[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-3dbb1a3ba51ae1f2-building-ai-native-search-with-spanner-summary":3,"summaries-facets-categories":148,"summary-related-3dbb1a3ba51ae1f2-building-ai-native-search-with-spanner-summary":5652},{"id":4,"title":5,"ai":6,"body":13,"categories":104,"created_at":106,"date_modified":106,"description":97,"extension":107,"faq":106,"featured":108,"kicker_label":106,"meta":109,"navigation":126,"path":127,"published_at":128,"question":106,"scraped_at":129,"seo":130,"sitemap":131,"source_id":132,"source_name":133,"source_type":134,"source_url":135,"stem":136,"tags":137,"thumbnail_url":143,"tldr":144,"tweet":145,"unknown_tags":146,"__hash__":147},"summaries\u002Fsummaries\u002F3dbb1a3ba51ae1f2-building-ai-native-search-with-spanner-summary.md","Building AI-Native Search with Spanner",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",9969,862,4121,0.00378525,{"type":14,"value":15,"toc":96},"minimark",[16,21,25,29,32,55,59,62,89,93],[17,18,20],"h2",{"id":19},"the-shift-to-unified-search-architectures","The Shift to Unified Search Architectures",[22,23,24],"p",{},"Traditionally, building search-heavy applications required a fragmented stack: a primary relational database for transactions, a separate full-text search engine (like Elasticsearch or Algolia), and a vector database for AI workloads. This architecture introduces significant operational toil, including ETL pipelines, data duplication, and the dreaded \"data lag\" where search results reflect stale state. Spanner solves this by integrating these capabilities into a single, transactionally consistent platform.",[17,26,28],{"id":27},"the-three-pillars-of-spanner-search","The Three Pillars of Spanner Search",[22,30,31],{},"Spanner provides three primary search modalities that can be used independently or in combination:",[33,34,35,43,49],"ol",{},[36,37,38,42],"li",{},[39,40,41],"strong",{},"Full-Text Search:"," Uses tokenization and inverted indexes to handle keyword matching. It includes advanced features like fuzzy search (via n-grams) to handle typos and synonyms, and \"enhanced search\"—a proprietary Google technology that rewrites queries to include semantically relevant terms (e.g., expanding \"hair dye\" to include \"coloring\" or \"dyeing\").",[36,44,45,48],{},[39,46,47],{},"Vector Search:"," Maps documents and queries into high-dimensional vector space, allowing for semantic retrieval. Spanner supports both exact (k-NN) and approximate (ANN) nearest neighbor searches, ensuring that AI-driven applications can perform similarity lookups directly on operational data.",[36,50,51,54],{},[39,52,53],{},"Hybrid Search:"," By combining full-text and vector search, developers can achieve the \"best of both worlds.\" This approach uses Reciprocal Rank Fusion (RRF) to merge results, ensuring that queries benefit from both precise keyword matching and contextual semantic understanding.",[17,56,58],{"id":57},"operational-advantages","Operational Advantages",[22,60,61],{},"By moving search into the primary database, teams gain several critical engineering benefits:",[63,64,65,71,77,83],"ul",{},[36,66,67,70],{},[39,68,69],{},"Transactional Consistency:"," Search indexes are updated in real-time. When an agent or user updates a record, the change is immediately reflected in the search index, providing true read-after-write consistency.",[36,72,73,76],{},[39,74,75],{},"Simplified Infrastructure:"," Eliminating ETL pipelines reduces maintenance overhead and infrastructure costs. Atteo, a CRM platform, reported saving over $500,000 annually by consolidating their search stack into Spanner.",[36,78,79,82],{},[39,80,81],{},"Deterministic Control:"," Unlike many managed search services that act as black boxes, Spanner allows developers to use query hints to control join orders, parallelism, and execution plans, providing predictable performance for planet-scale workloads.",[36,84,85,88],{},[39,86,87],{},"Point-in-Time Recovery:"," Because search indexes are part of the Spanner data model, developers can perform point-in-time reads to query the state of the search index as it existed at any previous moment.",[17,90,92],{"id":91},"implementation-strategy","Implementation Strategy",[22,94,95],{},"Spanner handles these complex search requirements through standard DDL. Developers define text or vector indexes directly on their tables, and the system handles backfilling and ongoing synchronization. For ranking, developers can choose between text-based relevance, vector-based similarity, or hybrid fusion, allowing for highly tailored retrieval logic without leaving the database environment.",{"title":97,"searchDepth":98,"depth":98,"links":99},"",2,[100,101,102,103],{"id":19,"depth":98,"text":20},{"id":27,"depth":98,"text":28},{"id":57,"depth":98,"text":58},{"id":91,"depth":98,"text":92},[105],"RAG & Retrieval",null,"md",false,{"content_references":110,"triage":121},[111,116,119],{"type":112,"title":113,"url":114,"context":115},"tool","Google Cloud Spanner","https:\u002F\u002Fcloud.google.com\u002Fspanner","mentioned",{"type":112,"title":117,"url":118,"context":115},"Atteo","https:\u002F\u002Fatteo.ai",{"type":112,"title":120,"context":115},"Gemini Enterprise Agent Platform",{"relevance":122,"novelty":123,"quality":123,"actionability":123,"composite":124,"reasoning":125},5,4,4.35,"Category: RAG & Retrieval. The article discusses the integration of full-text and vector search into Google Cloud Spanner, addressing the pain point of operational complexity in search-heavy applications. It provides actionable insights on how to leverage these capabilities for building AI-native search systems, making it highly relevant for engineers looking to optimize their search architectures.",true,"\u002Fsummaries\u002F3dbb1a3ba51ae1f2-building-ai-native-search-with-spanner-summary","2026-06-25 16:33:20","2026-06-29 14:34:04",{"title":5,"description":97},{"loc":127},"3dbb1a3ba51ae1f2","Google Cloud Tech","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=fAf4Zh-CC08","summaries\u002F3dbb1a3ba51ae1f2-building-ai-native-search-with-spanner-summary",[138,139,140,141,142],"rag","vector-search","spanner","full-text-search","database","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FfAf4Zh-CC08\u002Fhqdefault.jpg","Google Cloud Spanner now integrates full-text, vector, and hybrid search directly into the database, eliminating the need for separate search engines, ETL pipelines, and data synchronization issues.","This session provides an overview of how to implement hybrid search—combining full-text and vector search—directly within [Google Cloud Spanner](https:\u002F\u002Fcloud.google.com\u002Fspanner). The speakers explain how this architecture eliminates the need for separate search indices and ETL pipelines, followed by a case study from [Atteo](https:\u002F\u002Fatteo.ai) on using these features to power their CRM's data layer.",[140,141,142],"NOYpLy41teNzu_u6CJTDJok2-jWjf94DGmmWDfAdjA4",[149,152,155,158,161,164,166,168,171,173,175,177,179,182,184,186,188,190,193,195,197,199,201,203,205,207,209,211,213,215,217,219,221,223,225,228,231,233,235,237,239,241,243,245,247,249,251,254,256,258,260,262,264,266,268,270,272,274,276,278,280,282,285,287,289,291,293,295,297,299,301,303,305,307,310,312,314,316,318,320,322,324,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,369,371,373,375,377,379,381,383,385,388,390,392,394,396,398,400,402,404,406,408,410,412,414,416,418,420,422,424,426,429,431,433,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,465,467,469,471,473,476,478,480,483,485,487,489,491,493,495,497,499,501,503,505,507,509,512,514,516,518,520,522,524,526,528,531,533,535,537,539,541,543,545,547,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,709,711,713,715,717,719,721,723,725,727,729,731,733,735,737,739,741,743,745,747,749,751,753,755,757,759,761,763,765,768,770,772,774,777,779,781,783,785,787,789,791,793,795,798,800,802,804,806,808,810,812,814,816,818,820,822,824,826,828,830,832,834,836,838,840,842,844,846,848,850,852,854,856,858,860,862,864,866,868,870,872,874,876,878,880,882,884,886,888,890,892,894,896,898,900,902,904,906,908,910,912,914,916,918,920,922,924,926,928,930,932,934,936,938,940,942,944,946,948,950,952,954,956,958,960,962,964,966,968,970,972,974,976,978,980,982,984,986,988,990,992,994,996,998,1000,1002,1004,1006,1008,1010,1012,1014,1016,1018,1020,1022,1024,1026,1028,1030,1032,1034,1036,1038,1040,1042,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1200,1202,1204,1206,1208,1210,1212,1214,1216,1218,1220,1222,1224,1226,1228,1230,1232,1234,1236,1238,1240,1242,1244,1246,1248,1250,1252,1254,1256,1258,1260,1262,1264,1266,1268,1270,1272,1274,1276,1278,1280,1282,1284,1286,1288,1290,1292,1294,1296,1298,1300,1302,1304,1306,1308,1310,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1432,1434,1436,1438,1440,1442,1444,1446,1448,1450,1452,1454,1456,1458,1460,1462,1464,1466,1468,1470,1472,1474,1476,1478,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1507,1509,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1781,1783,1785,1787,1789,1791,1793,1795,1797,1799,1801,1803,1805,1807,1809,1811,1813,1815,1817,1819,1821,1824,1826,1828,1830,1832,1834,1836,1838,1840,1842,1844,1846,1848,1850,1852,1854,1856,1858,1860,1862,1864,1866,1868,1870,1872,1874,1876,1878,1880,1882,1884,1886,1888,1890,1892,1894,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1925,1927,1929,1931,1933,1935,1937,1939,1941,1943,1945,1947,1949,1951,1953,1955,1957,1959,1961,1963,1965,1967,1969,1971,1973,1975,1977,1979,1981,1983,1985,1987,1989,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018,2020,2022,2024,2026,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2513,2515,2517,2519,2521,2523,2525,2527,2529,2531,2533,2535,2537,2539,2541,2544,2546,2548,2550,2552,2554,2556,2558,2560,2562,2564,2566,2568,2570,2572,2574,2576,2578,2580,2582,2584,2586,2588,2590,2592,2594,2596,2598,2600,2602,2604,2606,2608,2610,2612,2614,2616,2618,2620,2622,2624,2626,2628,2630,2632,2634,2636,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2697,2699,2701,2703,2705,2707,2709,2711,2713,2715,2717,2719,2721,2723,2725,2727,2729,2731,2733,2735,2737,2739,2741,2743,2745,2747,2749,2751,2753,2755,2757,2759,2761,2763,2765,2767,2769,2771,2773,2775,2777,2779,2781,2783,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3643,3645,3647,3649,3651,3653,3655,3657,3659,3662,3664,3666,3668,3670,3672,3674,3676,3678,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700,3702,3704,3706,3708,3710,3712,3714,3716,3718,3720,3722,3724,3726,3728,3730,3732,3734,3736,3738,3740,3742,3744,3746,3748,3750,3752,3754,3756,3758,3760,3762,3764,3766,3768,3770,3772,3774,3776,3778,3780,3782,3784,3786,3788,3790,3792,3794,3796,3798,3800,3802,3804,3806,3808,3810,3812,3814,3816,3818,3820,3822,3824,3826,3828,3830,3832,3834,3836,3838,3840,3842,3844,3846,3848,3850,3852,3854,3856,3858,3860,3862,3864,3866,3868,3870,3872,3874,3876,3878,3880,3882,3884,3886,3888,3890,3892,3894,3896,3898,3900,3902,3904,3906,3908,3910,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4010,4012,4014,4016,4018,4020,4022,4024,4026,4028,4030,4032,4034,4036,4038,4040,4042,4044,4046,4048,4050,4052,4054,4056,4058,4060,4062,4064,4066,4068,4070,4072,4074,4076,4078,4080,4082,4084,4086,4088,4090,4092,4094,4096,4098,4100,4102,4104,4106,4108,4110,4112,4114,4116,4118,4120,4122,4124,4126,4128,4130,4132,4134,4136,4138,4140,4142,4144,4146,4148,4150,4152,4154,4156,4158,4160,4162,4164,4166,4168,4170,4172,4174,4176,4178,4180,4182,4184,4186,4188,4190,4192,4194,4196,4198,4200,4202,4204,4206,4208,4210,4212,4214,4216,4218,4220,4222,4224,4226,4228,4230,4232,4234,4236,4238,4240,4242,4244,4246,4248,4250,4252,4254,4256,4258,4260,4262,4264,4266,4268,4270,4272,4274,4276,4278,4280,4282,4284,4286,4288,4290,4292,4294,4296,4298,4300,4302,4304,4306,4308,4310,4312,4314,4316,4318,4320,4322,4324,4326,4328,4330,4332,4334,4336,4338,4340,4342,4344,4346,4348,4351,4353,4355,4357,4359,4361,4363,4365,4367,4369,4371,4373,4375,4377,4379,4381,4383,4385,4387,4389,4391,4393,4395,4397,4399,4401,4403,4405,4407,4409,4411,4413,4415,4417,4419,4421,4423,4425,4427,4429,4431,4433,4435,4437,4439,4441,4443,4445,4447,4449,4451,4453,4455,4457,4459,4461,4463,4465,4467,4469,4471,4473,4475,4477,4479,4481,4483,4485,4487,4489,4491,4493,4495,4497,4499,4501,4503,4505,4507,4509,4511,4514,4516,4518,4520,4522,4524,4526,4528,4530,4532,4534,4536,4538,4540,4542,4544,4546,4548,4550,4552,4554,4556,4558,4560,4562,4564,4566,4568,4570,4572,4574,4576,4578,4580,4582,4584,4586,4588,4590,4592,4594,4596,4598,4600,4602,4604,4606,4608,4610,4612,4614,4616,4618,4620,4622,4624,4626,4628,4630,4632,4634,4636,4638,4640,4642,4644,4646,4648,4650,4652,4654,4656,4658,4660,4662,4664,4666,4668,4670,4672,4674,4676,4678,4680,4682,4684,4686,4688,4690,4692,4694,4696,4698,4700,4702,4704,4706,4708,4710,4712,4714,4716,4718,4720,4722,4724,4726,4728,4730,4732,4734,4736,4738,4740,4742,4744,4746,4748,4750,4752,4754,4756,4758,4760,4762,4764,4766,4768,4770,4772,4774,4776,4778,4780,4782,4784,4786,4788,4790,4792,4794,4796,4798,4800,4802,4804,4806,4808,4810,4812,4814,4816,4818,4820,4822,4824,4826,4828,4830,4832,4834,4836,4838,4840,4842,4844,4846,4848,4850,4852,4854,4856,4858,4860,4862,4864,4866,4868,4870,4872,4874,4876,4878,4880,4882,4884,4886,4888,4890,4892,4894,4896,4898,4900,4902,4904,4906,4908,4910,4912,4914,4916,4918,4920,4922,4924,4926,4928,4930,4932,4934,4936,4938,4940,4942,4944,4946,4948,4950,4952,4954,4956,4958,4960,4962,4964,4966,4968,4970,4972,4974,4976,4978,4980,4982,4984,4986,4988,4990,4992,4994,4996,4998,5000,5002,5004,5006,5008,5010,5012,5014,5016,5018,5020,5022,5024,5026,5028,5030,5032,5034,5036,5038,5040,5042,5044,5046,5048,5050,5052,5054,5056,5058,5060,5062,5064,5066,5068,5070,5072,5074,5076,5078,5080,5082,5084,5086,5088,5090,5092,5094,5096,5098,5100,5102,5104,5106,5108,5110,5112,5114,5116,5118,5120,5122,5124,5126,5128,5130,5132,5134,5136,5138,5140,5142,5144,5146,5148,5150,5152,5154,5156,5158,5160,5162,5164,5166,5168,5170,5172,5174,5176,5178,5180,5182,5184,5186,5188,5190,5192,5194,5196,5198,5200,5202,5204,5206,5208,5210,5212,5214,5216,5218,5220,5222,5224,5226,5228,5230,5232,5234,5236,5238,5240,5242,5244,5246,5248,5250,5252,5254,5256,5258,5260,5262,5264,5266,5268,5270,5272,5274,5276,5278,5280,5282,5284,5286,5288,5290,5292,5294,5296,5298,5300,5302,5304,5306,5308,5310,5312,5314,5316,5318,5320,5322,5324,5326,5328,5330,5332,5334,5336,5338,5340,5342,5344,5346,5348,5350,5352,5354,5356,5358,5360,5362,5364,5366,5368,5370,5372,5374,5376,5378,5380,5382,5384,5386,5388,5390,5392,5394,5396,5398,5400,5402,5404,5406,5408,5410,5412,5414,5416,5418,5420,5422,5424,5426,5428,5430,5432,5434,5436,5438,5440,5442,5444,5446,5448,5450,5452,5454,5456,5458,5460,5462,5464,5466,5468,5470,5472,5474,5476,5478,5480,5482,5484,5486,5488,5490,5492,5494,5496,5498,5500,5502,5504,5506,5508,5510,5512,5514,5516,5518,5520,5522,5524,5526,5528,5530,5532,5534,5536,5538,5540,5542,5544,5546,5548,5550,5552,5554,5556,5558,5560,5562,5564,5566,5568,5570,5572,5574,5576,5578,5580,5582,5584,5586,5588,5590,5592,5594,5596,5598,5600,5602,5604,5606,5608,5610,5612,5614,5616,5618,5620,5622,5624,5626,5628,5630,5632,5634,5636,5638,5640,5642,5644,5646,5648,5650],{"categories":150},[151],"Developer Productivity",{"categories":153},[154],"Business & SaaS",{"categories":156},[157],"AI & LLMs",{"categories":159},[160],"AI Automation",{"categories":162},[163],"Product Strategy",{"categories":165},[157],{"categories":167},[151],{"categories":169},[170],"Software Engineering",{"categories":172},[157],{"categories":174},[154],{"categories":176},[],{"categories":178},[157],{"categories":180},[181],"Inference & Serving",{"categories":183},[157],{"categories":185},[157],{"categories":187},[160],{"categories":189},[],{"categories":191},[192],"AI News & Trends",{"categories":194},[160],{"categories":196},[157],{"categories":198},[154],{"categories":200},[160],{"categories":202},[192],{"categories":204},[160],{"categories":206},[160],{"categories":208},[157],{"categories":210},[160],{"categories":212},[157],{"categories":214},[157],{"categories":216},[157],{"categories":218},[192],{"categories":220},[157],{"categories":222},[157],{"categories":224},[],{"categories":226},[227],"Design & Frontend",{"categories":229},[230],"Data Science & Visualization",{"categories":232},[192],{"categories":234},[157],{"categories":236},[157],{"categories":238},[],{"categories":240},[157],{"categories":242},[160],{"categories":244},[170],{"categories":246},[157],{"categories":248},[160],{"categories":250},[157],{"categories":252},[253],"Marketing & Growth",{"categories":255},[227],{"categories":257},[157],{"categories":259},[160],{"categories":261},[157],{"categories":263},[],{"categories":265},[],{"categories":267},[227],{"categories":269},[157],{"categories":271},[160],{"categories":273},[151],{"categories":275},[170],{"categories":277},[227],{"categories":279},[157],{"categories":281},[170],{"categories":283},[284],"DevOps & Cloud",{"categories":286},[160],{"categories":288},[163],{"categories":290},[192],{"categories":292},[157],{"categories":294},[],{"categories":296},[157],{"categories":298},[],{"categories":300},[160],{"categories":302},[170],{"categories":304},[],{"categories":306},[170],{"categories":308},[309],"Governance & Standards",{"categories":311},[154],{"categories":313},[],{"categories":315},[],{"categories":317},[157],{"categories":319},[157],{"categories":321},[160],{"categories":323},[157],{"categories":325},[157],{"categories":327},[160],{"categories":329},[157],{"categories":331},[157],{"categories":333},[157],{"categories":335},[],{"categories":337},[170],{"categories":339},[],{"categories":341},[],{"categories":343},[170],{"categories":345},[],{"categories":347},[170],{"categories":349},[157],{"categories":351},[157],{"categories":353},[253],{"categories":355},[157],{"categories":357},[227],{"categories":359},[227],{"categories":361},[157],{"categories":363},[170],{"categories":365},[160],{"categories":367},[368],"GovTech & Public-Sector Adoption",{"categories":370},[170],{"categories":372},[157],{"categories":374},[157],{"categories":376},[160],{"categories":378},[160],{"categories":380},[230],{"categories":382},[192],{"categories":384},[160],{"categories":386},[387],"Legal AI Tools",{"categories":389},[160],{"categories":391},[253],{"categories":393},[160],{"categories":395},[163],{"categories":397},[170],{"categories":399},[368],{"categories":401},[],{"categories":403},[160],{"categories":405},[],{"categories":407},[160],{"categories":409},[160],{"categories":411},[105],{"categories":413},[154],{"categories":415},[157],{"categories":417},[170],{"categories":419},[284],{"categories":421},[227],{"categories":423},[157],{"categories":425},[],{"categories":427},[428],"Agents & Orchestration",{"categories":430},[170],{"categories":432},[157],{"categories":434},[],{"categories":436},[160],{"categories":438},[],{"categories":440},[157],{"categories":442},[],{"categories":444},[151],{"categories":446},[170],{"categories":448},[154],{"categories":450},[157],{"categories":452},[157],{"categories":454},[192],{"categories":456},[157],{"categories":458},[],{"categories":460},[157],{"categories":462},[],{"categories":464},[170],{"categories":466},[230],{"categories":468},[],{"categories":470},[157],{"categories":472},[227],{"categories":474},[475],"Models & Frontier Labs",{"categories":477},[],{"categories":479},[227],{"categories":481},[482],"Regulation & Governance of AI",{"categories":484},[160],{"categories":486},[],{"categories":488},[157],{"categories":490},[157],{"categories":492},[160],{"categories":494},[192],{"categories":496},[154],{"categories":498},[157],{"categories":500},[],{"categories":502},[170],{"categories":504},[160],{"categories":506},[157],{"categories":508},[163],{"categories":510},[511],"AI Policy & Regulation",{"categories":513},[],{"categories":515},[157],{"categories":517},[163],{"categories":519},[160],{"categories":521},[157],{"categories":523},[160],{"categories":525},[],{"categories":527},[230],{"categories":529},[530],"Evals & Reliability",{"categories":532},[157],{"categories":534},[],{"categories":536},[151],{"categories":538},[368],{"categories":540},[511],{"categories":542},[157],{"categories":544},[154],{"categories":546},[157],{"categories":548},[160],{"categories":550},[157],{"categories":552},[160],{"categories":554},[428],{"categories":556},[157],{"categories":558},[170],{"categories":560},[157],{"categories":562},[],{"categories":564},[],{"categories":566},[157],{"categories":568},[368],{"categories":570},[157],{"categories":572},[157],{"categories":574},[],{"categories":576},[227],{"categories":578},[],{"categories":580},[157],{"categories":582},[],{"categories":584},[160],{"categories":586},[157],{"categories":588},[227],{"categories":590},[],{"categories":592},[157],{"categories":594},[160],{"categories":596},[157],{"categories":598},[154],{"categories":600},[160],{"categories":602},[157],{"categories":604},[157],{"categories":606},[170],{"categories":608},[227],{"categories":610},[160],{"categories":612},[],{"categories":614},[170],{"categories":616},[160],{"categories":618},[],{"categories":620},[192],{"categories":622},[],{"categories":624},[157],{"categories":626},[157],{"categories":628},[154,253],{"categories":630},[],{"categories":632},[157],{"categories":634},[157],{"categories":636},[160],{"categories":638},[],{"categories":640},[],{"categories":642},[157],{"categories":644},[227],{"categories":646},[157],{"categories":648},[],{"categories":650},[157],{"categories":652},[284],{"categories":654},[],{"categories":656},[160],{"categories":658},[192],{"categories":660},[157],{"categories":662},[227],{"categories":664},[],{"categories":666},[192],{"categories":668},[157],{"categories":670},[181],{"categories":672},[157],{"categories":674},[160],{"categories":676},[192],{"categories":678},[475],{"categories":680},[157],{"categories":682},[253],{"categories":684},[],{"categories":686},[160],{"categories":688},[154],{"categories":690},[170],{"categories":692},[157],{"categories":694},[160],{"categories":696},[],{"categories":698},[157,284],{"categories":700},[157],{"categories":702},[157],{"categories":704},[157],{"categories":706},[160],{"categories":708},[157,170],{"categories":710},[230],{"categories":712},[157],{"categories":714},[157],{"categories":716},[170],{"categories":718},[160],{"categories":720},[511],{"categories":722},[253],{"categories":724},[160],{"categories":726},[157],{"categories":728},[157],{"categories":730},[160],{"categories":732},[],{"categories":734},[428],{"categories":736},[160],{"categories":738},[157],{"categories":740},[157,154],{"categories":742},[154],{"categories":744},[],{"categories":746},[227],{"categories":748},[227],{"categories":750},[157],{"categories":752},[],{"categories":754},[],{"categories":756},[192],{"categories":758},[],{"categories":760},[151],{"categories":762},[157],{"categories":764},[170],{"categories":766},[767],"Generative UI & Design-to-Code",{"categories":769},[157],{"categories":771},[227],{"categories":773},[157],{"categories":775},[776],"Algorithmic Accountability",{"categories":778},[160],{"categories":780},[170],{"categories":782},[192],{"categories":784},[227],{"categories":786},[],{"categories":788},[157],{"categories":790},[157],{"categories":792},[157],{"categories":794},[160],{"categories":796},[797],"MLOps & Infrastructure",{"categories":799},[157],{"categories":801},[157],{"categories":803},[157],{"categories":805},[157],{"categories":807},[192],{"categories":809},[151],{"categories":811},[157],{"categories":813},[160],{"categories":815},[284],{"categories":817},[157],{"categories":819},[227],{"categories":821},[157],{"categories":823},[160],{"categories":825},[],{"categories":827},[],{"categories":829},[181],{"categories":831},[227],{"categories":833},[192],{"categories":835},[230],{"categories":837},[],{"categories":839},[157],{"categories":841},[157],{"categories":843},[154],{"categories":845},[157],{"categories":847},[157],{"categories":849},[157],{"categories":851},[192],{"categories":853},[181],{"categories":855},[157],{"categories":857},[227],{"categories":859},[],{"categories":861},[160],{"categories":863},[170],{"categories":865},[],{"categories":867},[157],{"categories":869},[157],{"categories":871},[160],{"categories":873},[170],{"categories":875},[157],{"categories":877},[230],{"categories":879},[],{"categories":881},[157],{"categories":883},[],{"categories":885},[157],{"categories":887},[],{"categories":889},[163],{"categories":891},[154],{"categories":893},[160],{"categories":895},[160],{"categories":897},[],{"categories":899},[151],{"categories":901},[157],{"categories":903},[154],{"categories":905},[192],{"categories":907},[151],{"categories":909},[],{"categories":911},[157],{"categories":913},[],{"categories":915},[],{"categories":917},[192],{"categories":919},[192],{"categories":921},[],{"categories":923},[428],{"categories":925},[157],{"categories":927},[227],{"categories":929},[170],{"categories":931},[],{"categories":933},[387],{"categories":935},[154],{"categories":937},[],{"categories":939},[],{"categories":941},[151],{"categories":943},[230],{"categories":945},[],{"categories":947},[253],{"categories":949},[160],{"categories":951},[154],{"categories":953},[160],{"categories":955},[154],{"categories":957},[170],{"categories":959},[],{"categories":961},[181],{"categories":963},[163],{"categories":965},[157],{"categories":967},[227],{"categories":969},[170],{"categories":971},[154],{"categories":973},[157],{"categories":975},[160],{"categories":977},[154],{"categories":979},[157],{"categories":981},[],{"categories":983},[],{"categories":985},[170],{"categories":987},[230],{"categories":989},[163],{"categories":991},[157],{"categories":993},[160],{"categories":995},[157],{"categories":997},[],{"categories":999},[192],{"categories":1001},[163],{"categories":1003},[157],{"categories":1005},[530],{"categories":1007},[284],{"categories":1009},[],{"categories":1011},[160],{"categories":1013},[],{"categories":1015},[151],{"categories":1017},[],{"categories":1019},[157],{"categories":1021},[157],{"categories":1023},[227],{"categories":1025},[253],{"categories":1027},[170],{"categories":1029},[160],{"categories":1031},[],{"categories":1033},[170],{"categories":1035},[151],{"categories":1037},[],{"categories":1039},[192],{"categories":1041},[157,284],{"categories":1043},[1044],"Design Systems for AI",{"categories":1046},[157],{"categories":1048},[192],{"categories":1050},[157],{"categories":1052},[157],{"categories":1054},[154],{"categories":1056},[157],{"categories":1058},[],{"categories":1060},[157],{"categories":1062},[154],{"categories":1064},[157],{"categories":1066},[],{"categories":1068},[160],{"categories":1070},[170],{"categories":1072},[170],{"categories":1074},[227],{"categories":1076},[192],{"categories":1078},[230],{"categories":1080},[157],{"categories":1082},[151],{"categories":1084},[511],{"categories":1086},[157],{"categories":1088},[160],{"categories":1090},[157],{"categories":1092},[170],{"categories":1094},[170],{"categories":1096},[],{"categories":1098},[],{"categories":1100},[160],{"categories":1102},[163],{"categories":1104},[],{"categories":1106},[157],{"categories":1108},[],{"categories":1110},[227],{"categories":1112},[160],{"categories":1114},[170],{"categories":1116},[227],{"categories":1118},[157],{"categories":1120},[227],{"categories":1122},[],{"categories":1124},[],{"categories":1126},[192],{"categories":1128},[160],{"categories":1130},[160],{"categories":1132},[157],{"categories":1134},[157],{"categories":1136},[157],{"categories":1138},[154],{"categories":1140},[157],{"categories":1142},[157],{"categories":1144},[],{"categories":1146},[170],{"categories":1148},[170],{"categories":1150},[157],{"categories":1152},[170],{"categories":1154},[154],{"categories":1156},[],{"categories":1158},[157],{"categories":1160},[157],{"categories":1162},[157],{"categories":1164},[160],{"categories":1166},[151],{"categories":1168},[154],{"categories":1170},[192],{"categories":1172},[160],{"categories":1174},[181],{"categories":1176},[253],{"categories":1178},[157],{"categories":1180},[160],{"categories":1182},[],{"categories":1184},[227],{"categories":1186},[],{"categories":1188},[157],{"categories":1190},[157],{"categories":1192},[],{"categories":1194},[170],{"categories":1196},[154],{"categories":1198},[1199],"Visual & Generative Media",{"categories":1201},[160],{"categories":1203},[],{"categories":1205},[157],{"categories":1207},[157],{"categories":1209},[284],{"categories":1211},[230],{"categories":1213},[511],{"categories":1215},[170],{"categories":1217},[253],{"categories":1219},[157],{"categories":1221},[227],{"categories":1223},[157],{"categories":1225},[170],{"categories":1227},[160],{"categories":1229},[],{"categories":1231},[],{"categories":1233},[160],{"categories":1235},[151],{"categories":1237},[160],{"categories":1239},[475],{"categories":1241},[157],{"categories":1243},[163],{"categories":1245},[154],{"categories":1247},[],{"categories":1249},[157],{"categories":1251},[163],{"categories":1253},[157],{"categories":1255},[157],{"categories":1257},[157],{"categories":1259},[157],{"categories":1261},[157],{"categories":1263},[253],{"categories":1265},[157],{"categories":1267},[428],{"categories":1269},[157],{"categories":1271},[157],{"categories":1273},[157],{"categories":1275},[157],{"categories":1277},[157],{"categories":1279},[227],{"categories":1281},[160],{"categories":1283},[],{"categories":1285},[160],{"categories":1287},[],{"categories":1289},[284],{"categories":1291},[170],{"categories":1293},[],{"categories":1295},[475],{"categories":1297},[160],{"categories":1299},[157],{"categories":1301},[227,157],{"categories":1303},[151],{"categories":1305},[],{"categories":1307},[157],{"categories":1309},[151],{"categories":1311},[1312],"Medical Imaging & Radiology",{"categories":1314},[227],{"categories":1316},[160],{"categories":1318},[170],{"categories":1320},[],{"categories":1322},[157],{"categories":1324},[157],{"categories":1326},[157],{"categories":1328},[],{"categories":1330},[],{"categories":1332},[157],{"categories":1334},[428],{"categories":1336},[157],{"categories":1338},[151],{"categories":1340},[157],{"categories":1342},[157],{"categories":1344},[],{"categories":1346},[160],{"categories":1348},[157],{"categories":1350},[163],{"categories":1352},[170],{"categories":1354},[157],{"categories":1356},[428],{"categories":1358},[157],{"categories":1360},[160],{"categories":1362},[157],{"categories":1364},[227],{"categories":1366},[160],{"categories":1368},[284],{"categories":1370},[227],{"categories":1372},[154],{"categories":1374},[160],{"categories":1376},[157],{"categories":1378},[157],{"categories":1380},[157],{"categories":1382},[160],{"categories":1384},[170],{"categories":1386},[157],{"categories":1388},[163],{"categories":1390},[],{"categories":1392},[192],{"categories":1394},[],{"categories":1396},[163],{"categories":1398},[160],{"categories":1400},[1044],{"categories":1402},[1044],{"categories":1404},[227],{"categories":1406},[157],{"categories":1408},[157],{"categories":1410},[160],{"categories":1412},[170],{"categories":1414},[227],{"categories":1416},[160],{"categories":1418},[192],{"categories":1420},[],{"categories":1422},[157],{"categories":1424},[],{"categories":1426},[157],{"categories":1428},[157],{"categories":1430},[1431],"Contract Review & E-Discovery",{"categories":1433},[227],{"categories":1435},[157],{"categories":1437},[151],{"categories":1439},[192],{"categories":1441},[157],{"categories":1443},[157],{"categories":1445},[253],{"categories":1447},[157],{"categories":1449},[157],{"categories":1451},[160],{"categories":1453},[160],{"categories":1455},[776],{"categories":1457},[160],{"categories":1459},[428],{"categories":1461},[157],{"categories":1463},[157],{"categories":1465},[160],{"categories":1467},[157],{"categories":1469},[428],{"categories":1471},[105],{"categories":1473},[157],{"categories":1475},[160],{"categories":1477},[157],{"categories":1479},[1480],"Law-Firm Practice & Adoption",{"categories":1482},[157],{"categories":1484},[160],{"categories":1486},[227],{"categories":1488},[157],{"categories":1490},[157],{"categories":1492},[],{"categories":1494},[],{"categories":1496},[170],{"categories":1498},[],{"categories":1500},[151],{"categories":1502},[284],{"categories":1504},[157],{"categories":1506},[],{"categories":1508},[151],{"categories":1510},[154],{"categories":1512},[157],{"categories":1514},[253],{"categories":1516},[],{"categories":1518},[154],{"categories":1520},[154],{"categories":1522},[],{"categories":1524},[157],{"categories":1526},[157],{"categories":1528},[170],{"categories":1530},[],{"categories":1532},[],{"categories":1534},[],{"categories":1536},[],{"categories":1538},[157],{"categories":1540},[160],{"categories":1542},[284],{"categories":1544},[157],{"categories":1546},[151],{"categories":1548},[170],{"categories":1550},[157],{"categories":1552},[157],{"categories":1554},[170],{"categories":1556},[163],{"categories":1558},[157],{"categories":1560},[797],{"categories":1562},[157],{"categories":1564},[253],{"categories":1566},[170],{"categories":1568},[154],{"categories":1570},[157],{"categories":1572},[157],{"categories":1574},[227],{"categories":1576},[157],{"categories":1578},[157],{"categories":1580},[157],{"categories":1582},[160],{"categories":1584},[157,151],{"categories":1586},[428],{"categories":1588},[157],{"categories":1590},[170],{"categories":1592},[170],{"categories":1594},[227],{"categories":1596},[160],{"categories":1598},[170],{"categories":1600},[157],{"categories":1602},[157],{"categories":1604},[],{"categories":1606},[],{"categories":1608},[157],{"categories":1610},[],{"categories":1612},[157],{"categories":1614},[170],{"categories":1616},[230],{"categories":1618},[192],{"categories":1620},[227],{"categories":1622},[157],{"categories":1624},[170],{"categories":1626},[],{"categories":1628},[160],{"categories":1630},[157],{"categories":1632},[157],{"categories":1634},[157],{"categories":1636},[157],{"categories":1638},[],{"categories":1640},[160],{"categories":1642},[157],{"categories":1644},[157],{"categories":1646},[],{"categories":1648},[160],{"categories":1650},[157],{"categories":1652},[154],{"categories":1654},[157],{"categories":1656},[],{"categories":1658},[151],{"categories":1660},[157],{"categories":1662},[227],{"categories":1664},[170],{"categories":1666},[157],{"categories":1668},[151],{"categories":1670},[157],{"categories":1672},[170],{"categories":1674},[253],{"categories":1676},[160],{"categories":1678},[160],{"categories":1680},[157,227],{"categories":1682},[157],{"categories":1684},[192],{"categories":1686},[157],{"categories":1688},[192],{"categories":1690},[160],{"categories":1692},[227],{"categories":1694},[],{"categories":1696},[170],{"categories":1698},[284],{"categories":1700},[227],{"categories":1702},[170],{"categories":1704},[157],{"categories":1706},[163],{"categories":1708},[157],{"categories":1710},[160],{"categories":1712},[],{"categories":1714},[],{"categories":1716},[],{"categories":1718},[],{"categories":1720},[163],{"categories":1722},[170],{"categories":1724},[157],{"categories":1726},[160],{"categories":1728},[160],{"categories":1730},[154],{"categories":1732},[160],{"categories":1734},[284],{"categories":1736},[157],{"categories":1738},[157],{"categories":1740},[181],{"categories":1742},[428],{"categories":1744},[157],{"categories":1746},[160],{"categories":1748},[157],{"categories":1750},[157],{"categories":1752},[387],{"categories":1754},[776],{"categories":1756},[],{"categories":1758},[227],{"categories":1760},[1480],{"categories":1762},[170],{"categories":1764},[],{"categories":1766},[],{"categories":1768},[160],{"categories":1770},[],{"categories":1772},[],{"categories":1774},[253],{"categories":1776},[253],{"categories":1778},[160],{"categories":1780},[170],{"categories":1782},[],{"categories":1784},[157],{"categories":1786},[157],{"categories":1788},[170],{"categories":1790},[1431],{"categories":1792},[227],{"categories":1794},[227],{"categories":1796},[157],{"categories":1798},[160],{"categories":1800},[151],{"categories":1802},[157],{"categories":1804},[157],{"categories":1806},[227],{"categories":1808},[227],{"categories":1810},[160],{"categories":1812},[160],{"categories":1814},[157],{"categories":1816},[],{"categories":1818},[157],{"categories":1820},[],{"categories":1822},[1823],"Interaction & Product Design",{"categories":1825},[157],{"categories":1827},[160],{"categories":1829},[309],{"categories":1831},[192],{"categories":1833},[170],{"categories":1835},[157],{"categories":1837},[170],{"categories":1839},[151],{"categories":1841},[157],{"categories":1843},[],{"categories":1845},[160],{"categories":1847},[160],{"categories":1849},[],{"categories":1851},[170],{"categories":1853},[157],{"categories":1855},[151],{"categories":1857},[1823],{"categories":1859},[157],{"categories":1861},[151],{"categories":1863},[151],{"categories":1865},[],{"categories":1867},[170],{"categories":1869},[],{"categories":1871},[160],{"categories":1873},[192],{"categories":1875},[157],{"categories":1877},[160],{"categories":1879},[157],{"categories":1881},[160],{"categories":1883},[157],{"categories":1885},[192],{"categories":1887},[230],{"categories":1889},[157],{"categories":1891},[163],{"categories":1893},[170],{"categories":1895},[1896],"Coding Agents & Dev Productivity",{"categories":1898},[192],{"categories":1900},[227],{"categories":1902},[],{"categories":1904},[776],{"categories":1906},[],{"categories":1908},[157],{"categories":1910},[157],{"categories":1912},[192],{"categories":1914},[],{"categories":1916},[],{"categories":1918},[],{"categories":1920},[160],{"categories":1922},[157],{"categories":1924},[],{"categories":1926},[170],{"categories":1928},[170],{"categories":1930},[157],{"categories":1932},[230],{"categories":1934},[],{"categories":1936},[157],{"categories":1938},[157],{"categories":1940},[157],{"categories":1942},[230],{"categories":1944},[170],{"categories":1946},[],{"categories":1948},[],{"categories":1950},[160],{"categories":1952},[160],{"categories":1954},[368],{"categories":1956},[170],{"categories":1958},[170],{"categories":1960},[160],{"categories":1962},[192],{"categories":1964},[192],{"categories":1966},[160],{"categories":1968},[160],{"categories":1970},[157],{"categories":1972},[151],{"categories":1974},[1823],{"categories":1976},[157,284],{"categories":1978},[],{"categories":1980},[227],{"categories":1982},[170],{"categories":1984},[151],{"categories":1986},[157],{"categories":1988},[160],{"categories":1990},[1991],"The Designer's Role & Craft",{"categories":1993},[227],{"categories":1995},[],{"categories":1997},[160],{"categories":1999},[157],{"categories":2001},[160],{"categories":2003},[160],{"categories":2005},[157],{"categories":2007},[253],{"categories":2009},[157],{"categories":2011},[170],{"categories":2013},[227],{"categories":2015},[157],{"categories":2017},[],{"categories":2019},[160],{"categories":2021},[227],{"categories":2023},[157],{"categories":2025},[157],{"categories":2027},[2028],"AI UX Patterns",{"categories":2030},[160],{"categories":2032},[160],{"categories":2034},[160],{"categories":2036},[160],{"categories":2038},[253],{"categories":2040},[230],{"categories":2042},[157],{"categories":2044},[160],{"categories":2046},[157],{"categories":2048},[1044],{"categories":2050},[],{"categories":2052},[253],{"categories":2054},[192],{"categories":2056},[170],{"categories":2058},[157],{"categories":2060},[160],{"categories":2062},[],{"categories":2064},[],{"categories":2066},[157],{"categories":2068},[160],{"categories":2070},[157],{"categories":2072},[160],{"categories":2074},[368],{"categories":2076},[227],{"categories":2078},[192],{"categories":2080},[170],{"categories":2082},[157],{"categories":2084},[160],{"categories":2086},[160],{"categories":2088},[],{"categories":2090},[157],{"categories":2092},[],{"categories":2094},[],{"categories":2096},[157],{"categories":2098},[157],{"categories":2100},[160],{"categories":2102},[170],{"categories":2104},[],{"categories":2106},[],{"categories":2108},[230],{"categories":2110},[181],{"categories":2112},[157],{"categories":2114},[230],{"categories":2116},[192],{"categories":2118},[157],{"categories":2120},[157],{"categories":2122},[160],{"categories":2124},[160],{"categories":2126},[157],{"categories":2128},[160],{"categories":2130},[],{"categories":2132},[],{"categories":2134},[157],{"categories":2136},[284],{"categories":2138},[157],{"categories":2140},[],{"categories":2142},[],{"categories":2144},[227],{"categories":2146},[797],{"categories":2148},[160],{"categories":2150},[151],{"categories":2152},[1991],{"categories":2154},[],{"categories":2156},[],{"categories":2158},[157],{"categories":2160},[],{"categories":2162},[],{"categories":2164},[170],{"categories":2166},[192],{"categories":2168},[253],{"categories":2170},[154],{"categories":2172},[157],{"categories":2174},[157],{"categories":2176},[154],{"categories":2178},[],{"categories":2180},[227],{"categories":2182},[157],{"categories":2184},[160],{"categories":2186},[154],{"categories":2188},[157],{"categories":2190},[157],{"categories":2192},[151],{"categories":2194},[157],{"categories":2196},[],{"categories":2198},[151],{"categories":2200},[157],{"categories":2202},[253],{"categories":2204},[160],{"categories":2206},[192],{"categories":2208},[157],{"categories":2210},[154],{"categories":2212},[157],{"categories":2214},[157],{"categories":2216},[157],{"categories":2218},[160],{"categories":2220},[],{"categories":2222},[157],{"categories":2224},[170],{"categories":2226},[151],{"categories":2228},[157],{"categories":2230},[157],{"categories":2232},[],{"categories":2234},[428],{"categories":2236},[192],{"categories":2238},[157],{"categories":2240},[157],{"categories":2242},[],{"categories":2244},[154],{"categories":2246},[154],{"categories":2248},[157],{"categories":2250},[157],{"categories":2252},[163],{"categories":2254},[157],{"categories":2256},[157],{"categories":2258},[170],{"categories":2260},[170],{"categories":2262},[157],{"categories":2264},[],{"categories":2266},[170],{"categories":2268},[157],{"categories":2270},[511],{"categories":2272},[],{"categories":2274},[],{"categories":2276},[157],{"categories":2278},[192],{"categories":2280},[],{"categories":2282},[284],{"categories":2284},[157],{"categories":2286},[157],{"categories":2288},[227],{"categories":2290},[767],{"categories":2292},[],{"categories":2294},[157],{"categories":2296},[170],{"categories":2298},[157],{"categories":2300},[157],{"categories":2302},[157,284],{"categories":2304},[157],{"categories":2306},[157],{"categories":2308},[227],{"categories":2310},[160],{"categories":2312},[],{"categories":2314},[160],{"categories":2316},[160],{"categories":2318},[157],{"categories":2320},[157],{"categories":2322},[157],{"categories":2324},[230],{"categories":2326},[157],{"categories":2328},[2028],{"categories":2330},[151],{"categories":2332},[230],{"categories":2334},[151],{"categories":2336},[170],{"categories":2338},[227],{"categories":2340},[160],{"categories":2342},[157],{"categories":2344},[],{"categories":2346},[157],{"categories":2348},[192],{"categories":2350},[157],{"categories":2352},[160],{"categories":2354},[157],{"categories":2356},[157],{"categories":2358},[154],{"categories":2360},[],{"categories":2362},[284],{"categories":2364},[157],{"categories":2366},[368],{"categories":2368},[227],{"categories":2370},[227],{"categories":2372},[170],{"categories":2374},[160],{"categories":2376},[157],{"categories":2378},[154],{"categories":2380},[192],{"categories":2382},[157],{"categories":2384},[227],{"categories":2386},[160],{"categories":2388},[157],{"categories":2390},[157],{"categories":2392},[475],{"categories":2394},[],{"categories":2396},[157],{"categories":2398},[157],{"categories":2400},[157],{"categories":2402},[],{"categories":2404},[],{"categories":2406},[157],{"categories":2408},[157],{"categories":2410},[157],{"categories":2412},[157],{"categories":2414},[170],{"categories":2416},[157],{"categories":2418},[157],{"categories":2420},[160],{"categories":2422},[157],{"categories":2424},[157],{"categories":2426},[157],{"categories":2428},[157],{"categories":2430},[],{"categories":2432},[230],{"categories":2434},[157],{"categories":2436},[160],{"categories":2438},[157],{"categories":2440},[],{"categories":2442},[],{"categories":2444},[157],{"categories":2446},[157],{"categories":2448},[157],{"categories":2450},[192],{"categories":2452},[],{"categories":2454},[157],{"categories":2456},[227],{"categories":2458},[157],{"categories":2460},[284],{"categories":2462},[1480],{"categories":2464},[192],{"categories":2466},[170],{"categories":2468},[170],{"categories":2470},[170],{"categories":2472},[192],{"categories":2474},[192],{"categories":2476},[284],{"categories":2478},[],{"categories":2480},[192],{"categories":2482},[157],{"categories":2484},[151],{"categories":2486},[170],{"categories":2488},[157],{"categories":2490},[192],{"categories":2492},[],{"categories":2494},[157],{"categories":2496},[170],{"categories":2498},[230],{"categories":2500},[157],{"categories":2502},[192],{"categories":2504},[157],{"categories":2506},[170],{"categories":2508},[160],{"categories":2510},[192],{"categories":2512},[160],{"categories":2514},[284],{"categories":2516},[160],{"categories":2518},[157],{"categories":2520},[157],{"categories":2522},[170],{"categories":2524},[157],{"categories":2526},[],{"categories":2528},[154],{"categories":2530},[170],{"categories":2532},[],{"categories":2534},[],{"categories":2536},[157],{"categories":2538},[160],{"categories":2540},[157],{"categories":2542},[2543],"Frameworks & Tooling",{"categories":2545},[157],{"categories":2547},[157],{"categories":2549},[157],{"categories":2551},[157],{"categories":2553},[],{"categories":2555},[230],{"categories":2557},[230],{"categories":2559},[151],{"categories":2561},[160],{"categories":2563},[227],{"categories":2565},[],{"categories":2567},[1480],{"categories":2569},[157],{"categories":2571},[170],{"categories":2573},[157],{"categories":2575},[284],{"categories":2577},[284],{"categories":2579},[],{"categories":2581},[160],{"categories":2583},[192],{"categories":2585},[192],{"categories":2587},[157],{"categories":2589},[160],{"categories":2591},[],{"categories":2593},[227],{"categories":2595},[157],{"categories":2597},[157],{"categories":2599},[],{"categories":2601},[157],{"categories":2603},[],{"categories":2605},[170],{"categories":2607},[157],{"categories":2609},[170],{"categories":2611},[284],{"categories":2613},[157],{"categories":2615},[170],{"categories":2617},[154],{"categories":2619},[157],{"categories":2621},[1480],{"categories":2623},[],{"categories":2625},[160],{"categories":2627},[151],{"categories":2629},[151],{"categories":2631},[],{"categories":2633},[160],{"categories":2635},[157],{"categories":2637},[2638],"AI Design Tooling",{"categories":2640},[227],{"categories":2642},[157],{"categories":2644},[157],{"categories":2646},[170],{"categories":2648},[227],{"categories":2650},[157],{"categories":2652},[170],{"categories":2654},[192],{"categories":2656},[163],{"categories":2658},[170],{"categories":2660},[160],{"categories":2662},[],{"categories":2664},[157],{"categories":2666},[157],{"categories":2668},[160],{"categories":2670},[157],{"categories":2672},[157],{"categories":2674},[],{"categories":2676},[160],{"categories":2678},[2543],{"categories":2680},[157],{"categories":2682},[160],{"categories":2684},[160],{"categories":2686},[170],{"categories":2688},[170],{"categories":2690},[],{"categories":2692},[170],{"categories":2694},[157],{"categories":2696},[157],{"categories":2698},[160],{"categories":2700},[154],{"categories":2702},[157],{"categories":2704},[],{"categories":2706},[157],{"categories":2708},[1823],{"categories":2710},[],{"categories":2712},[157],{"categories":2714},[157],{"categories":2716},[],{"categories":2718},[157],{"categories":2720},[428],{"categories":2722},[157],{"categories":2724},[253],{"categories":2726},[192],{"categories":2728},[157],{"categories":2730},[157],{"categories":2732},[1480],{"categories":2734},[151],{"categories":2736},[157],{"categories":2738},[157],{"categories":2740},[230],{"categories":2742},[157],{"categories":2744},[192],{"categories":2746},[160],{"categories":2748},[],{"categories":2750},[157],{"categories":2752},[227],{"categories":2754},[157],{"categories":2756},[253],{"categories":2758},[157],{"categories":2760},[160],{"categories":2762},[],{"categories":2764},[],{"categories":2766},[],{"categories":2768},[151],{"categories":2770},[192],{"categories":2772},[160],{"categories":2774},[157],{"categories":2776},[157],{"categories":2778},[157],{"categories":2780},[387],{"categories":2782},[227],{"categories":2784},[160],{"categories":2786},[157],{"categories":2788},[],{"categories":2790},[160],{"categories":2792},[160],{"categories":2794},[],{"categories":2796},[157],{"categories":2798},[160],{"categories":2800},[157],{"categories":2802},[],{"categories":2804},[157],{"categories":2806},[157],{"categories":2808},[192],{"categories":2810},[227],{"categories":2812},[160],{"categories":2814},[227],{"categories":2816},[160],{"categories":2818},[154],{"categories":2820},[],{"categories":2822},[],{"categories":2824},[157],{"categories":2826},[157],{"categories":2828},[151],{"categories":2830},[160],{"categories":2832},[192],{"categories":2834},[],{"categories":2836},[227],{"categories":2838},[],{"categories":2840},[170],{"categories":2842},[170],{"categories":2844},[227],{"categories":2846},[170],{"categories":2848},[157],{"categories":2850},[],{"categories":2852},[157],{"categories":2854},[157],{"categories":2856},[],{"categories":2858},[253],{"categories":2860},[157],{"categories":2862},[284],{"categories":2864},[170],{"categories":2866},[],{"categories":2868},[160],{"categories":2870},[157],{"categories":2872},[151],{"categories":2874},[475],{"categories":2876},[160],{"categories":2878},[160],{"categories":2880},[157],{"categories":2882},[157],{"categories":2884},[],{"categories":2886},[151],{"categories":2888},[157],{"categories":2890},[154],{"categories":2892},[170],{"categories":2894},[227],{"categories":2896},[],{"categories":2898},[],{"categories":2900},[],{"categories":2902},[160],{"categories":2904},[170],{"categories":2906},[227],{"categories":2908},[192],{"categories":2910},[157],{"categories":2912},[192],{"categories":2914},[160],{"categories":2916},[227],{"categories":2918},[157],{"categories":2920},[],{"categories":2922},[157],{"categories":2924},[181],{"categories":2926},[160],{"categories":2928},[227],{"categories":2930},[192],{"categories":2932},[154],{"categories":2934},[170],{"categories":2936},[157],{"categories":2938},[192],{"categories":2940},[253],{"categories":2942},[],{"categories":2944},[],{"categories":2946},[230],{"categories":2948},[428],{"categories":2950},[157],{"categories":2952},[160],{"categories":2954},[157,170],{"categories":2956},[192],{"categories":2958},[157],{"categories":2960},[157],{"categories":2962},[160],{"categories":2964},[157],{"categories":2966},[160],{"categories":2968},[157],{"categories":2970},[157],{"categories":2972},[],{"categories":2974},[1044],{"categories":2976},[170],{"categories":2978},[227],{"categories":2980},[157],{"categories":2982},[157],{"categories":2984},[230],{"categories":2986},[160],{"categories":2988},[253],{"categories":2990},[284],{"categories":2992},[],{"categories":2994},[157],{"categories":2996},[154],{"categories":2998},[160],{"categories":3000},[151],{"categories":3002},[160],{"categories":3004},[157],{"categories":3006},[160],{"categories":3008},[163],{"categories":3010},[170],{"categories":3012},[157],{"categories":3014},[157],{"categories":3016},[],{"categories":3018},[],{"categories":3020},[],{"categories":3022},[284],{"categories":3024},[157],{"categories":3026},[192],{"categories":3028},[157],{"categories":3030},[157],{"categories":3032},[157],{"categories":3034},[157],{"categories":3036},[],{"categories":3038},[230],{"categories":3040},[154],{"categories":3042},[160],{"categories":3044},[157],{"categories":3046},[],{"categories":3048},[157],{"categories":3050},[160],{"categories":3052},[157],{"categories":3054},[284],{"categories":3056},[],{"categories":3058},[227],{"categories":3060},[227],{"categories":3062},[],{"categories":3064},[170],{"categories":3066},[157],{"categories":3068},[227],{"categories":3070},[157],{"categories":3072},[154],{"categories":3074},[160],{"categories":3076},[157],{"categories":3078},[],{"categories":3080},[192],{"categories":3082},[157],{"categories":3084},[157],{"categories":3086},[227],{"categories":3088},[160],{"categories":3090},[192],{"categories":3092},[],{"categories":3094},[160],{"categories":3096},[160],{"categories":3098},[227],{"categories":3100},[157],{"categories":3102},[157],{"categories":3104},[157],{"categories":3106},[428],{"categories":3108},[157],{"categories":3110},[],{"categories":3112},[157],{"categories":3114},[157],{"categories":3116},[284],{"categories":3118},[192],{"categories":3120},[230],{"categories":3122},[511],{"categories":3124},[230],{"categories":3126},[],{"categories":3128},[],{"categories":3130},[],{"categories":3132},[160],{"categories":3134},[160],{"categories":3136},[170],{"categories":3138},[157],{"categories":3140},[105],{"categories":3142},[170],{"categories":3144},[157],{"categories":3146},[157],{"categories":3148},[157],{"categories":3150},[157],{"categories":3152},[160],{"categories":3154},[],{"categories":3156},[],{"categories":3158},[157],{"categories":3160},[],{"categories":3162},[157],{"categories":3164},[160],{"categories":3166},[227],{"categories":3168},[157],{"categories":3170},[157],{"categories":3172},[],{"categories":3174},[163],{"categories":3176},[157],{"categories":3178},[227],{"categories":3180},[157],{"categories":3182},[154],{"categories":3184},[157],{"categories":3186},[253],{"categories":3188},[160],{"categories":3190},[157],{"categories":3192},[767],{"categories":3194},[157],{"categories":3196},[160],{"categories":3198},[157],{"categories":3200},[170],{"categories":3202},[157],{"categories":3204},[475],{"categories":3206},[227],{"categories":3208},[],{"categories":3210},[192],{"categories":3212},[428],{"categories":3214},[160],{"categories":3216},[157],{"categories":3218},[],{"categories":3220},[192],{"categories":3222},[368],{"categories":3224},[160],{"categories":3226},[160],{"categories":3228},[157],{"categories":3230},[157],{"categories":3232},[160],{"categories":3234},[],{"categories":3236},[154],{"categories":3238},[160],{"categories":3240},[],{"categories":3242},[170],{"categories":3244},[157],{"categories":3246},[151],{"categories":3248},[192],{"categories":3250},[284],{"categories":3252},[181],{"categories":3254},[160],{"categories":3256},[160],{"categories":3258},[157],{"categories":3260},[160],{"categories":3262},[151],{"categories":3264},[],{"categories":3266},[157],{"categories":3268},[157],{"categories":3270},[],{"categories":3272},[],{"categories":3274},[227],{"categories":3276},[157,154],{"categories":3278},[160],{"categories":3280},[157],{"categories":3282},[],{"categories":3284},[151],{"categories":3286},[230],{"categories":3288},[154],{"categories":3290},[157],{"categories":3292},[170],{"categories":3294},[157],{"categories":3296},[160],{"categories":3298},[157],{"categories":3300},[157],{"categories":3302},[157],{"categories":3304},[192],{"categories":3306},[1044],{"categories":3308},[160],{"categories":3310},[157],{"categories":3312},[],{"categories":3314},[],{"categories":3316},[160],{"categories":3318},[157],{"categories":3320},[284],{"categories":3322},[],{"categories":3324},[157],{"categories":3326},[160],{"categories":3328},[181],{"categories":3330},[160],{"categories":3332},[428],{"categories":3334},[],{"categories":3336},[387],{"categories":3338},[160],{"categories":3340},[157],{"categories":3342},[253],{"categories":3344},[157],{"categories":3346},[230],{"categories":3348},[160],{"categories":3350},[157],{"categories":3352},[428],{"categories":3354},[157],{"categories":3356},[284],{"categories":3358},[],{"categories":3360},[157],{"categories":3362},[253],{"categories":3364},[227],{"categories":3366},[157],{"categories":3368},[157],{"categories":3370},[],{"categories":3372},[253],{"categories":3374},[192],{"categories":3376},[157],{"categories":3378},[157],{"categories":3380},[511],{"categories":3382},[151],{"categories":3384},[157],{"categories":3386},[],{"categories":3388},[],{"categories":3390},[227],{"categories":3392},[157],{"categories":3394},[230],{"categories":3396},[253],{"categories":3398},[160],{"categories":3400},[253],{"categories":3402},[192],{"categories":3404},[],{"categories":3406},[157],{"categories":3408},[],{"categories":3410},[157],{"categories":3412},[530],{"categories":3414},[157],{"categories":3416},[157],{"categories":3418},[160],{"categories":3420},[428],{"categories":3422},[157],{"categories":3424},[157],{"categories":3426},[157],{"categories":3428},[],{"categories":3430},[157,170],{"categories":3432},[192],{"categories":3434},[160],{"categories":3436},[170],{"categories":3438},[160],{"categories":3440},[797],{"categories":3442},[170],{"categories":3444},[157],{"categories":3446},[151],{"categories":3448},[],{"categories":3450},[],{"categories":3452},[160],{"categories":3454},[157],{"categories":3456},[170],{"categories":3458},[151],{"categories":3460},[170],{"categories":3462},[170],{"categories":3464},[157],{"categories":3466},[253],{"categories":3468},[157],{"categories":3470},[170],{"categories":3472},[],{"categories":3474},[157],{"categories":3476},[227,157],{"categories":3478},[284],{"categories":3480},[151],{"categories":3482},[],{"categories":3484},[157],{"categories":3486},[428],{"categories":3488},[154],{"categories":3490},[154],{"categories":3492},[157],{"categories":3494},[157],{"categories":3496},[368],{"categories":3498},[157],{"categories":3500},[170],{"categories":3502},[160],{"categories":3504},[157],{"categories":3506},[157],{"categories":3508},[192],{"categories":3510},[253],{"categories":3512},[227],{"categories":3514},[157],{"categories":3516},[157],{"categories":3518},[157],{"categories":3520},[157],{"categories":3522},[151],{"categories":3524},[157],{"categories":3526},[160],{"categories":3528},[160],{"categories":3530},[170],{"categories":3532},[192],{"categories":3534},[170],{"categories":3536},[],{"categories":3538},[],{"categories":3540},[230],{"categories":3542},[157],{"categories":3544},[170],{"categories":3546},[157],{"categories":3548},[227],{"categories":3550},[428],{"categories":3552},[387],{"categories":3554},[368],{"categories":3556},[157],{"categories":3558},[157],{"categories":3560},[157],{"categories":3562},[230],{"categories":3564},[157],{"categories":3566},[157],{"categories":3568},[157],{"categories":3570},[160],{"categories":3572},[151],{"categories":3574},[160],{"categories":3576},[157,154],{"categories":3578},[],{"categories":3580},[227],{"categories":3582},[],{"categories":3584},[163],{"categories":3586},[157],{"categories":3588},[192],{"categories":3590},[151],{"categories":3592},[151],{"categories":3594},[160],{"categories":3596},[160],{"categories":3598},[160],{"categories":3600},[157],{"categories":3602},[157],{"categories":3604},[154],{"categories":3606},[170],{"categories":3608},[253],{"categories":3610},[157],{"categories":3612},[],{"categories":3614},[192],{"categories":3616},[157],{"categories":3618},[157],{"categories":3620},[157],{"categories":3622},[157],{"categories":3624},[157],{"categories":3626},[170],{"categories":3628},[192],{"categories":3630},[170],{"categories":3632},[170],{"categories":3634},[157],{"categories":3636},[157],{"categories":3638},[387],{"categories":3640},[157],{"categories":3642},[160],{"categories":3644},[192],{"categories":3646},[157],{"categories":3648},[157],{"categories":3650},[160],{"categories":3652},[157],{"categories":3654},[157],{"categories":3656},[157],{"categories":3658},[2543],{"categories":3660},[3661],"Clinical AI",{"categories":3663},[227],{"categories":3665},[157],{"categories":3667},[157],{"categories":3669},[157],{"categories":3671},[284],{"categories":3673},[2028],{"categories":3675},[157],{"categories":3677},[163],{"categories":3679},[157],{"categories":3681},[160],{"categories":3683},[157],{"categories":3685},[157],{"categories":3687},[192],{"categories":3689},[157],{"categories":3691},[160],{"categories":3693},[253],{"categories":3695},[157],{"categories":3697},[157],{"categories":3699},[154],{"categories":3701},[157],{"categories":3703},[475],{"categories":3705},[157],{"categories":3707},[],{"categories":3709},[157],{"categories":3711},[170],{"categories":3713},[157],{"categories":3715},[],{"categories":3717},[],{"categories":3719},[157],{"categories":3721},[],{"categories":3723},[154],{"categories":3725},[157],{"categories":3727},[160],{"categories":3729},[192],{"categories":3731},[192],{"categories":3733},[192],{"categories":3735},[192],{"categories":3737},[],{"categories":3739},[151],{"categories":3741},[160],{"categories":3743},[192],{"categories":3745},[157],{"categories":3747},[530],{"categories":3749},[163],{"categories":3751},[157],{"categories":3753},[151],{"categories":3755},[160],{"categories":3757},[157],{"categories":3759},[157,160],{"categories":3761},[160],{"categories":3763},[284],{"categories":3765},[192],{"categories":3767},[160],{"categories":3769},[192],{"categories":3771},[160],{"categories":3773},[157],{"categories":3775},[],{"categories":3777},[192],{"categories":3779},[253],{"categories":3781},[151],{"categories":3783},[157],{"categories":3785},[157],{"categories":3787},[],{"categories":3789},[170],{"categories":3791},[],{"categories":3793},[151],{"categories":3795},[160],{"categories":3797},[192],{"categories":3799},[157],{"categories":3801},[192],{"categories":3803},[151],{"categories":3805},[192],{"categories":3807},[192],{"categories":3809},[],{"categories":3811},[154],{"categories":3813},[160],{"categories":3815},[192],{"categories":3817},[192],{"categories":3819},[192],{"categories":3821},[192],{"categories":3823},[192],{"categories":3825},[192],{"categories":3827},[192],{"categories":3829},[192],{"categories":3831},[192],{"categories":3833},[192],{"categories":3835},[230],{"categories":3837},[151],{"categories":3839},[157],{"categories":3841},[157],{"categories":3843},[160],{"categories":3845},[160],{"categories":3847},[],{"categories":3849},[157,151],{"categories":3851},[],{"categories":3853},[160],{"categories":3855},[192],{"categories":3857},[160],{"categories":3859},[797],{"categories":3861},[157],{"categories":3863},[157],{"categories":3865},[157],{"categories":3867},[157],{"categories":3869},[368],{"categories":3871},[157],{"categories":3873},[160],{"categories":3875},[154],{"categories":3877},[160],{"categories":3879},[797],{"categories":3881},[],{"categories":3883},[160],{"categories":3885},[227],{"categories":3887},[192],{"categories":3889},[157],{"categories":3891},[],{"categories":3893},[],{"categories":3895},[160],{"categories":3897},[227],{"categories":3899},[157],{"categories":3901},[],{"categories":3903},[157],{"categories":3905},[],{"categories":3907},[253],{"categories":3909},[157],{"categories":3911},[],{"categories":3913},[],{"categories":3915},[192],{"categories":3917},[151],{"categories":3919},[157],{"categories":3921},[154],{"categories":3923},[157],{"categories":3925},[157],{"categories":3927},[157],{"categories":3929},[154],{"categories":3931},[227],{"categories":3933},[],{"categories":3935},[157],{"categories":3937},[192],{"categories":3939},[],{"categories":3941},[157],{"categories":3943},[157],{"categories":3945},[227],{"categories":3947},[157],{"categories":3949},[253],{"categories":3951},[157],{"categories":3953},[284],{"categories":3955},[],{"categories":3957},[160],{"categories":3959},[253],{"categories":3961},[170],{"categories":3963},[],{"categories":3965},[157],{"categories":3967},[],{"categories":3969},[160],{"categories":3971},[227],{"categories":3973},[170],{"categories":3975},[],{"categories":3977},[2543],{"categories":3979},[154],{"categories":3981},[151],{"categories":3983},[230],{"categories":3985},[160],{"categories":3987},[227],{"categories":3989},[170],{"categories":3991},[],{"categories":3993},[],{"categories":3995},[157],{"categories":3997},[151],{"categories":3999},[157],{"categories":4001},[253],{"categories":4003},[],{"categories":4005},[160],{"categories":4007},[160],{"categories":4009},[160],{"categories":4011},[192],{"categories":4013},[170],{"categories":4015},[157],{"categories":4017},[160],{"categories":4019},[163],{"categories":4021},[157],{"categories":4023},[160],{"categories":4025},[157],{"categories":4027},[163],{"categories":4029},[253],{"categories":4031},[192],{"categories":4033},[],{"categories":4035},[253],{"categories":4037},[],{"categories":4039},[170],{"categories":4041},[160],{"categories":4043},[],{"categories":4045},[157],{"categories":4047},[157],{"categories":4049},[157],{"categories":4051},[157],{"categories":4053},[160],{"categories":4055},[154],{"categories":4057},[151],{"categories":4059},[157],{"categories":4061},[227],{"categories":4063},[170],{"categories":4065},[170],{"categories":4067},[157],{"categories":4069},[230],{"categories":4071},[160],{"categories":4073},[157],{"categories":4075},[160],{"categories":4077},[157],{"categories":4079},[154],{"categories":4081},[227],{"categories":4083},[170],{"categories":4085},[160],{"categories":4087},[157],{"categories":4089},[163],{"categories":4091},[157],{"categories":4093},[160],{"categories":4095},[157],{"categories":4097},[192],{"categories":4099},[],{"categories":4101},[151],{"categories":4103},[157],{"categories":4105},[157],{"categories":4107},[157],{"categories":4109},[170],{"categories":4111},[157],{"categories":4113},[170],{"categories":4115},[157],{"categories":4117},[160],{"categories":4119},[157],{"categories":4121},[157],{"categories":4123},[157],{"categories":4125},[157],{"categories":4127},[],{"categories":4129},[157],{"categories":4131},[227],{"categories":4133},[154],{"categories":4135},[192],{"categories":4137},[160],{"categories":4139},[157],{"categories":4141},[157],{"categories":4143},[227],{"categories":4145},[160],{"categories":4147},[157],{"categories":4149},[253],{"categories":4151},[157],{"categories":4153},[230],{"categories":4155},[157],{"categories":4157},[157],{"categories":4159},[192],{"categories":4161},[157],{"categories":4163},[157],{"categories":4165},[160],{"categories":4167},[284],{"categories":4169},[157],{"categories":4171},[160],{"categories":4173},[230],{"categories":4175},[],{"categories":4177},[160],{"categories":4179},[170],{"categories":4181},[157],{"categories":4183},[1896],{"categories":4185},[227],{"categories":4187},[309],{"categories":4189},[157],{"categories":4191},[151],{"categories":4193},[170],{"categories":4195},[154],{"categories":4197},[170],{"categories":4199},[157],{"categories":4201},[],{"categories":4203},[160],{"categories":4205},[160],{"categories":4207},[157],{"categories":4209},[157],{"categories":4211},[230],{"categories":4213},[],{"categories":4215},[192],{"categories":4217},[],{"categories":4219},[192],{"categories":4221},[157],{"categories":4223},[157],{"categories":4225},[160],{"categories":4227},[160],{"categories":4229},[160],{"categories":4231},[],{"categories":4233},[192],{"categories":4235},[157],{"categories":4237},[],{"categories":4239},[157],{"categories":4241},[157],{"categories":4243},[],{"categories":4245},[227],{"categories":4247},[170],{"categories":4249},[160],{"categories":4251},[157],{"categories":4253},[157],{"categories":4255},[253],{"categories":4257},[157],{"categories":4259},[157],{"categories":4261},[151],{"categories":4263},[],{"categories":4265},[157],{"categories":4267},[157],{"categories":4269},[],{"categories":4271},[151],{"categories":4273},[192],{"categories":4275},[170],{"categories":4277},[428],{"categories":4279},[157],{"categories":4281},[157],{"categories":4283},[157],{"categories":4285},[170],{"categories":4287},[192],{"categories":4289},[227],{"categories":4291},[157],{"categories":4293},[157],{"categories":4295},[157],{"categories":4297},[192],{"categories":4299},[227],{"categories":4301},[157],{"categories":4303},[192],{"categories":4305},[227],{"categories":4307},[157],{"categories":4309},[192],{"categories":4311},[160],{"categories":4313},[160],{"categories":4315},[160],{"categories":4317},[170],{"categories":4319},[192],{"categories":4321},[160],{"categories":4323},[160],{"categories":4325},[157],{"categories":4327},[170],{"categories":4329},[227],{"categories":4331},[157],{"categories":4333},[],{"categories":4335},[160],{"categories":4337},[],{"categories":4339},[],{"categories":4341},[],{"categories":4343},[160],{"categories":4345},[154],{"categories":4347},[160],{"categories":4349},[4350],"Liability & Ethics",{"categories":4352},[157],{"categories":4354},[160],{"categories":4356},[151],{"categories":4358},[160],{"categories":4360},[154],{"categories":4362},[253],{"categories":4364},[160],{"categories":4366},[],{"categories":4368},[511],{"categories":4370},[160],{"categories":4372},[],{"categories":4374},[151],{"categories":4376},[160],{"categories":4378},[],{"categories":4380},[160],{"categories":4382},[157],{"categories":4384},[157],{"categories":4386},[192],{"categories":4388},[157],{"categories":4390},[157],{"categories":4392},[160],{"categories":4394},[157],{"categories":4396},[157],{"categories":4398},[192],{"categories":4400},[160],{"categories":4402},[170],{"categories":4404},[227],{"categories":4406},[151],{"categories":4408},[157],{"categories":4410},[],{"categories":4412},[160],{"categories":4414},[160],{"categories":4416},[428],{"categories":4418},[227],{"categories":4420},[284],{"categories":4422},[192],{"categories":4424},[157],{"categories":4426},[227],{"categories":4428},[157],{"categories":4430},[151],{"categories":4432},[],{"categories":4434},[160],{"categories":4436},[157],{"categories":4438},[157],{"categories":4440},[160],{"categories":4442},[157],{"categories":4444},[227],{"categories":4446},[],{"categories":4448},[160],{"categories":4450},[163],{"categories":4452},[192],{"categories":4454},[160],{"categories":4456},[154],{"categories":4458},[],{"categories":4460},[157],{"categories":4462},[163],{"categories":4464},[157],{"categories":4466},[160],{"categories":4468},[192],{"categories":4470},[151],{"categories":4472},[284],{"categories":4474},[157],{"categories":4476},[157],{"categories":4478},[157],{"categories":4480},[192],{"categories":4482},[154],{"categories":4484},[157],{"categories":4486},[227],{"categories":4488},[192],{"categories":4490},[284],{"categories":4492},[157],{"categories":4494},[160],{"categories":4496},[],{"categories":4498},[475],{"categories":4500},[],{"categories":4502},[157],{"categories":4504},[284],{"categories":4506},[230],{"categories":4508},[160],{"categories":4510},[160],{"categories":4512},[4513],"Design News & Tools",{"categories":4515},[157],{"categories":4517},[192],{"categories":4519},[157],{"categories":4521},[151],{"categories":4523},[157],{"categories":4525},[227],{"categories":4527},[160],{"categories":4529},[160],{"categories":4531},[157],{"categories":4533},[428],{"categories":4535},[157],{"categories":4537},[428],{"categories":4539},[253],{"categories":4541},[157],{"categories":4543},[160],{"categories":4545},[],{"categories":4547},[157],{"categories":4549},[157],{"categories":4551},[157],{"categories":4553},[192],{"categories":4555},[151],{"categories":4557},[],{"categories":4559},[157],{"categories":4561},[157],{"categories":4563},[170],{"categories":4565},[530],{"categories":4567},[170],{"categories":4569},[227],{"categories":4571},[157],{"categories":4573},[157,160],{"categories":4575},[253,154],{"categories":4577},[157],{"categories":4579},[157],{"categories":4581},[157],{"categories":4583},[],{"categories":4585},[160],{"categories":4587},[],{"categories":4589},[170],{"categories":4591},[157],{"categories":4593},[170],{"categories":4595},[],{"categories":4597},[160],{"categories":4599},[157],{"categories":4601},[192],{"categories":4603},[157],{"categories":4605},[],{"categories":4607},[160],{"categories":4609},[157],{"categories":4611},[],{"categories":4613},[227],{"categories":4615},[157],{"categories":4617},[160],{"categories":4619},[157],{"categories":4621},[157],{"categories":4623},[151],{"categories":4625},[160],{"categories":4627},[157],{"categories":4629},[],{"categories":4631},[284],{"categories":4633},[253],{"categories":4635},[154],{"categories":4637},[154],{"categories":4639},[157],{"categories":4641},[151],{"categories":4643},[151],{"categories":4645},[157],{"categories":4647},[160],{"categories":4649},[157],{"categories":4651},[157],{"categories":4653},[157],{"categories":4655},[170],{"categories":4657},[157],{"categories":4659},[151],{"categories":4661},[160],{"categories":4663},[157],{"categories":4665},[253],{"categories":4667},[428],{"categories":4669},[192],{"categories":4671},[157],{"categories":4673},[157],{"categories":4675},[160],{"categories":4677},[157],{"categories":4679},[],{"categories":4681},[170],{"categories":4683},[],{"categories":4685},[170],{"categories":4687},[160],{"categories":4689},[151],{"categories":4691},[],{"categories":4693},[230],{"categories":4695},[284],{"categories":4697},[157],{"categories":4699},[170],{"categories":4701},[157],{"categories":4703},[],{"categories":4705},[192],{"categories":4707},[160],{"categories":4709},[170],{"categories":4711},[227],{"categories":4713},[157],{"categories":4715},[160],{"categories":4717},[170],{"categories":4719},[160],{"categories":4721},[192],{"categories":4723},[157],{"categories":4725},[151],{"categories":4727},[192],{"categories":4729},[170],{"categories":4731},[157],{"categories":4733},[227],{"categories":4735},[154],{"categories":4737},[157],{"categories":4739},[157],{"categories":4741},[157],{"categories":4743},[157],{"categories":4745},[157],{"categories":4747},[160],{"categories":4749},[157],{"categories":4751},[160],{"categories":4753},[157],{"categories":4755},[157],{"categories":4757},[151],{"categories":4759},[157],{"categories":4761},[160],{"categories":4763},[160],{"categories":4765},[227],{"categories":4767},[160],{"categories":4769},[160],{"categories":4771},[151],{"categories":4773},[160],{"categories":4775},[227],{"categories":4777},[],{"categories":4779},[157],{"categories":4781},[230],{"categories":4783},[428],{"categories":4785},[157],{"categories":4787},[157],{"categories":4789},[157],{"categories":4791},[170],{"categories":4793},[],{"categories":4795},[160],{"categories":4797},[253],{"categories":4799},[157],{"categories":4801},[192],{"categories":4803},[160],{"categories":4805},[157],{"categories":4807},[253],{"categories":4809},[160],{"categories":4811},[154],{"categories":4813},[154],{"categories":4815},[157],{"categories":4817},[157],{"categories":4819},[157],{"categories":4821},[151],{"categories":4823},[],{"categories":4825},[157],{"categories":4827},[160],{"categories":4829},[160],{"categories":4831},[157],{"categories":4833},[157],{"categories":4835},[157],{"categories":4837},[170],{"categories":4839},[],{"categories":4841},[151],{"categories":4843},[157],{"categories":4845},[157],{"categories":4847},[160],{"categories":4849},[160],{"categories":4851},[],{"categories":4853},[170],{"categories":4855},[170],{"categories":4857},[157],{"categories":4859},[253],{"categories":4861},[227],{"categories":4863},[],{"categories":4865},[157],{"categories":4867},[160],{"categories":4869},[151],{"categories":4871},[157],{"categories":4873},[170],{"categories":4875},[151],{"categories":4877},[192],{"categories":4879},[230],{"categories":4881},[192],{"categories":4883},[160],{"categories":4885},[],{"categories":4887},[192],{"categories":4889},[160],{"categories":4891},[227],{"categories":4893},[230],{"categories":4895},[157],{"categories":4897},[],{"categories":4899},[160],{"categories":4901},[2543],{"categories":4903},[192],{"categories":4905},[170],{"categories":4907},[157],{"categories":4909},[157],{"categories":4911},[154],{"categories":4913},[157],{"categories":4915},[151],{"categories":4917},[1480],{"categories":4919},[284],{"categories":4921},[151],{"categories":4923},[],{"categories":4925},[],{"categories":4927},[192],{"categories":4929},[160],{"categories":4931},[192],{"categories":4933},[],{"categories":4935},[160],{"categories":4937},[160],{"categories":4939},[160],{"categories":4941},[],{"categories":4943},[157],{"categories":4945},[],{"categories":4947},[192],{"categories":4949},[151],{"categories":4951},[227],{"categories":4953},[157],{"categories":4955},[192],{"categories":4957},[157],{"categories":4959},[192],{"categories":4961},[],{"categories":4963},[192],{"categories":4965},[151],{"categories":4967},[428],{"categories":4969},[160],{"categories":4971},[157],{"categories":4973},[],{"categories":4975},[170],{"categories":4977},[160],{"categories":4979},[163],{"categories":4981},[160],{"categories":4983},[151],{"categories":4985},[],{"categories":4987},[],{"categories":4989},[],{"categories":4991},[227],{"categories":4993},[160],{"categories":4995},[157],{"categories":4997},[157],{"categories":4999},[],{"categories":5001},[],{"categories":5003},[],{"categories":5005},[227],{"categories":5007},[157],{"categories":5009},[],{"categories":5011},[160],{"categories":5013},[157],{"categories":5015},[151],{"categories":5017},[],{"categories":5019},[],{"categories":5021},[227],{"categories":5023},[157],{"categories":5025},[192],{"categories":5027},[],{"categories":5029},[253],{"categories":5031},[192],{"categories":5033},[253],{"categories":5035},[230],{"categories":5037},[157],{"categories":5039},[157],{"categories":5041},[],{"categories":5043},[],{"categories":5045},[160],{"categories":5047},[],{"categories":5049},[157],{"categories":5051},[428],{"categories":5053},[157],{"categories":5055},[157],{"categories":5057},[],{"categories":5059},[160],{"categories":5061},[157],{"categories":5063},[157],{"categories":5065},[],{"categories":5067},[160],{"categories":5069},[157],{"categories":5071},[192],{"categories":5073},[157],{"categories":5075},[253],{"categories":5077},[154],{"categories":5079},[157],{"categories":5081},[157],{"categories":5083},[160],{"categories":5085},[230],{"categories":5087},[160],{"categories":5089},[160],{"categories":5091},[],{"categories":5093},[],{"categories":5095},[157],{"categories":5097},[],{"categories":5099},[192],{"categories":5101},[154],{"categories":5103},[],{"categories":5105},[],{"categories":5107},[227],{"categories":5109},[151],{"categories":5111},[],{"categories":5113},[154],{"categories":5115},[253],{"categories":5117},[157],{"categories":5119},[170],{"categories":5121},[151],{"categories":5123},[230],{"categories":5125},[154],{"categories":5127},[170],{"categories":5129},[170],{"categories":5131},[],{"categories":5133},[157],{"categories":5135},[],{"categories":5137},[160],{"categories":5139},[151],{"categories":5141},[227],{"categories":5143},[157],{"categories":5145},[151],{"categories":5147},[160],{"categories":5149},[284],{"categories":5151},[157],{"categories":5153},[157],{"categories":5155},[157],{"categories":5157},[151],{"categories":5159},[230],{"categories":5161},[160],{"categories":5163},[],{"categories":5165},[157],{"categories":5167},[170],{"categories":5169},[192],{"categories":5171},[170],{"categories":5173},[157],{"categories":5175},[163],{"categories":5177},[],{"categories":5179},[227],{"categories":5181},[192],{"categories":5183},[151],{"categories":5185},[160],{"categories":5187},[157],{"categories":5189},[157],{"categories":5191},[160],{"categories":5193},[157],{"categories":5195},[157],{"categories":5197},[154],{"categories":5199},[160],{"categories":5201},[160,284],{"categories":5203},[160],{"categories":5205},[170],{"categories":5207},[157],{"categories":5209},[157],{"categories":5211},[230],{"categories":5213},[160],{"categories":5215},[253],{"categories":5217},[160],{"categories":5219},[154],{"categories":5221},[],{"categories":5223},[160],{"categories":5225},[157],{"categories":5227},[154],{"categories":5229},[],{"categories":5231},[],{"categories":5233},[170],{"categories":5235},[157],{"categories":5237},[160],{"categories":5239},[230],{"categories":5241},[253],{"categories":5243},[157],{"categories":5245},[157],{"categories":5247},[160],{"categories":5249},[],{"categories":5251},[160],{"categories":5253},[192],{"categories":5255},[160],{"categories":5257},[],{"categories":5259},[192],{"categories":5261},[170],{"categories":5263},[2543],{"categories":5265},[151],{"categories":5267},[170],{"categories":5269},[157],{"categories":5271},[160],{"categories":5273},[157],{"categories":5275},[157],{"categories":5277},[253],{"categories":5279},[170],{"categories":5281},[],{"categories":5283},[192],{"categories":5285},[157],{"categories":5287},[],{"categories":5289},[160],{"categories":5291},[157],{"categories":5293},[157],{"categories":5295},[157],{"categories":5297},[160],{"categories":5299},[157],{"categories":5301},[157],{"categories":5303},[163],{"categories":5305},[160],{"categories":5307},[157],{"categories":5309},[157],{"categories":5311},[157],{"categories":5313},[157],{"categories":5315},[157],{"categories":5317},[154],{"categories":5319},[],{"categories":5321},[163],{"categories":5323},[192],{"categories":5325},[160],{"categories":5327},[157],{"categories":5329},[170],{"categories":5331},[],{"categories":5333},[170],{"categories":5335},[170],{"categories":5337},[160],{"categories":5339},[170],{"categories":5341},[157],{"categories":5343},[157],{"categories":5345},[170],{"categories":5347},[157],{"categories":5349},[160],{"categories":5351},[192],{"categories":5353},[157],{"categories":5355},[157],{"categories":5357},[157],{"categories":5359},[154],{"categories":5361},[157],{"categories":5363},[160],{"categories":5365},[227],{"categories":5367},[],{"categories":5369},[157],{"categories":5371},[230],{"categories":5373},[160],{"categories":5375},[157],{"categories":5377},[],{"categories":5379},[157],{"categories":5381},[157],{"categories":5383},[192],{"categories":5385},[157],{"categories":5387},[157],{"categories":5389},[160],{"categories":5391},[253],{"categories":5393},[],{"categories":5395},[],{"categories":5397},[170],{"categories":5399},[192],{"categories":5401},[170],{"categories":5403},[192],{"categories":5405},[157],{"categories":5407},[253],{"categories":5409},[157],{"categories":5411},[151],{"categories":5413},[160],{"categories":5415},[157],{"categories":5417},[160],{"categories":5419},[160],{"categories":5421},[157],{"categories":5423},[154],{"categories":5425},[],{"categories":5427},[230],{"categories":5429},[157],{"categories":5431},[],{"categories":5433},[192],{"categories":5435},[157],{"categories":5437},[230],{"categories":5439},[157],{"categories":5441},[170],{"categories":5443},[170],{"categories":5445},[170],{"categories":5447},[160],{"categories":5449},[160],{"categories":5451},[160],{"categories":5453},[157],{"categories":5455},[227],{"categories":5457},[230],{"categories":5459},[230],{"categories":5461},[],{"categories":5463},[192],{"categories":5465},[157],{"categories":5467},[157],{"categories":5469},[170],{"categories":5471},[],{"categories":5473},[192],{"categories":5475},[192],{"categories":5477},[192],{"categories":5479},[],{"categories":5481},[160],{"categories":5483},[157],{"categories":5485},[],{"categories":5487},[151],{"categories":5489},[154],{"categories":5491},[],{"categories":5493},[157],{"categories":5495},[157],{"categories":5497},[],{"categories":5499},[170],{"categories":5501},[],{"categories":5503},[],{"categories":5505},[],{"categories":5507},[],{"categories":5509},[157],{"categories":5511},[192],{"categories":5513},[],{"categories":5515},[],{"categories":5517},[157],{"categories":5519},[157],{"categories":5521},[157],{"categories":5523},[230],{"categories":5525},[157],{"categories":5527},[230],{"categories":5529},[],{"categories":5531},[230],{"categories":5533},[230],{"categories":5535},[284],{"categories":5537},[160],{"categories":5539},[170],{"categories":5541},[],{"categories":5543},[],{"categories":5545},[230],{"categories":5547},[170],{"categories":5549},[170],{"categories":5551},[170],{"categories":5553},[],{"categories":5555},[151],{"categories":5557},[170],{"categories":5559},[170],{"categories":5561},[151],{"categories":5563},[170],{"categories":5565},[154],{"categories":5567},[170],{"categories":5569},[170],{"categories":5571},[170],{"categories":5573},[230],{"categories":5575},[192],{"categories":5577},[192],{"categories":5579},[157],{"categories":5581},[170],{"categories":5583},[230],{"categories":5585},[284],{"categories":5587},[230],{"categories":5589},[230],{"categories":5591},[230],{"categories":5593},[],{"categories":5595},[154],{"categories":5597},[],{"categories":5599},[284],{"categories":5601},[170],{"categories":5603},[170],{"categories":5605},[170],{"categories":5607},[160],{"categories":5609},[192,154],{"categories":5611},[230],{"categories":5613},[],{"categories":5615},[],{"categories":5617},[230],{"categories":5619},[],{"categories":5621},[230],{"categories":5623},[192],{"categories":5625},[160],{"categories":5627},[],{"categories":5629},[170],{"categories":5631},[157],{"categories":5633},[227],{"categories":5635},[],{"categories":5637},[157],{"categories":5639},[],{"categories":5641},[192],{"categories":5643},[151],{"categories":5645},[230],{"categories":5647},[],{"categories":5649},[170],{"categories":5651},[192],[5653,5802,5887,5988],{"id":5654,"title":5655,"ai":5656,"body":5661,"categories":5777,"created_at":106,"date_modified":106,"description":97,"extension":107,"faq":106,"featured":108,"kicker_label":106,"meta":5778,"navigation":126,"path":5791,"published_at":128,"question":106,"scraped_at":5792,"seo":5793,"sitemap":5794,"source_id":132,"source_name":133,"source_type":134,"source_url":135,"stem":5795,"tags":5796,"thumbnail_url":143,"tldr":5798,"tweet":5799,"unknown_tags":5800,"__hash__":5801},"summaries\u002Fsummaries\u002F3dbb1a3ba51ae1f2-building-ai-powered-search-with-google-cloud-spann-summary.md","Building AI-Powered Search with Google Cloud Spanner",{"provider":7,"model":8,"input_tokens":5657,"output_tokens":5658,"processing_time_ms":5659,"cost_usd":5660},9152,1113,5588,0.0039575,{"type":14,"value":5662,"toc":5769},[5663,5665,5668,5671,5675,5678,5695,5699,5702,5706,5709,5713,5745,5749],[17,5664,20],{"id":19},[22,5666,5667],{},"Traditionally, developers maintained separate systems for transactional data (SQL), full-text search (e.g., Elasticsearch, Algolia), and vector storage. This architecture introduces significant operational overhead, including data duplication, complex ETL pipelines, and, most critically, data staleness. Google Cloud Spanner addresses this by integrating full-text, vector, and graph search directly into the relational database layer.",[22,5669,5670],{},"By keeping search indexes within the primary database, developers achieve read-after-write consistency. When an AI agent or user updates a record, the search and vector indexes are updated transactionally, ensuring that subsequent queries reflect the latest state of the data without lag.",[17,5672,5674],{"id":5673},"hybrid-search-combining-text-and-context","Hybrid Search: Combining Text and Context",[22,5676,5677],{},"Spanner provides three primary search modalities that can be fused for superior results:",[63,5679,5680,5685,5690],{},[36,5681,5682,5684],{},[39,5683,41],{}," Uses tokenization and n-grams to handle keyword matching, including fuzzy search for spelling variants and synonyms.",[36,5686,5687,5689],{},[39,5688,47],{}," Uses embeddings to understand the semantic meaning of data, allowing for context-aware retrieval that goes beyond exact keyword matches.",[36,5691,5692,5694],{},[39,5693,53],{}," Employs Reciprocal Rank Fusion (RRF) to merge results from both text and vector indexes, providing the \"best of both worlds\" by balancing precise keyword relevance with broad semantic understanding.",[17,5696,5698],{"id":5697},"intelligent-query-expansion","Intelligent Query Expansion",[22,5700,5701],{},"Beyond basic fuzzy matching, Spanner incorporates \"Enhanced Search,\" a feature leveraging Google’s proprietary query expansion technology. When enabled, the database automatically rewrites user queries to include synonyms, related terms, and semantic variations. For example, a search for \"hair dye\" is expanded to include terms like \"coloring\" or \"dyeing,\" significantly increasing recall without requiring manual prompt engineering or complex application-side logic.",[17,5703,5705],{"id":5704},"scaling-for-ai-native-applications","Scaling for AI-Native Applications",[22,5707,5708],{},"Attio, an AI-native CRM, serves as a case study for this architecture. After outgrowing PostgreSQL, they migrated to Spanner to handle massive, multi-tenant workloads. By moving from an external search provider (Algolia) to Spanner’s native search, they eliminated materialization delays and achieved significant cost savings—projecting over $500,000 in savings compared to their previous external search infrastructure. Their \"Ask Attio\" interface now handles over a billion documents and 50,000 reads per second, demonstrating that Spanner’s scale-out capabilities are sufficient for high-concurrency agentic workloads.",[17,5710,5712],{"id":5711},"key-takeaways","Key Takeaways",[63,5714,5715,5721,5727,5733,5739],{},[36,5716,5717,5720],{},[39,5718,5719],{},"Eliminate ETL:"," By keeping search indexes inside your primary database, you remove the latency and complexity of syncing data to external search engines.",[36,5722,5723,5726],{},[39,5724,5725],{},"Leverage Transactional Consistency:"," Use Spanner's point-in-time reads and read-after-write consistency to ensure AI agents always operate on the most current data.",[36,5728,5729,5732],{},[39,5730,5731],{},"Use Hybrid Fusion:"," Always combine full-text and vector search via Reciprocal Rank Fusion (RRF) to capture both specific keyword matches and broad semantic intent.",[36,5734,5735,5738],{},[39,5736,5737],{},"Optimize with Query Hints:"," For complex multi-tenant workloads, use Spanner’s query hints to explicitly define join orders and parallelism, bypassing the limitations of standard query optimizers.",[36,5740,5741,5744],{},[39,5742,5743],{},"Enable Enhanced Search:"," Use built-in query expansion to handle multilingual data and synonym matching automatically, mirroring the intelligence of Google Search within your own applications.",[17,5746,5748],{"id":5747},"notable-quotes","Notable Quotes",[63,5750,5751,5759,5766],{},[36,5752,5753,5754,5758],{},"\"The beautiful thing about ",[5755,5756,5757],"span",{},"Spanner"," is that as a developer you can provide it with a query plan... your developers are able to premeditate the query plan that is going to best fit your workload.\" — Alexander Christie, on the control Spanner provides for complex, multi-tenant query performance.",[36,5760,5761,5762,5765],{},"\"The basic model of ",[5755,5763,5764],{},"external search"," is you send them a push request and they promise that they'll index that for search at some point between now and the end of the universe.\" — Alexander Christie, highlighting the latency issues inherent in traditional ETL-based search pipelines.",[36,5767,5768],{},"\"Spanner search is just Spanner. So it benefits from all of the availability and uptime... as well as some of Spanner's cooler, more interesting features like point-in-time reads.\" — Alexander Christie, on the operational benefits of a unified data platform.",{"title":97,"searchDepth":98,"depth":98,"links":5770},[5771,5772,5773,5774,5775,5776],{"id":19,"depth":98,"text":20},{"id":5673,"depth":98,"text":5674},{"id":5697,"depth":98,"text":5698},{"id":5704,"depth":98,"text":5705},{"id":5711,"depth":98,"text":5712},{"id":5747,"depth":98,"text":5748},[157],{"content_references":5779,"triage":5789},[5780,5782,5785],{"type":112,"title":113,"url":114,"context":5781},"recommended",{"type":112,"title":5783,"url":5784,"context":115},"Algolia","https:\u002F\u002Fwww.algolia.com\u002F",{"type":112,"title":5786,"url":5787,"context":5788},"Attio","https:\u002F\u002Fattio.com\u002F","reviewed",{"relevance":122,"novelty":123,"quality":123,"actionability":123,"composite":124,"reasoning":5790},"Category: AI & LLMs. The article discusses the integration of AI capabilities into Google Cloud Spanner, addressing a specific pain point of managing separate systems for search and transactional data. It provides actionable insights on how to implement hybrid search architectures, which is directly relevant for developers building AI-powered products.","\u002Fsummaries\u002F3dbb1a3ba51ae1f2-building-ai-powered-search-with-google-cloud-spann-summary","2026-06-26 12:57:21",{"title":5655,"description":97},{"loc":5791},"summaries\u002F3dbb1a3ba51ae1f2-building-ai-powered-search-with-google-cloud-spann-summary",[5797,140,139,142],"ai-llms","Google Cloud Spanner enables hybrid search by combining full-text, vector, and graph capabilities within a single, transactionally consistent database, eliminating the need for complex ETL pipelines and external search indexes.","This session provides a technical overview of how to implement hybrid search—combining full-text and vector search—directly within [Google Cloud Spanner](https:\u002F\u002Fcloud.google.com\u002Fspanner). The speakers explain how this architecture eliminates the need for external search indexing and ETL pipelines, featuring a case study from [Attio](https:\u002F\u002Fattio.com) on using the platform for CRM data.",[5797,140,139,142],"KEQz3J3KllDcHh09Yf_pLO-Mk1aIcxAgXd8ldRAZDOs",{"id":5803,"title":5804,"ai":5805,"body":5810,"categories":5864,"created_at":106,"date_modified":106,"description":97,"extension":107,"faq":106,"featured":108,"kicker_label":106,"meta":5865,"navigation":126,"path":5871,"published_at":5872,"question":106,"scraped_at":5872,"seo":5873,"sitemap":5874,"source_id":5875,"source_name":5876,"source_type":5877,"source_url":5878,"stem":5879,"tags":5880,"thumbnail_url":106,"tldr":5884,"tweet":106,"unknown_tags":5885,"__hash__":5886},"summaries\u002Fsummaries\u002F914cb64673f5c1e7-dyslexlens-analyzing-dyslexic-ai-user-experiences-summary.md","DysLexLens: Analyzing Dyslexic AI User Experiences via LLMs",{"provider":7,"model":8,"input_tokens":5806,"output_tokens":5807,"processing_time_ms":5808,"cost_usd":5809},6365,411,2306,0.00220775,{"type":14,"value":5811,"toc":5860},[5812,5816,5819,5822,5836,5840,5843,5857],[17,5813,5815],{"id":5814},"architecture-for-low-resource-data-analysis","Architecture for Low-Resource Data Analysis",[22,5817,5818],{},"DysLexLens addresses the challenge of extracting meaningful insights from sparse, noisy social media data regarding the lived experiences of dyslexic learners using AI. The framework operates as an end-to-end pipeline designed to transform unstructured forum posts into verifiable, knowledge-grounded insights.",[22,5820,5821],{},"Key components include:",[63,5823,5824,5830],{},[36,5825,5826,5829],{},[39,5827,5828],{},"Dictionary-Driven Filtering:"," To combat noise in low-resource contexts, the system uses a specialized dictionary to filter Reddit posts, ensuring the corpus remains focused on the intersection of dyslexia and AI.",[36,5831,5832,5835],{},[39,5833,5834],{},"KG-Based Reasoning:"," The framework integrates LLM-assisted semantic analysis with Knowledge Graphs (KG) to perform structured query reasoning, allowing for more reliable pattern discovery than standard retrieval alone.",[17,5837,5839],{"id":5838},"verification-and-evaluation-rigor","Verification and Evaluation Rigor",[22,5841,5842],{},"Because the framework targets sensitive user experiences, it prioritizes evidence alignment and hallucination mitigation. It employs a dual-layered evaluation approach:",[63,5844,5845,5851],{},[36,5846,5847,5850],{},[39,5848,5849],{},"Quantitative Metrics:"," The system utilizes RAGAS and Query Robustness metrics to benchmark the performance of LLM-generated responses against the source data.",[36,5852,5853,5856],{},[39,5854,5855],{},"Qualitative Validation:"," The authors provide structured guidelines for human-grounded assessment, specifically focusing on whether the generated insights are accurately supported by the original forum evidence.",[22,5858,5859],{},"The authors demonstrated the framework's efficacy using 30 specific queries on dyslexia-related Reddit data, providing a reproducible baseline for researchers looking to apply similar architectures to other low-resource community datasets.",{"title":97,"searchDepth":98,"depth":98,"links":5861},[5862,5863],{"id":5814,"depth":98,"text":5815},{"id":5838,"depth":98,"text":5839},[105],{"content_references":5866,"triage":5867},[],{"relevance":123,"novelty":5868,"quality":123,"actionability":5868,"composite":5869,"reasoning":5870},3,3.6,"Category: RAG & Retrieval. The article presents a framework for extracting insights from noisy data, which aligns with the audience's interest in retrieval and evaluation methods. It introduces a dual-layered evaluation approach that could inform engineers about effective evaluation strategies, though it lacks detailed actionable steps for implementation.","\u002Fsummaries\u002F914cb64673f5c1e7-dyslexlens-analyzing-dyslexic-ai-user-experiences-summary","2026-06-29 14:33:22",{"title":5804,"description":97},{"loc":5871},"914cb64673f5c1e7","arXiv cs.AI","article","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.27619","summaries\u002F914cb64673f5c1e7-dyslexlens-analyzing-dyslexic-ai-user-experiences-summary",[138,5881,5882,5883],"llm","evals","knowledge-graph","DysLexLens is an end-to-end framework that extracts, structures, and validates insights from noisy online forum data to understand how dyslexic learners interact with AI tools.",[5883],"wo7adXhy2y-tsym6j-v0Nje9OmCs3aNiac1LgoU3nEY",{"id":5888,"title":5889,"ai":5890,"body":5895,"categories":5965,"created_at":106,"date_modified":106,"description":97,"extension":107,"faq":106,"featured":108,"kicker_label":106,"meta":5966,"navigation":126,"path":5970,"published_at":5971,"question":106,"scraped_at":5972,"seo":5973,"sitemap":5974,"source_id":5975,"source_name":5976,"source_type":134,"source_url":5977,"stem":5978,"tags":5979,"thumbnail_url":5983,"tldr":5984,"tweet":5985,"unknown_tags":5986,"__hash__":5987},"summaries\u002Fsummaries\u002F0a9c426cca4adb44-cross-document-ai-for-predictive-financial-complia-summary.md","Cross-Document AI for Predictive Financial Compliance",{"provider":7,"model":8,"input_tokens":5891,"output_tokens":5892,"processing_time_ms":5893,"cost_usd":5894},6248,538,2952,0.002369,{"type":14,"value":5896,"toc":5960},[5897,5901,5909,5913,5916,5936,5940,5943,5957],[17,5898,5900],{"id":5899},"the-limitation-of-document-level-compliance","The Limitation of Document-Level Compliance",[22,5902,5903,5904,5908],{},"Traditional financial compliance systems rely on rule-based validation of individual documents (e.g., checking a single invoice against procurement policy). This approach fails to detect sophisticated fraud because modern illicit activity is often hidden in the inconsistencies ",[5905,5906,5907],"em",{},"between"," documents—such as discrepancies across payroll, tax filings, and procurement records. When each document passes its isolated validation, the broader, interconnected fraud pattern remains invisible.",[17,5910,5912],{"id":5911},"a-three-layered-intelligence-framework","A Three-Layered Intelligence Framework",[22,5914,5915],{},"To solve this, the proposed architecture shifts from reactive validation to proactive, cross-document intelligence using three core components:",[63,5917,5918,5924,5930],{},[36,5919,5920,5923],{},[39,5921,5922],{},"Graph-Based Entity Correlation:"," This engine maps relationships between employees, vendors, accounts, and regulatory files. By creating a unified network of enterprise activity, it reveals structural anomalies that isolated document analysis cannot see.",[36,5925,5926,5929],{},[39,5927,5928],{},"Adaptive Probabilistic Risk Modeling:"," Instead of static rules, this model uses multiple indicators—such as anomaly strength, source reliability, and historical patterns—to assign a confidence-based risk score. The system continuously learns from audit outcomes, refining its scoring to prioritize high-risk cases.",[36,5931,5932,5935],{},[39,5933,5934],{},"Cross-Jurisdictional Normalization:"," This layer standardizes currencies, tax structures, and reporting standards across different regions. It ensures that risk assessment remains consistent regardless of where the transaction originated.",[17,5937,5939],{"id":5938},"operational-impact-and-performance","Operational Impact and Performance",[22,5941,5942],{},"Evaluated against 3 million records across four jurisdictions over a five-year period, the framework demonstrated significant improvements over baseline rule-based systems:",[63,5944,5945,5951],{},[36,5946,5947,5950],{},[39,5948,5949],{},"Detection Accuracy:"," Achieved 91% precision and 87% recall, resulting in an F1 score of 0.89.",[36,5952,5953,5956],{},[39,5954,5955],{},"Operational Efficiency:"," Delivered a 76% reduction in false positives and a 40% decrease in manual audit effort.",[22,5958,5959],{},"By moving to a continuous learning cycle where every completed audit feeds back into the model, organizations can transition from reactive, periodic reviews to a predictive governance model that identifies risks before they become audit findings.",{"title":97,"searchDepth":98,"depth":98,"links":5961},[5962,5963,5964],{"id":5899,"depth":98,"text":5900},{"id":5911,"depth":98,"text":5912},{"id":5938,"depth":98,"text":5939},[105],{"content_references":5967,"triage":5968},[],{"relevance":123,"novelty":5868,"quality":123,"actionability":5868,"composite":5869,"reasoning":5969},"Category: RAG & Retrieval. The article discusses a novel approach to financial compliance that leverages cross-document analysis, which is relevant to RAG strategies. It presents new insights into reducing false positives and improving detection accuracy, but lacks specific actionable steps for implementation.","\u002Fsummaries\u002F0a9c426cca4adb44-cross-document-ai-for-predictive-financial-complia-summary","2026-06-28 23:00:18","2026-06-29 14:33:10",{"title":5889,"description":97},{"loc":5970},"0a9c426cca4adb44","AI Engineer","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=Iwe_RY-fYgI","summaries\u002F0a9c426cca4adb44-cross-document-ai-for-predictive-financial-complia-summary",[138,5980,5981,5982],"agents","mlops","structured-outputs","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FIwe_RY-fYgI\u002Fhqdefault.jpg","Moving from document-level validation to cross-document graph correlation and probabilistic risk modeling reduces false positives by 76% and enables proactive fraud detection.","This is a high-level architectural overview of a multi-component framework for enterprise fraud detection. The speaker explains how to move from isolated document validation to a connected system using graph-based entity correlation, probabilistic risk modeling, and cross-jurisdictional data normalization.",[],"oFcmSl8O2WV8lGR3CoYxPT1EGTaP7HkKrD3x9IVhdb4",{"id":5989,"title":5990,"ai":5991,"body":5997,"categories":6028,"created_at":106,"date_modified":106,"description":97,"extension":107,"faq":106,"featured":108,"kicker_label":106,"meta":6029,"navigation":126,"path":6033,"published_at":6034,"question":106,"scraped_at":6035,"seo":6036,"sitemap":6037,"source_id":6038,"source_name":6039,"source_type":5877,"source_url":6040,"stem":6041,"tags":6042,"thumbnail_url":106,"tldr":6043,"tweet":106,"unknown_tags":6044,"__hash__":6045},"summaries\u002Fsummaries\u002Fb395b6790f7cac0d-graphrag-and-vectorless-rag-fix-vector-rag-s-silen-summary.md","GraphRAG and Vectorless RAG Fix Vector RAG's Silent Failures",{"provider":7,"model":5992,"input_tokens":5993,"output_tokens":5994,"processing_time_ms":5995,"cost_usd":5996},"x-ai\u002Fgrok-4.1-fast",3854,1559,13996,0.00104345,{"type":14,"value":5998,"toc":6023},[5999,6003,6006,6010,6013,6017,6020],[17,6000,6002],{"id":6001},"vector-rags-structural-blind-spot","Vector RAG's Structural Blind Spot",[22,6004,6005],{},"Traditional vector RAG retrieves semantically similar document chunks, but these are often close yet wrong, leading the LLM to generate confident, plausible answers that mislead users. No errors trigger, no logs flag issues—failures surface only via delayed user complaints weeks later. Tweaking parameters like embedding models or top-k doesn't fix this; it's baked into relying solely on vector similarity, which ignores entity relationships and document structure.",[17,6007,6009],{"id":6008},"graphrag-leverage-knowledge-graphs-for-relational-context","GraphRAG: Leverage Knowledge Graphs for Relational Context",[22,6011,6012],{},"GraphRAG overlays a knowledge graph on your data to explicitly map relationships between entities (e.g., people, places, concepts). Retrieval pulls connected subgraphs, not just isolated chunks, enabling the LLM to reason over interconnected facts. Use this when your domain has complex entities—like legal docs or enterprise knowledge bases—where proximity alone fails but relational paths reveal truth. Trade-off: Higher upfront indexing cost for graph construction, but gains precision on global queries.",[17,6014,6016],{"id":6015},"vectorless-rag-llm-driven-reasoning-over-raw-structure","Vectorless RAG: LLM-Driven Reasoning Over Raw Structure",[22,6018,6019],{},"Vectorless RAG ditches vector databases entirely, feeding the LLM hierarchical document outlines or tree structures (e.g., via markdown headers, XML tags). The model navigates and summarizes sections dynamically without embeddings. Ideal for hierarchical content like reports or codebases, where structure guides relevance better than semantics. Trade-off: Slower at scale without vector speedups, but avoids embedding drift and shines on precise, local queries.",[22,6021,6022],{},"Neither replaces vector RAG as a drop-in—pick GraphRAG for entity-heavy data, Vectorless for structured docs. Both eliminate the 'smoothly wrong' failure by addressing what vectors miss: relationships or hierarchy.",{"title":97,"searchDepth":98,"depth":98,"links":6024},[6025,6026,6027],{"id":6001,"depth":98,"text":6002},{"id":6008,"depth":98,"text":6009},{"id":6015,"depth":98,"text":6016},[],{"content_references":6030,"triage":6031},[],{"relevance":122,"novelty":123,"quality":123,"actionability":123,"composite":124,"reasoning":6032},"Category: AI & LLMs. The article provides a deep dive into advanced context engineering techniques for AI models, specifically addressing the limitations of traditional vector RAG and presenting innovative alternatives like GraphRAG and Vectorless RAG. It offers actionable insights on when to use each method based on specific data types, making it highly relevant for product builders looking to implement AI effectively.","\u002Fsummaries\u002Fb395b6790f7cac0d-graphrag-and-vectorless-rag-fix-vector-rag-s-silen-summary","2026-05-03 07:34:05","2026-05-03 17:00:59",{"title":5990,"description":97},{"loc":6033},"b395b6790f7cac0d","Towards AI","https:\u002F\u002Fpub.towardsai.net\u002Fgraphrag-vs-vectorless-rag-vs-vector-rag-a-2026-guide-to-advanced-context-engineering-e8e9264cab38?source=rss----98111c9905da---4","summaries\u002Fb395b6790f7cac0d-graphrag-and-vectorless-rag-fix-vector-rag-s-silen-summary",[5881,138],"Vector RAG structurally fails by confidently hallucinating on semantically similar but incorrect chunks with no errors logged. GraphRAG maps entity relationships via graphs; Vectorless RAG skips vectors for LLM reasoning over document structure—each excels where the other can't.",[138],"SRq2FDVakmAyBlM0jCkkgfsMc3ogQZXFSpDxvTIhVKA"]