14:01:31","2026-05-04 16:07:17",{"title":6409,"description":93},{"loc":6623},"f76685fd0455c76e","AI News & Strategy Daily | Nate B Jones","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rYqt6mMlv7o","summaries\u002Fada6c21aa9882eda-t-c-l-d-audit-spot-ai-s-erosion-of-your-role-summary",[136,137,6633],"dev-productivity","Categorize your last two weeks' tasks as Theater (T), Commodity (C), Line (L), or Durable (D) to reveal what's AI-vulnerable, then redirect time to irreplaceable question-holding work.",[137,6633],"lwAIIHpGLcmdd7HT99Xx_9gnm2NTKm4HUbbLFLQHMrE"]