[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-aa3ba81f7f87dc76-scaling-coding-agents-lessons-from-building-langfu-summary":3,"summaries-facets-categories":178,"summary-related-aa3ba81f7f87dc76-scaling-coding-agents-lessons-from-building-langfu-summary":4057},{"id":4,"title":5,"ai":6,"body":13,"categories":138,"created_at":140,"date_modified":140,"description":130,"extension":141,"faq":140,"featured":142,"kicker_label":140,"meta":143,"navigation":157,"path":158,"published_at":159,"question":140,"scraped_at":160,"seo":161,"sitemap":162,"source_id":163,"source_name":164,"source_type":165,"source_url":166,"stem":167,"tags":168,"thumbnail_url":173,"tldr":174,"tweet":175,"unknown_tags":176,"__hash__":177},"summaries\u002Fsummaries\u002Faa3ba81f7f87dc76-scaling-coding-agents-lessons-from-building-langfu-summary.md","Scaling Coding Agents: Lessons from Building Langfuse Skills",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",8667,1155,7821,0.00389925,{"type":14,"value":15,"toc":129},"minimark",[16,21,25,29,32,61,65,68,75,79,111,115],[17,18,20],"h2",{"id":19},"the-problem-stale-context-and-non-optimal-agent-behavior","The Problem: Stale Context and Non-Optimal Agent Behavior",[22,23,24],"p",{},"When using coding agents like Claude Code to integrate infrastructure tools like Langfuse, developers often face a \"stale context\" trap. Agents rely on pre-training data, which leads to hallucinations regarding API interfaces that have evolved. Furthermore, agents often prioritize speed over correctness, implementing instrumentation incorrectly, realizing the failure, and then only fetching documentation as a secondary correction step. This creates inefficient, multi-turn workflows that lack visibility into the agent's actual decision-making process.",[17,26,28],{"id":27},"building-a-reliable-skill","Building a Reliable Skill",[22,30,31],{},"To solve this, the Langfuse team developed a \"skill\"—a formalized shortcut for agents. Instead of forcing agents to crawl hundreds of pages of documentation, they implemented:",[33,34,35,43,49,55],"ul",{},[36,37,38,42],"li",{},[39,40,41],"strong",{},"Natural Language Search Endpoint:"," Rather than relying on generic web searches, the agent queries a dedicated search endpoint that returns relevant documentation chunks. This allows the team to track what problems users are actually encountering, serving as a feedback loop for documentation gaps.",[36,44,45,48],{},[39,46,47],{},"Agent Sitemap:"," Exposing a sitemap helps the agent navigate the documentation structure efficiently without wasting tokens on irrelevant pages.",[36,50,51,54],{},[39,52,53],{},"Markdown-First Content Negotiation:"," Ensuring the agent requests and receives documentation in Markdown format prevents token waste and parsing errors associated with HTML.",[36,56,57,60],{},[39,58,59],{},"Reference-Based Context:"," To avoid the \"local cache\" problem where duplicated documentation becomes stale, the skill is designed to point to live references rather than embedding static content.",[17,62,64],{"id":63},"the-role-of-evaluation-and-target-functions","The Role of Evaluation and Target Functions",[22,66,67],{},"Even a basic evaluation setup—comparing the file system state before and after the agent runs—is superior to having no evaluation at all. The team used natural language checks (LLM-as-a-judge) to verify that instrumentation was correctly injected into sample repositories.",[22,69,70,71,74],{},"However, the team discovered that ",[39,72,73],{},"target functions are critical",". When they used auto-research to optimize the skill, the agent attempted to minimize the number of turns. This caused the agent to \"optimize out\" the documentation-fetching steps because it believed it already knew how the system worked. This backfired, as it removed the safety mechanism that ensures the agent uses up-to-date information. Defining the right target function—balancing speed with the necessity of verification—is the primary challenge in agentic development.",[17,76,78],{"id":77},"key-takeaways","Key Takeaways",[33,80,81,87,93,99,105],{},[36,82,83,86],{},[39,84,85],{},"Look at the traces:"," Runtime execution traces provide 80% of the insights needed to improve agent performance. Don't over-engineer evaluation until you have manually inspected what the agent is actually doing.",[36,88,89,92],{},[39,90,91],{},"Avoid static duplication:"," Do not bake documentation into the agent's prompt or skill definition. Point to live search endpoints to ensure the agent always has access to the latest API changes.",[36,94,95,98],{},[39,96,97],{},"Define target functions carefully:"," If you optimize for \"fewer turns,\" the agent will likely skip critical verification steps. Ensure your target function includes success metrics like \"correct instrumentation verified by traces.\"",[36,100,101,104],{},[39,102,103],{},"Use search as a signal:"," A search endpoint is not just for the agent; it is a telemetry tool for you. Track the queries to identify where your documentation is failing users.",[36,106,107,110],{},[39,108,109],{},"Default to interactive discovery:"," Don't assume user environment variables (like data regions). Prompt the agent to ask the user for configuration details rather than hardcoding defaults that may be incorrect for enterprise users.",[17,112,114],{"id":113},"notable-quotes","Notable Quotes",[33,116,117,120,123,126],{},[36,118,119],{},"\"The resulting trace captures two LLM calls with no visibility into what the agent actually did.\"\n(Context: Describing the failure of standard agentic instrumentation where the 'why' is lost.)",[36,121,122],{},"\"If you basically ask to minimize the number of turns, then our agent that tried to optimize the skill just took out all of the notes that we had to fetch documentation.\"\n(Context: Explaining how a poorly defined target function can lead to the agent 'optimizing' away reliability.)",[36,124,125],{},"\"Dynamic content should be referenced because there's a huge incentive for developers to just contribute a lot of context to the skill, but then it goes out of date.\"\n(Context: Warning against the common pitfall of duplicating documentation into the agent's local environment.)",[36,127,128],{},"\"We always defaulted to Europe and now we kind of like for an agent, like adding another environment variable, they don't care—it's not effort for them.\"\n(Context: Highlighting that agents can handle more complex configuration than human users, so don't simplify to the point of inaccuracy.)",{"title":130,"searchDepth":131,"depth":131,"links":132},"",2,[133,134,135,136,137],{"id":19,"depth":131,"text":20},{"id":27,"depth":131,"text":28},{"id":63,"depth":131,"text":64},{"id":77,"depth":131,"text":78},{"id":113,"depth":131,"text":114},[139],"AI & LLMs",null,"md",false,{"content_references":144,"triage":152},[145,150],{"type":146,"title":147,"url":148,"context":149},"tool","Langfuse","https:\u002F\u002Flangfuse.com","mentioned",{"type":146,"title":151,"context":149},"Claude Code",{"relevance":153,"novelty":154,"quality":154,"actionability":154,"composite":155,"reasoning":156},5,4,4.35,"Category: AI & LLMs. The article provides in-depth insights into building reliable coding agents, addressing specific pain points like stale context and optimizing agent behavior, which is crucial for developers integrating AI into their workflows. It offers actionable strategies such as implementing a natural language search endpoint and reference-based context, making it highly relevant and practical for the target audience.",true,"\u002Fsummaries\u002Faa3ba81f7f87dc76-scaling-coding-agents-lessons-from-building-langfu-summary","2026-05-20 15:00:06","2026-05-20 19:00:18",{"title":5,"description":130},{"loc":158},"aa3ba81f7f87dc76","AI Engineer","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=vNCY9kXXyDQ","summaries\u002Faa3ba81f7f87dc76-scaling-coding-agents-lessons-from-building-langfu-summary",[169,170,171,172],"llm","prompt-engineering","ai-agents","dev-productivity","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FvNCY9kXXyDQ\u002Fhqdefault.jpg","To make coding agents reliable, move away from static pre-training context toward dynamic, search-based documentation retrieval and rigorous evaluation, while carefully defining target functions to avoid optimizing away reliability.","This is a technical post-mortem on the limitations of using general-purpose coding agents for complex library integration. The speaker explains how they moved away from relying on an agent's stale pre-training data by building a custom skill that forces the agent to query live documentation and follow specific implementation patterns, rather than guessing at outdated API signatures.",[171,172],"asDj96Of6cWP3VN4JFS9kBqxp_f2G5-xPNT72fE3WXo",[179,182,185,187,190,193,195,197,199,201,203,205,208,210,212,214,216,218,220,222,224,226,228,230,232,235,238,240,242,245,247,249,252,254,256,258,260,262,264,266,268,270,272,274,277,279,281,283,285,287,289,291,293,295,297,299,301,303,305,307,309,311,313,315,317,319,321,323,325,327,329,331,333,335,337,339,341,343,345,347,349,351,353,355,357,359,361,363,365,367,369,371,373,375,377,379,381,383,385,387,389,391,393,395,397,399,401,403,405,407,409,411,413,415,417,419,421,423,425,427,429,431,433,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,465,467,469,471,473,475,477,479,481,483,485,487,489,491,493,495,497,499,501,503,505,507,509,511,513,515,517,519,521,523,525,527,529,531,533,535,537,539,541,543,545,547,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,709,711,713,715,717,719,721,723,725,727,729,731,733,735,737,739,741,743,745,747,749,751,753,755,757,759,761,763,765,767,769,771,773,775,777,779,781,783,785,787,789,791,793,795,797,799,801,803,805,807,809,811,813,815,817,819,821,823,825,827,829,831,833,835,837,839,841,843,845,847,849,851,853,855,857,859,861,863,865,867,869,871,873,875,877,879,881,883,885,887,889,891,893,895,897,899,901,903,905,907,909,911,913,915,917,919,921,923,925,927,929,931,933,935,937,939,941,943,945,947,949,951,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1199,1201,1203,1205,1207,1209,1211,1213,1215,1217,1219,1221,1223,1225,1227,1229,1231,1233,1235,1237,1239,1241,1243,1245,1247,1249,1251,1253,1255,1257,1259,1261,1263,1265,1267,1269,1271,1273,1275,1277,1279,1281,1283,1285,1287,1289,1291,1293,1295,1297,1299,1301,1303,1305,1307,1309,1311,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1431,1433,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1461,1463,1465,1467,1469,1471,1473,1475,1477,1479,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1507,1509,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1781,1783,1785,1787,1789,1791,1793,1795,1797,1799,1801,1803,1805,1807,1809,1811,1813,1815,1817,1819,1821,1823,1825,1827,1829,1831,1833,1835,1837,1839,1841,1843,1845,1847,1849,1851,1853,1855,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1925,1927,1929,1931,1933,1935,1937,1939,1941,1943,1945,1947,1949,1951,1953,1955,1957,1959,1961,1963,1965,1967,1969,1971,1973,1975,1977,1979,1981,1983,1985,1987,1989,1991,1993,1995,1997,1999,2001,2003,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2513,2515,2517,2519,2521,2523,2525,2527,2529,2531,2533,2535,2537,2539,2541,2543,2545,2547,2549,2551,2553,2555,2557,2559,2561,2563,2565,2567,2569,2571,2573,2575,2577,2579,2581,2583,2585,2587,2589,2591,2593,2595,2597,2599,2601,2603,2605,2607,2609,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2697,2699,2701,2703,2705,2707,2709,2711,2713,2715,2717,2719,2721,2723,2725,2727,2729,2731,2733,2735,2737,2739,2741,2743,2745,2747,2749,2751,2753,2755,2757,2759,2761,2763,2765,2767,2769,2771,2773,2775,2777,2779,2781,2783,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3643,3645,3647,3649,3651,3653,3655,3657,3659,3661,3663,3665,3667,3669,3671,3673,3675,3677,3679,3681,3683,3685,3687,3689,3691,3693,3695,3697,3699,3701,3703,3705,3707,3709,3711,3713,3715,3717,3719,3721,3723,3725,3727,3729,3731,3733,3735,3737,3739,3741,3743,3745,3747,3749,3751,3753,3755,3757,3759,3761,3763,3765,3767,3769,3771,3773,3775,3777,3779,3781,3783,3785,3787,3789,3791,3793,3795,3797,3799,3801,3803,3805,3807,3809,3811,3813,3815,3817,3819,3821,3823,3825,3827,3829,3831,3833,3835,3837,3839,3841,3843,3845,3847,3849,3851,3853,3855,3857,3859,3861,3863,3865,3867,3869,3871,3873,3875,3877,3879,3881,3883,3885,3887,3889,3891,3893,3895,3897,3899,3901,3903,3905,3907,3909,3911,3913,3915,3917,3919,3921,3923,3925,3927,3929,3931,3933,3935,3937,3939,3941,3943,3945,3947,3949,3951,3953,3955,3957,3959,3961,3963,3965,3967,3969,3971,3973,3975,3977,3979,3981,3983,3985,3987,3989,3991,3993,3995,3997,3999,4001,4003,4005,4007,4009,4011,4013,4015,4017,4019,4021,4023,4025,4027,4029,4031,4033,4035,4037,4039,4041,4043,4045,4047,4049,4051,4053,4055],{"categories":180},[181],"Developer Productivity",{"categories":183},[184],"Business & SaaS",{"categories":186},[139],{"categories":188},[189],"AI Automation",{"categories":191},[192],"Product Strategy",{"categories":194},[139],{"categories":196},[181],{"categories":198},[184],{"categories":200},[],{"categories":202},[139],{"categories":204},[],{"categories":206},[207],"AI News & Trends",{"categories":209},[189],{"categories":211},[189],{"categories":213},[207],{"categories":215},[189],{"categories":217},[189],{"categories":219},[139],{"categories":221},[139],{"categories":223},[139],{"categories":225},[207],{"categories":227},[139],{"categories":229},[139],{"categories":231},[],{"categories":233},[234],"Design & Frontend",{"categories":236},[237],"Data Science & Visualization",{"categories":239},[207],{"categories":241},[],{"categories":243},[244],"Software Engineering",{"categories":246},[139],{"categories":248},[189],{"categories":250},[251],"Marketing & Growth",{"categories":253},[234],{"categories":255},[139],{"categories":257},[189],{"categories":259},[],{"categories":261},[],{"categories":263},[234],{"categories":265},[189],{"categories":267},[181],{"categories":269},[244],{"categories":271},[234],{"categories":273},[139],{"categories":275},[276],"DevOps & Cloud",{"categories":278},[189],{"categories":280},[207],{"categories":282},[],{"categories":284},[],{"categories":286},[189],{"categories":288},[244],{"categories":290},[],{"categories":292},[184],{"categories":294},[],{"categories":296},[],{"categories":298},[189],{"categories":300},[139],{"categories":302},[189],{"categories":304},[139],{"categories":306},[139],{"categories":308},[],{"categories":310},[244],{"categories":312},[],{"categories":314},[],{"categories":316},[244],{"categories":318},[],{"categories":320},[244],{"categories":322},[139],{"categories":324},[139],{"categories":326},[251],{"categories":328},[234],{"categories":330},[234],{"categories":332},[139],{"categories":334},[189],{"categories":336},[244],{"categories":338},[139],{"categories":340},[139],{"categories":342},[189],{"categories":344},[189],{"categories":346},[237],{"categories":348},[207],{"categories":350},[189],{"categories":352},[251],{"categories":354},[189],{"categories":356},[192],{"categories":358},[244],{"categories":360},[],{"categories":362},[189],{"categories":364},[],{"categories":366},[189],{"categories":368},[244],{"categories":370},[276],{"categories":372},[234],{"categories":374},[139],{"categories":376},[],{"categories":378},[],{"categories":380},[189],{"categories":382},[],{"categories":384},[139],{"categories":386},[],{"categories":388},[181],{"categories":390},[244],{"categories":392},[184],{"categories":394},[139],{"categories":396},[207],{"categories":398},[139],{"categories":400},[],{"categories":402},[139],{"categories":404},[],{"categories":406},[244],{"categories":408},[237],{"categories":410},[],{"categories":412},[139],{"categories":414},[234],{"categories":416},[],{"categories":418},[234],{"categories":420},[189],{"categories":422},[],{"categories":424},[139],{"categories":426},[189],{"categories":428},[207],{"categories":430},[184],{"categories":432},[139],{"categories":434},[],{"categories":436},[189],{"categories":438},[139],{"categories":440},[192],{"categories":442},[],{"categories":444},[139],{"categories":446},[189],{"categories":448},[189],{"categories":450},[],{"categories":452},[237],{"categories":454},[139],{"categories":456},[],{"categories":458},[181],{"categories":460},[184],{"categories":462},[139],{"categories":464},[189],{"categories":466},[244],{"categories":468},[139],{"categories":470},[],{"categories":472},[],{"categories":474},[139],{"categories":476},[139],{"categories":478},[],{"categories":480},[234],{"categories":482},[],{"categories":484},[139],{"categories":486},[],{"categories":488},[189],{"categories":490},[139],{"categories":492},[234],{"categories":494},[],{"categories":496},[139],{"categories":498},[139],{"categories":500},[184],{"categories":502},[189],{"categories":504},[139],{"categories":506},[234],{"categories":508},[189],{"categories":510},[],{"categories":512},[],{"categories":514},[207],{"categories":516},[],{"categories":518},[139],{"categories":520},[184,251],{"categories":522},[],{"categories":524},[139],{"categories":526},[189],{"categories":528},[],{"categories":530},[],{"categories":532},[139],{"categories":534},[],{"categories":536},[139],{"categories":538},[276],{"categories":540},[],{"categories":542},[207],{"categories":544},[234],{"categories":546},[],{"categories":548},[207],{"categories":550},[207],{"categories":552},[139],{"categories":554},[251],{"categories":556},[],{"categories":558},[184],{"categories":560},[189],{"categories":562},[],{"categories":564},[139,276],{"categories":566},[139],{"categories":568},[139],{"categories":570},[139],{"categories":572},[189],{"categories":574},[139,244],{"categories":576},[237],{"categories":578},[139],{"categories":580},[251],{"categories":582},[189],{"categories":584},[189],{"categories":586},[],{"categories":588},[189],{"categories":590},[139],{"categories":592},[139,184],{"categories":594},[],{"categories":596},[234],{"categories":598},[234],{"categories":600},[],{"categories":602},[],{"categories":604},[207],{"categories":606},[],{"categories":608},[181],{"categories":610},[244],{"categories":612},[139],{"categories":614},[234],{"categories":616},[189],{"categories":618},[244],{"categories":620},[207],{"categories":622},[234],{"categories":624},[],{"categories":626},[139],{"categories":628},[139],{"categories":630},[139],{"categories":632},[139],{"categories":634},[207],{"categories":636},[181],{"categories":638},[139],{"categories":640},[189],{"categories":642},[276],{"categories":644},[234],{"categories":646},[189],{"categories":648},[],{"categories":650},[],{"categories":652},[234],{"categories":654},[207],{"categories":656},[237],{"categories":658},[],{"categories":660},[139],{"categories":662},[139],{"categories":664},[184],{"categories":666},[139],{"categories":668},[139],{"categories":670},[207],{"categories":672},[],{"categories":674},[189],{"categories":676},[244],{"categories":678},[],{"categories":680},[139],{"categories":682},[139],{"categories":684},[189],{"categories":686},[],{"categories":688},[],{"categories":690},[139],{"categories":692},[],{"categories":694},[184],{"categories":696},[189],{"categories":698},[189],{"categories":700},[],{"categories":702},[181],{"categories":704},[139],{"categories":706},[184],{"categories":708},[207],{"categories":710},[181],{"categories":712},[],{"categories":714},[],{"categories":716},[],{"categories":718},[207],{"categories":720},[207],{"categories":722},[],{"categories":724},[],{"categories":726},[184],{"categories":728},[],{"categories":730},[],{"categories":732},[181],{"categories":734},[],{"categories":736},[251],{"categories":738},[189],{"categories":740},[184],{"categories":742},[189],{"categories":744},[244],{"categories":746},[],{"categories":748},[192],{"categories":750},[234],{"categories":752},[244],{"categories":754},[139],{"categories":756},[189],{"categories":758},[184],{"categories":760},[139],{"categories":762},[],{"categories":764},[],{"categories":766},[244],{"categories":768},[237],{"categories":770},[192],{"categories":772},[189],{"categories":774},[139],{"categories":776},[],{"categories":778},[276],{"categories":780},[],{"categories":782},[189],{"categories":784},[],{"categories":786},[181],{"categories":788},[],{"categories":790},[139],{"categories":792},[139],{"categories":794},[234],{"categories":796},[251],{"categories":798},[189],{"categories":800},[],{"categories":802},[181],{"categories":804},[],{"categories":806},[207],{"categories":808},[139,276],{"categories":810},[139],{"categories":812},[207],{"categories":814},[139],{"categories":816},[184],{"categories":818},[139],{"categories":820},[],{"categories":822},[139],{"categories":824},[184],{"categories":826},[],{"categories":828},[244],{"categories":830},[234],{"categories":832},[207],{"categories":834},[237],{"categories":836},[181],{"categories":838},[139],{"categories":840},[189],{"categories":842},[244],{"categories":844},[],{"categories":846},[],{"categories":848},[192],{"categories":850},[],{"categories":852},[139],{"categories":854},[],{"categories":856},[234],{"categories":858},[244],{"categories":860},[234],{"categories":862},[139],{"categories":864},[234],{"categories":866},[],{"categories":868},[],{"categories":870},[207],{"categories":872},[189],{"categories":874},[139],{"categories":876},[139],{"categories":878},[139],{"categories":880},[184],{"categories":882},[139],{"categories":884},[],{"categories":886},[244],{"categories":888},[244],{"categories":890},[184],{"categories":892},[],{"categories":894},[139],{"categories":896},[139],{"categories":898},[184],{"categories":900},[207],{"categories":902},[251],{"categories":904},[139],{"categories":906},[189],{"categories":908},[],{"categories":910},[234],{"categories":912},[],{"categories":914},[139],{"categories":916},[139],{"categories":918},[],{"categories":920},[184],{"categories":922},[189],{"categories":924},[],{"categories":926},[276],{"categories":928},[237],{"categories":930},[244],{"categories":932},[251],{"categories":934},[139],{"categories":936},[244],{"categories":938},[189],{"categories":940},[],{"categories":942},[],{"categories":944},[189],{"categories":946},[181],{"categories":948},[189],{"categories":950},[192],{"categories":952},[184],{"categories":954},[],{"categories":956},[139],{"categories":958},[192],{"categories":960},[139],{"categories":962},[139],{"categories":964},[251],{"categories":966},[139],{"categories":968},[234],{"categories":970},[189],{"categories":972},[],{"categories":974},[],{"categories":976},[276],{"categories":978},[244],{"categories":980},[],{"categories":982},[189],{"categories":984},[139],{"categories":986},[234,139],{"categories":988},[181],{"categories":990},[],{"categories":992},[139],{"categories":994},[181],{"categories":996},[234],{"categories":998},[189],{"categories":1000},[244],{"categories":1002},[],{"categories":1004},[139],{"categories":1006},[],{"categories":1008},[],{"categories":1010},[139],{"categories":1012},[181],{"categories":1014},[],{"categories":1016},[189],{"categories":1018},[192],{"categories":1020},[139],{"categories":1022},[139],{"categories":1024},[139],{"categories":1026},[234],{"categories":1028},[189],{"categories":1030},[276],{"categories":1032},[234],{"categories":1034},[189],{"categories":1036},[139],{"categories":1038},[139],{"categories":1040},[139],{"categories":1042},[244],{"categories":1044},[],{"categories":1046},[207],{"categories":1048},[],{"categories":1050},[192],{"categories":1052},[189],{"categories":1054},[234],{"categories":1056},[139],{"categories":1058},[189],{"categories":1060},[244],{"categories":1062},[234],{"categories":1064},[189],{"categories":1066},[207],{"categories":1068},[],{"categories":1070},[139],{"categories":1072},[234],{"categories":1074},[139],{"categories":1076},[181],{"categories":1078},[207],{"categories":1080},[139],{"categories":1082},[251],{"categories":1084},[139],{"categories":1086},[189],{"categories":1088},[139],{"categories":1090},[189],{"categories":1092},[189],{"categories":1094},[139],{"categories":1096},[189],{"categories":1098},[234],{"categories":1100},[139],{"categories":1102},[],{"categories":1104},[],{"categories":1106},[244],{"categories":1108},[],{"categories":1110},[181],{"categories":1112},[276],{"categories":1114},[139],{"categories":1116},[],{"categories":1118},[181],{"categories":1120},[184],{"categories":1122},[251],{"categories":1124},[],{"categories":1126},[184],{"categories":1128},[],{"categories":1130},[139],{"categories":1132},[],{"categories":1134},[],{"categories":1136},[],{"categories":1138},[],{"categories":1140},[139],{"categories":1142},[189],{"categories":1144},[276],{"categories":1146},[181],{"categories":1148},[244],{"categories":1150},[139],{"categories":1152},[244],{"categories":1154},[192],{"categories":1156},[139],{"categories":1158},[251],{"categories":1160},[184],{"categories":1162},[139],{"categories":1164},[139],{"categories":1166},[139],{"categories":1168},[139,181],{"categories":1170},[244],{"categories":1172},[244],{"categories":1174},[234],{"categories":1176},[139],{"categories":1178},[],{"categories":1180},[],{"categories":1182},[],{"categories":1184},[244],{"categories":1186},[237],{"categories":1188},[207],{"categories":1190},[234],{"categories":1192},[],{"categories":1194},[139],{"categories":1196},[139],{"categories":1198},[],{"categories":1200},[189],{"categories":1202},[139],{"categories":1204},[],{"categories":1206},[189],{"categories":1208},[139],{"categories":1210},[184],{"categories":1212},[],{"categories":1214},[181],{"categories":1216},[139],{"categories":1218},[181],{"categories":1220},[139],{"categories":1222},[244],{"categories":1224},[251],{"categories":1226},[189],{"categories":1228},[139,234],{"categories":1230},[207],{"categories":1232},[139],{"categories":1234},[234],{"categories":1236},[],{"categories":1238},[244],{"categories":1240},[276],{"categories":1242},[234],{"categories":1244},[189],{"categories":1246},[],{"categories":1248},[],{"categories":1250},[],{"categories":1252},[],{"categories":1254},[244],{"categories":1256},[189],{"categories":1258},[189],{"categories":1260},[276],{"categories":1262},[139],{"categories":1264},[139],{"categories":1266},[189],{"categories":1268},[139],{"categories":1270},[139],{"categories":1272},[],{"categories":1274},[234],{"categories":1276},[],{"categories":1278},[],{"categories":1280},[189],{"categories":1282},[],{"categories":1284},[],{"categories":1286},[251],{"categories":1288},[251],{"categories":1290},[189],{"categories":1292},[244],{"categories":1294},[],{"categories":1296},[139],{"categories":1298},[139],{"categories":1300},[244],{"categories":1302},[234],{"categories":1304},[234],{"categories":1306},[189],{"categories":1308},[181],{"categories":1310},[139],{"categories":1312},[234],{"categories":1314},[234],{"categories":1316},[189],{"categories":1318},[189],{"categories":1320},[139],{"categories":1322},[],{"categories":1324},[],{"categories":1326},[139],{"categories":1328},[189],{"categories":1330},[207],{"categories":1332},[244],{"categories":1334},[139],{"categories":1336},[181],{"categories":1338},[139],{"categories":1340},[],{"categories":1342},[189],{"categories":1344},[189],{"categories":1346},[],{"categories":1348},[139],{"categories":1350},[181],{"categories":1352},[139],{"categories":1354},[181],{"categories":1356},[181],{"categories":1358},[],{"categories":1360},[],{"categories":1362},[189],{"categories":1364},[207],{"categories":1366},[189],{"categories":1368},[139],{"categories":1370},[139],{"categories":1372},[207],{"categories":1374},[237],{"categories":1376},[192],{"categories":1378},[207],{"categories":1380},[234],{"categories":1382},[],{"categories":1384},[],{"categories":1386},[207],{"categories":1388},[],{"categories":1390},[],{"categories":1392},[],{"categories":1394},[],{"categories":1396},[244],{"categories":1398},[237],{"categories":1400},[],{"categories":1402},[139],{"categories":1404},[139],{"categories":1406},[237],{"categories":1408},[244],{"categories":1410},[],{"categories":1412},[],{"categories":1414},[189],{"categories":1416},[207],{"categories":1418},[207],{"categories":1420},[189],{"categories":1422},[181],{"categories":1424},[139,276],{"categories":1426},[],{"categories":1428},[234],{"categories":1430},[181],{"categories":1432},[189],{"categories":1434},[234],{"categories":1436},[],{"categories":1438},[189],{"categories":1440},[189],{"categories":1442},[139],{"categories":1444},[251],{"categories":1446},[244],{"categories":1448},[234],{"categories":1450},[],{"categories":1452},[189],{"categories":1454},[139],{"categories":1456},[189],{"categories":1458},[189],{"categories":1460},[189],{"categories":1462},[251],{"categories":1464},[139],{"categories":1466},[189],{"categories":1468},[139],{"categories":1470},[],{"categories":1472},[251],{"categories":1474},[207],{"categories":1476},[189],{"categories":1478},[],{"categories":1480},[],{"categories":1482},[139],{"categories":1484},[189],{"categories":1486},[207],{"categories":1488},[189],{"categories":1490},[189],{"categories":1492},[],{"categories":1494},[139],{"categories":1496},[],{"categories":1498},[],{"categories":1500},[189],{"categories":1502},[],{"categories":1504},[],{"categories":1506},[237],{"categories":1508},[139],{"categories":1510},[237],{"categories":1512},[207],{"categories":1514},[139],{"categories":1516},[139],{"categories":1518},[189],{"categories":1520},[139],{"categories":1522},[],{"categories":1524},[],{"categories":1526},[276],{"categories":1528},[139],{"categories":1530},[],{"categories":1532},[],{"categories":1534},[181],{"categories":1536},[],{"categories":1538},[],{"categories":1540},[139],{"categories":1542},[],{"categories":1544},[],{"categories":1546},[244],{"categories":1548},[207],{"categories":1550},[251],{"categories":1552},[184],{"categories":1554},[139],{"categories":1556},[139],{"categories":1558},[184],{"categories":1560},[],{"categories":1562},[234],{"categories":1564},[189],{"categories":1566},[184],{"categories":1568},[139],{"categories":1570},[139],{"categories":1572},[181],{"categories":1574},[],{"categories":1576},[181],{"categories":1578},[139],{"categories":1580},[251],{"categories":1582},[189],{"categories":1584},[207],{"categories":1586},[184],{"categories":1588},[139],{"categories":1590},[139],{"categories":1592},[189],{"categories":1594},[],{"categories":1596},[139],{"categories":1598},[181],{"categories":1600},[139],{"categories":1602},[139],{"categories":1604},[],{"categories":1606},[207],{"categories":1608},[139],{"categories":1610},[],{"categories":1612},[184],{"categories":1614},[184],{"categories":1616},[139],{"categories":1618},[],{"categories":1620},[],{"categories":1622},[],{"categories":1624},[139],{"categories":1626},[207],{"categories":1628},[],{"categories":1630},[276],{"categories":1632},[139],{"categories":1634},[],{"categories":1636},[139],{"categories":1638},[139],{"categories":1640},[139],{"categories":1642},[139,276],{"categories":1644},[139],{"categories":1646},[139],{"categories":1648},[234],{"categories":1650},[189],{"categories":1652},[],{"categories":1654},[189],{"categories":1656},[189],{"categories":1658},[139],{"categories":1660},[139],{"categories":1662},[139],{"categories":1664},[181],{"categories":1666},[181],{"categories":1668},[244],{"categories":1670},[234],{"categories":1672},[189],{"categories":1674},[],{"categories":1676},[139],{"categories":1678},[207],{"categories":1680},[139],{"categories":1682},[184],{"categories":1684},[],{"categories":1686},[276],{"categories":1688},[234],{"categories":1690},[234],{"categories":1692},[189],{"categories":1694},[207],{"categories":1696},[189],{"categories":1698},[139],{"categories":1700},[],{"categories":1702},[139],{"categories":1704},[],{"categories":1706},[],{"categories":1708},[139],{"categories":1710},[139],{"categories":1712},[139],{"categories":1714},[189],{"categories":1716},[139],{"categories":1718},[139],{"categories":1720},[],{"categories":1722},[237],{"categories":1724},[189],{"categories":1726},[],{"categories":1728},[],{"categories":1730},[139],{"categories":1732},[207],{"categories":1734},[],{"categories":1736},[234],{"categories":1738},[276],{"categories":1740},[207],{"categories":1742},[244],{"categories":1744},[244],{"categories":1746},[207],{"categories":1748},[207],{"categories":1750},[276],{"categories":1752},[],{"categories":1754},[207],{"categories":1756},[139],{"categories":1758},[181],{"categories":1760},[139],{"categories":1762},[207],{"categories":1764},[],{"categories":1766},[244],{"categories":1768},[237],{"categories":1770},[139],{"categories":1772},[207],{"categories":1774},[244],{"categories":1776},[189],{"categories":1778},[207],{"categories":1780},[276],{"categories":1782},[189],{"categories":1784},[139],{"categories":1786},[139],{"categories":1788},[139],{"categories":1790},[],{"categories":1792},[184],{"categories":1794},[],{"categories":1796},[],{"categories":1798},[139],{"categories":1800},[139],{"categories":1802},[139],{"categories":1804},[139],{"categories":1806},[],{"categories":1808},[237],{"categories":1810},[181],{"categories":1812},[],{"categories":1814},[139],{"categories":1816},[139],{"categories":1818},[276],{"categories":1820},[276],{"categories":1822},[],{"categories":1824},[189],{"categories":1826},[207],{"categories":1828},[207],{"categories":1830},[139],{"categories":1832},[189],{"categories":1834},[],{"categories":1836},[234],{"categories":1838},[139],{"categories":1840},[139],{"categories":1842},[],{"categories":1844},[139],{"categories":1846},[],{"categories":1848},[244],{"categories":1850},[276],{"categories":1852},[139],{"categories":1854},[244],{"categories":1856},[184],{"categories":1858},[139],{"categories":1860},[],{"categories":1862},[189],{"categories":1864},[181],{"categories":1866},[181],{"categories":1868},[],{"categories":1870},[139],{"categories":1872},[234],{"categories":1874},[189],{"categories":1876},[],{"categories":1878},[139],{"categories":1880},[139],{"categories":1882},[189],{"categories":1884},[],{"categories":1886},[189],{"categories":1888},[244],{"categories":1890},[],{"categories":1892},[139],{"categories":1894},[],{"categories":1896},[139],{"categories":1898},[],{"categories":1900},[139],{"categories":1902},[139],{"categories":1904},[],{"categories":1906},[139],{"categories":1908},[207],{"categories":1910},[139],{"categories":1912},[139],{"categories":1914},[181],{"categories":1916},[139],{"categories":1918},[207],{"categories":1920},[189],{"categories":1922},[],{"categories":1924},[139],{"categories":1926},[234],{"categories":1928},[251],{"categories":1930},[139],{"categories":1932},[],{"categories":1934},[],{"categories":1936},[],{"categories":1938},[181],{"categories":1940},[207],{"categories":1942},[189],{"categories":1944},[139],{"categories":1946},[234],{"categories":1948},[189],{"categories":1950},[],{"categories":1952},[189],{"categories":1954},[],{"categories":1956},[139],{"categories":1958},[189],{"categories":1960},[139],{"categories":1962},[],{"categories":1964},[139],{"categories":1966},[139],{"categories":1968},[207],{"categories":1970},[234],{"categories":1972},[189],{"categories":1974},[234],{"categories":1976},[184],{"categories":1978},[],{"categories":1980},[],{"categories":1982},[139],{"categories":1984},[181],{"categories":1986},[207],{"categories":1988},[],{"categories":1990},[234],{"categories":1992},[],{"categories":1994},[244],{"categories":1996},[244],{"categories":1998},[234],{"categories":2000},[],{"categories":2002},[139],{"categories":2004},[],{"categories":2006},[251],{"categories":2008},[139],{"categories":2010},[276],{"categories":2012},[244],{"categories":2014},[],{"categories":2016},[189],{"categories":2018},[139],{"categories":2020},[181],{"categories":2022},[189],{"categories":2024},[189],{"categories":2026},[139],{"categories":2028},[],{"categories":2030},[181],{"categories":2032},[139],{"categories":2034},[184],{"categories":2036},[244],{"categories":2038},[234],{"categories":2040},[],{"categories":2042},[],{"categories":2044},[],{"categories":2046},[189],{"categories":2048},[234],{"categories":2050},[207],{"categories":2052},[139],{"categories":2054},[207],{"categories":2056},[234],{"categories":2058},[],{"categories":2060},[234],{"categories":2062},[207],{"categories":2064},[184],{"categories":2066},[244],{"categories":2068},[139],{"categories":2070},[207],{"categories":2072},[251],{"categories":2074},[],{"categories":2076},[],{"categories":2078},[237],{"categories":2080},[139,244],{"categories":2082},[207],{"categories":2084},[139],{"categories":2086},[189],{"categories":2088},[139],{"categories":2090},[189],{"categories":2092},[139],{"categories":2094},[139],{"categories":2096},[],{"categories":2098},[244],{"categories":2100},[139],{"categories":2102},[237],{"categories":2104},[189],{"categories":2106},[251],{"categories":2108},[276],{"categories":2110},[],{"categories":2112},[181],{"categories":2114},[189],{"categories":2116},[189],{"categories":2118},[244],{"categories":2120},[139],{"categories":2122},[139],{"categories":2124},[],{"categories":2126},[],{"categories":2128},[],{"categories":2130},[276],{"categories":2132},[207],{"categories":2134},[139],{"categories":2136},[139],{"categories":2138},[139],{"categories":2140},[],{"categories":2142},[237],{"categories":2144},[184],{"categories":2146},[],{"categories":2148},[189],{"categories":2150},[276],{"categories":2152},[],{"categories":2154},[234],{"categories":2156},[234],{"categories":2158},[],{"categories":2160},[244],{"categories":2162},[139],{"categories":2164},[234],{"categories":2166},[139],{"categories":2168},[],{"categories":2170},[207],{"categories":2172},[139],{"categories":2174},[139],{"categories":2176},[234],{"categories":2178},[189],{"categories":2180},[207],{"categories":2182},[],{"categories":2184},[189],{"categories":2186},[234],{"categories":2188},[139],{"categories":2190},[],{"categories":2192},[139],{"categories":2194},[139],{"categories":2196},[276],{"categories":2198},[207],{"categories":2200},[237],{"categories":2202},[237],{"categories":2204},[],{"categories":2206},[],{"categories":2208},[],{"categories":2210},[189],{"categories":2212},[244],{"categories":2214},[244],{"categories":2216},[139],{"categories":2218},[],{"categories":2220},[],{"categories":2222},[139],{"categories":2224},[],{"categories":2226},[189],{"categories":2228},[139],{"categories":2230},[],{"categories":2232},[139],{"categories":2234},[184],{"categories":2236},[139],{"categories":2238},[251],{"categories":2240},[189],{"categories":2242},[139],{"categories":2244},[139],{"categories":2246},[139],{"categories":2248},[244],{"categories":2250},[],{"categories":2252},[207],{"categories":2254},[189],{"categories":2256},[],{"categories":2258},[207],{"categories":2260},[189],{"categories":2262},[189],{"categories":2264},[],{"categories":2266},[184],{"categories":2268},[189],{"categories":2270},[],{"categories":2272},[139],{"categories":2274},[181],{"categories":2276},[207],{"categories":2278},[276],{"categories":2280},[189],{"categories":2282},[189],{"categories":2284},[181],{"categories":2286},[],{"categories":2288},[139],{"categories":2290},[],{"categories":2292},[],{"categories":2294},[234],{"categories":2296},[139,184],{"categories":2298},[139],{"categories":2300},[],{"categories":2302},[181],{"categories":2304},[237],{"categories":2306},[139],{"categories":2308},[244],{"categories":2310},[139],{"categories":2312},[189],{"categories":2314},[139],{"categories":2316},[139],{"categories":2318},[207],{"categories":2320},[189],{"categories":2322},[],{"categories":2324},[],{"categories":2326},[189],{"categories":2328},[139],{"categories":2330},[276],{"categories":2332},[],{"categories":2334},[139],{"categories":2336},[189],{"categories":2338},[],{"categories":2340},[189],{"categories":2342},[139],{"categories":2344},[251],{"categories":2346},[237],{"categories":2348},[189],{"categories":2350},[139],{"categories":2352},[276],{"categories":2354},[],{"categories":2356},[139],{"categories":2358},[251],{"categories":2360},[234],{"categories":2362},[139],{"categories":2364},[139],{"categories":2366},[],{"categories":2368},[251],{"categories":2370},[207],{"categories":2372},[139],{"categories":2374},[139],{"categories":2376},[181],{"categories":2378},[],{"categories":2380},[],{"categories":2382},[234],{"categories":2384},[139],{"categories":2386},[237],{"categories":2388},[251],{"categories":2390},[251],{"categories":2392},[207],{"categories":2394},[],{"categories":2396},[],{"categories":2398},[139],{"categories":2400},[139],{"categories":2402},[139],{"categories":2404},[],{"categories":2406},[139,244],{"categories":2408},[207],{"categories":2410},[189],{"categories":2412},[244],{"categories":2414},[139],{"categories":2416},[181],{"categories":2418},[],{"categories":2420},[],{"categories":2422},[181],{"categories":2424},[244],{"categories":2426},[251],{"categories":2428},[139],{"categories":2430},[],{"categories":2432},[234,139],{"categories":2434},[276],{"categories":2436},[181],{"categories":2438},[],{"categories":2440},[184],{"categories":2442},[184],{"categories":2444},[139],{"categories":2446},[139],{"categories":2448},[244],{"categories":2450},[189],{"categories":2452},[207],{"categories":2454},[251],{"categories":2456},[234],{"categories":2458},[139],{"categories":2460},[139],{"categories":2462},[139],{"categories":2464},[181],{"categories":2466},[139],{"categories":2468},[189],{"categories":2470},[207],{"categories":2472},[],{"categories":2474},[],{"categories":2476},[237],{"categories":2478},[244],{"categories":2480},[139],{"categories":2482},[234],{"categories":2484},[139],{"categories":2486},[237],{"categories":2488},[139],{"categories":2490},[139],{"categories":2492},[139],{"categories":2494},[189],{"categories":2496},[189],{"categories":2498},[139,184],{"categories":2500},[],{"categories":2502},[234],{"categories":2504},[],{"categories":2506},[139],{"categories":2508},[207],{"categories":2510},[181],{"categories":2512},[181],{"categories":2514},[189],{"categories":2516},[139],{"categories":2518},[139],{"categories":2520},[184],{"categories":2522},[244],{"categories":2524},[251],{"categories":2526},[139],{"categories":2528},[],{"categories":2530},[207],{"categories":2532},[139],{"categories":2534},[139],{"categories":2536},[139],{"categories":2538},[139],{"categories":2540},[207],{"categories":2542},[244],{"categories":2544},[244],{"categories":2546},[139],{"categories":2548},[139],{"categories":2550},[189],{"categories":2552},[207],{"categories":2554},[139],{"categories":2556},[234],{"categories":2558},[139],{"categories":2560},[139],{"categories":2562},[276],{"categories":2564},[139],{"categories":2566},[192],{"categories":2568},[189],{"categories":2570},[139],{"categories":2572},[207],{"categories":2574},[189],{"categories":2576},[251],{"categories":2578},[139],{"categories":2580},[],{"categories":2582},[139],{"categories":2584},[],{"categories":2586},[],{"categories":2588},[],{"categories":2590},[184],{"categories":2592},[139],{"categories":2594},[189],{"categories":2596},[207],{"categories":2598},[207],{"categories":2600},[207],{"categories":2602},[207],{"categories":2604},[],{"categories":2606},[181],{"categories":2608},[189],{"categories":2610},[207],{"categories":2612},[139],{"categories":2614},[181],{"categories":2616},[189],{"categories":2618},[139],{"categories":2620},[139,189],{"categories":2622},[189],{"categories":2624},[276],{"categories":2626},[207],{"categories":2628},[207],{"categories":2630},[189],{"categories":2632},[139],{"categories":2634},[],{"categories":2636},[207],{"categories":2638},[251],{"categories":2640},[181],{"categories":2642},[139],{"categories":2644},[139],{"categories":2646},[],{"categories":2648},[244],{"categories":2650},[],{"categories":2652},[181],{"categories":2654},[189],{"categories":2656},[207],{"categories":2658},[139],{"categories":2660},[207],{"categories":2662},[181],{"categories":2664},[207],{"categories":2666},[207],{"categories":2668},[],{"categories":2670},[184],{"categories":2672},[189],{"categories":2674},[207],{"categories":2676},[207],{"categories":2678},[207],{"categories":2680},[207],{"categories":2682},[207],{"categories":2684},[207],{"categories":2686},[207],{"categories":2688},[207],{"categories":2690},[207],{"categories":2692},[207],{"categories":2694},[237],{"categories":2696},[181],{"categories":2698},[139],{"categories":2700},[139],{"categories":2702},[],{"categories":2704},[139,181],{"categories":2706},[],{"categories":2708},[189],{"categories":2710},[207],{"categories":2712},[189],{"categories":2714},[139],{"categories":2716},[139],{"categories":2718},[139],{"categories":2720},[139],{"categories":2722},[139],{"categories":2724},[189],{"categories":2726},[184],{"categories":2728},[],{"categories":2730},[234],{"categories":2732},[207],{"categories":2734},[139],{"categories":2736},[],{"categories":2738},[],{"categories":2740},[189],{"categories":2742},[234],{"categories":2744},[139],{"categories":2746},[],{"categories":2748},[139],{"categories":2750},[],{"categories":2752},[251],{"categories":2754},[139],{"categories":2756},[],{"categories":2758},[],{"categories":2760},[207],{"categories":2762},[181],{"categories":2764},[139],{"categories":2766},[184],{"categories":2768},[139],{"categories":2770},[184],{"categories":2772},[234],{"categories":2774},[],{"categories":2776},[207],{"categories":2778},[],{"categories":2780},[234],{"categories":2782},[139],{"categories":2784},[251],{"categories":2786},[],{"categories":2788},[251],{"categories":2790},[],{"categories":2792},[],{"categories":2794},[189],{"categories":2796},[],{"categories":2798},[184],{"categories":2800},[181],{"categories":2802},[234],{"categories":2804},[244],{"categories":2806},[],{"categories":2808},[],{"categories":2810},[139],{"categories":2812},[181],{"categories":2814},[251],{"categories":2816},[],{"categories":2818},[189],{"categories":2820},[189],{"categories":2822},[207],{"categories":2824},[244],{"categories":2826},[139],{"categories":2828},[189],{"categories":2830},[139],{"categories":2832},[189],{"categories":2834},[139],{"categories":2836},[192],{"categories":2838},[207],{"categories":2840},[],{"categories":2842},[251],{"categories":2844},[],{"categories":2846},[244],{"categories":2848},[189],{"categories":2850},[],{"categories":2852},[139],{"categories":2854},[189],{"categories":2856},[184],{"categories":2858},[181],{"categories":2860},[139],{"categories":2862},[234],{"categories":2864},[244],{"categories":2866},[244],{"categories":2868},[139],{"categories":2870},[237],{"categories":2872},[139],{"categories":2874},[189],{"categories":2876},[184],{"categories":2878},[234],{"categories":2880},[189],{"categories":2882},[139],{"categories":2884},[139],{"categories":2886},[189],{"categories":2888},[207],{"categories":2890},[],{"categories":2892},[181],{"categories":2894},[139],{"categories":2896},[189],{"categories":2898},[139],{"categories":2900},[139],{"categories":2902},[],{"categories":2904},[234],{"categories":2906},[184],{"categories":2908},[207],{"categories":2910},[139],{"categories":2912},[139],{"categories":2914},[234],{"categories":2916},[139],{"categories":2918},[251],{"categories":2920},[237],{"categories":2922},[139],{"categories":2924},[207],{"categories":2926},[139],{"categories":2928},[189],{"categories":2930},[276],{"categories":2932},[139],{"categories":2934},[189],{"categories":2936},[237],{"categories":2938},[],{"categories":2940},[189],{"categories":2942},[244],{"categories":2944},[234],{"categories":2946},[139],{"categories":2948},[181],{"categories":2950},[184],{"categories":2952},[244],{"categories":2954},[139],{"categories":2956},[],{"categories":2958},[189],{"categories":2960},[189],{"categories":2962},[139],{"categories":2964},[237],{"categories":2966},[],{"categories":2968},[207],{"categories":2970},[],{"categories":2972},[207],{"categories":2974},[139],{"categories":2976},[189],{"categories":2978},[189],{"categories":2980},[189],{"categories":2982},[],{"categories":2984},[207],{"categories":2986},[],{"categories":2988},[139],{"categories":2990},[139],{"categories":2992},[],{"categories":2994},[234],{"categories":2996},[189],{"categories":2998},[251],{"categories":3000},[181],{"categories":3002},[],{"categories":3004},[139],{"categories":3006},[],{"categories":3008},[181],{"categories":3010},[207],{"categories":3012},[244],{"categories":3014},[139],{"categories":3016},[139],{"categories":3018},[139],{"categories":3020},[244],{"categories":3022},[207],{"categories":3024},[234],{"categories":3026},[139],{"categories":3028},[139],{"categories":3030},[139],{"categories":3032},[207],{"categories":3034},[139],{"categories":3036},[207],{"categories":3038},[207],{"categories":3040},[189],{"categories":3042},[189],{"categories":3044},[244],{"categories":3046},[207],{"categories":3048},[189],{"categories":3050},[139],{"categories":3052},[244],{"categories":3054},[234],{"categories":3056},[],{"categories":3058},[189],{"categories":3060},[],{"categories":3062},[],{"categories":3064},[],{"categories":3066},[184],{"categories":3068},[139],{"categories":3070},[189],{"categories":3072},[181],{"categories":3074},[189],{"categories":3076},[251],{"categories":3078},[],{"categories":3080},[189],{"categories":3082},[],{"categories":3084},[181],{"categories":3086},[189],{"categories":3088},[],{"categories":3090},[189],{"categories":3092},[139],{"categories":3094},[207],{"categories":3096},[139],{"categories":3098},[189],{"categories":3100},[207],{"categories":3102},[189],{"categories":3104},[244],{"categories":3106},[234],{"categories":3108},[181],{"categories":3110},[],{"categories":3112},[189],{"categories":3114},[234],{"categories":3116},[276],{"categories":3118},[207],{"categories":3120},[139],{"categories":3122},[234],{"categories":3124},[181],{"categories":3126},[],{"categories":3128},[189],{"categories":3130},[139],{"categories":3132},[189],{"categories":3134},[139],{"categories":3136},[],{"categories":3138},[189],{"categories":3140},[192],{"categories":3142},[207],{"categories":3144},[189],{"categories":3146},[184],{"categories":3148},[],{"categories":3150},[139],{"categories":3152},[192],{"categories":3154},[139],{"categories":3156},[189],{"categories":3158},[207],{"categories":3160},[181],{"categories":3162},[276],{"categories":3164},[139],{"categories":3166},[139],{"categories":3168},[139],{"categories":3170},[207],{"categories":3172},[184],{"categories":3174},[139],{"categories":3176},[234],{"categories":3178},[207],{"categories":3180},[276],{"categories":3182},[139],{"categories":3184},[],{"categories":3186},[],{"categories":3188},[139],{"categories":3190},[276],{"categories":3192},[237],{"categories":3194},[189],{"categories":3196},[189],{"categories":3198},[207],{"categories":3200},[139],{"categories":3202},[181],{"categories":3204},[234],{"categories":3206},[189],{"categories":3208},[139],{"categories":3210},[251],{"categories":3212},[139],{"categories":3214},[189],{"categories":3216},[],{"categories":3218},[139],{"categories":3220},[139],{"categories":3222},[207],{"categories":3224},[181],{"categories":3226},[],{"categories":3228},[139],{"categories":3230},[139],{"categories":3232},[244],{"categories":3234},[234],{"categories":3236},[139,189],{"categories":3238},[251,184],{"categories":3240},[139],{"categories":3242},[],{"categories":3244},[189],{"categories":3246},[],{"categories":3248},[244],{"categories":3250},[139],{"categories":3252},[],{"categories":3254},[139],{"categories":3256},[207],{"categories":3258},[],{"categories":3260},[189],{"categories":3262},[139],{"categories":3264},[],{"categories":3266},[234],{"categories":3268},[189],{"categories":3270},[139],{"categories":3272},[181],{"categories":3274},[189],{"categories":3276},[139],{"categories":3278},[],{"categories":3280},[276],{"categories":3282},[251],{"categories":3284},[184],{"categories":3286},[184],{"categories":3288},[181],{"categories":3290},[181],{"categories":3292},[139],{"categories":3294},[189],{"categories":3296},[139],{"categories":3298},[139],{"categories":3300},[181],{"categories":3302},[139],{"categories":3304},[251],{"categories":3306},[207],{"categories":3308},[139],{"categories":3310},[189],{"categories":3312},[139],{"categories":3314},[],{"categories":3316},[244],{"categories":3318},[],{"categories":3320},[244],{"categories":3322},[189],{"categories":3324},[181],{"categories":3326},[],{"categories":3328},[276],{"categories":3330},[139],{"categories":3332},[],{"categories":3334},[207],{"categories":3336},[189],{"categories":3338},[244],{"categories":3340},[139],{"categories":3342},[189],{"categories":3344},[244],{"categories":3346},[189],{"categories":3348},[207],{"categories":3350},[181],{"categories":3352},[207],{"categories":3354},[244],{"categories":3356},[139],{"categories":3358},[234],{"categories":3360},[139],{"categories":3362},[139],{"categories":3364},[139],{"categories":3366},[139],{"categories":3368},[139],{"categories":3370},[189],{"categories":3372},[139],{"categories":3374},[189],{"categories":3376},[139],{"categories":3378},[181],{"categories":3380},[139],{"categories":3382},[189],{"categories":3384},[234],{"categories":3386},[181],{"categories":3388},[189],{"categories":3390},[234],{"categories":3392},[],{"categories":3394},[139],{"categories":3396},[139],{"categories":3398},[244],{"categories":3400},[],{"categories":3402},[189],{"categories":3404},[251],{"categories":3406},[139],{"categories":3408},[207],{"categories":3410},[251],{"categories":3412},[189],{"categories":3414},[184],{"categories":3416},[184],{"categories":3418},[139],{"categories":3420},[181],{"categories":3422},[],{"categories":3424},[189],{"categories":3426},[139],{"categories":3428},[],{"categories":3430},[181],{"categories":3432},[139],{"categories":3434},[189],{"categories":3436},[189],{"categories":3438},[],{"categories":3440},[244],{"categories":3442},[244],{"categories":3444},[251],{"categories":3446},[234],{"categories":3448},[],{"categories":3450},[139],{"categories":3452},[189],{"categories":3454},[181],{"categories":3456},[139],{"categories":3458},[244],{"categories":3460},[181],{"categories":3462},[207],{"categories":3464},[207],{"categories":3466},[],{"categories":3468},[207],{"categories":3470},[189],{"categories":3472},[234],{"categories":3474},[237],{"categories":3476},[139],{"categories":3478},[],{"categories":3480},[207],{"categories":3482},[244],{"categories":3484},[184],{"categories":3486},[139],{"categories":3488},[181],{"categories":3490},[276],{"categories":3492},[181],{"categories":3494},[],{"categories":3496},[],{"categories":3498},[207],{"categories":3500},[],{"categories":3502},[189],{"categories":3504},[189],{"categories":3506},[189],{"categories":3508},[],{"categories":3510},[139],{"categories":3512},[],{"categories":3514},[207],{"categories":3516},[181],{"categories":3518},[234],{"categories":3520},[139],{"categories":3522},[207],{"categories":3524},[207],{"categories":3526},[],{"categories":3528},[207],{"categories":3530},[181],{"categories":3532},[139],{"categories":3534},[],{"categories":3536},[189],{"categories":3538},[189],{"categories":3540},[181],{"categories":3542},[],{"categories":3544},[],{"categories":3546},[],{"categories":3548},[234],{"categories":3550},[189],{"categories":3552},[139],{"categories":3554},[],{"categories":3556},[],{"categories":3558},[],{"categories":3560},[234],{"categories":3562},[],{"categories":3564},[139],{"categories":3566},[181],{"categories":3568},[],{"categories":3570},[],{"categories":3572},[234],{"categories":3574},[139],{"categories":3576},[207],{"categories":3578},[],{"categories":3580},[251],{"categories":3582},[207],{"categories":3584},[251],{"categories":3586},[139],{"categories":3588},[],{"categories":3590},[],{"categories":3592},[189],{"categories":3594},[],{"categories":3596},[],{"categories":3598},[189],{"categories":3600},[139],{"categories":3602},[],{"categories":3604},[189],{"categories":3606},[207],{"categories":3608},[139],{"categories":3610},[251],{"categories":3612},[237],{"categories":3614},[189],{"categories":3616},[189],{"categories":3618},[],{"categories":3620},[],{"categories":3622},[],{"categories":3624},[207],{"categories":3626},[],{"categories":3628},[],{"categories":3630},[234],{"categories":3632},[181],{"categories":3634},[],{"categories":3636},[184],{"categories":3638},[251],{"categories":3640},[139],{"categories":3642},[244],{"categories":3644},[181],{"categories":3646},[237],{"categories":3648},[184],{"categories":3650},[244],{"categories":3652},[244],{"categories":3654},[],{"categories":3656},[],{"categories":3658},[189],{"categories":3660},[181],{"categories":3662},[234],{"categories":3664},[181],{"categories":3666},[189],{"categories":3668},[276],{"categories":3670},[139],{"categories":3672},[181],{"categories":3674},[189],{"categories":3676},[],{"categories":3678},[139],{"categories":3680},[207],{"categories":3682},[244],{"categories":3684},[],{"categories":3686},[234],{"categories":3688},[207],{"categories":3690},[181],{"categories":3692},[189],{"categories":3694},[139],{"categories":3696},[184],{"categories":3698},[189,276],{"categories":3700},[189],{"categories":3702},[244],{"categories":3704},[139],{"categories":3706},[139],{"categories":3708},[237],{"categories":3710},[251],{"categories":3712},[189],{"categories":3714},[],{"categories":3716},[189],{"categories":3718},[139],{"categories":3720},[184],{"categories":3722},[],{"categories":3724},[],{"categories":3726},[139],{"categories":3728},[237],{"categories":3730},[139],{"categories":3732},[],{"categories":3734},[207],{"categories":3736},[],{"categories":3738},[207],{"categories":3740},[181],{"categories":3742},[244],{"categories":3744},[139],{"categories":3746},[189],{"categories":3748},[139],{"categories":3750},[139],{"categories":3752},[251],{"categories":3754},[244],{"categories":3756},[],{"categories":3758},[207],{"categories":3760},[139],{"categories":3762},[],{"categories":3764},[139],{"categories":3766},[189],{"categories":3768},[139],{"categories":3770},[189],{"categories":3772},[139],{"categories":3774},[139],{"categories":3776},[139],{"categories":3778},[139],{"categories":3780},[184],{"categories":3782},[],{"categories":3784},[192],{"categories":3786},[207],{"categories":3788},[139],{"categories":3790},[],{"categories":3792},[244],{"categories":3794},[139],{"categories":3796},[139],{"categories":3798},[139],{"categories":3800},[189],{"categories":3802},[207],{"categories":3804},[139],{"categories":3806},[139],{"categories":3808},[139],{"categories":3810},[184],{"categories":3812},[189],{"categories":3814},[234],{"categories":3816},[],{"categories":3818},[237],{"categories":3820},[139],{"categories":3822},[],{"categories":3824},[207],{"categories":3826},[251],{"categories":3828},[],{"categories":3830},[],{"categories":3832},[207],{"categories":3834},[207],{"categories":3836},[251],{"categories":3838},[181],{"categories":3840},[189],{"categories":3842},[189],{"categories":3844},[139],{"categories":3846},[184],{"categories":3848},[],{"categories":3850},[],{"categories":3852},[207],{"categories":3854},[237],{"categories":3856},[244],{"categories":3858},[189],{"categories":3860},[234],{"categories":3862},[237],{"categories":3864},[237],{"categories":3866},[],{"categories":3868},[207],{"categories":3870},[139],{"categories":3872},[139],{"categories":3874},[244],{"categories":3876},[],{"categories":3878},[207],{"categories":3880},[207],{"categories":3882},[207],{"categories":3884},[],{"categories":3886},[189],{"categories":3888},[139],{"categories":3890},[],{"categories":3892},[181],{"categories":3894},[184],{"categories":3896},[],{"categories":3898},[139],{"categories":3900},[139],{"categories":3902},[],{"categories":3904},[244],{"categories":3906},[],{"categories":3908},[],{"categories":3910},[],{"categories":3912},[],{"categories":3914},[139],{"categories":3916},[207],{"categories":3918},[],{"categories":3920},[],{"categories":3922},[139],{"categories":3924},[139],{"categories":3926},[139],{"categories":3928},[237],{"categories":3930},[139],{"categories":3932},[237],{"categories":3934},[],{"categories":3936},[237],{"categories":3938},[237],{"categories":3940},[276],{"categories":3942},[189],{"categories":3944},[244],{"categories":3946},[],{"categories":3948},[],{"categories":3950},[237],{"categories":3952},[244],{"categories":3954},[244],{"categories":3956},[244],{"categories":3958},[],{"categories":3960},[181],{"categories":3962},[244],{"categories":3964},[244],{"categories":3966},[181],{"categories":3968},[244],{"categories":3970},[184],{"categories":3972},[244],{"categories":3974},[244],{"categories":3976},[244],{"categories":3978},[237],{"categories":3980},[207],{"categories":3982},[207],{"categories":3984},[139],{"categories":3986},[244],{"categories":3988},[237],{"categories":3990},[276],{"categories":3992},[237],{"categories":3994},[237],{"categories":3996},[237],{"categories":3998},[],{"categories":4000},[184],{"categories":4002},[],{"categories":4004},[276],{"categories":4006},[244],{"categories":4008},[244],{"categories":4010},[244],{"categories":4012},[189],{"categories":4014},[207,184],{"categories":4016},[237],{"categories":4018},[],{"categories":4020},[],{"categories":4022},[237],{"categories":4024},[],{"categories":4026},[237],{"categories":4028},[207],{"categories":4030},[189],{"categories":4032},[],{"categories":4034},[244],{"categories":4036},[139],{"categories":4038},[234],{"categories":4040},[],{"categories":4042},[139],{"categories":4044},[],{"categories":4046},[207],{"categories":4048},[181],{"categories":4050},[237],{"categories":4052},[],{"categories":4054},[244],{"categories":4056},[207],[4058,4120,4324,4395],{"id":4059,"title":4060,"ai":4061,"body":4067,"categories":4095,"created_at":140,"date_modified":140,"description":130,"extension":141,"faq":140,"featured":142,"kicker_label":140,"meta":4096,"navigation":157,"path":4106,"published_at":4107,"question":140,"scraped_at":4108,"seo":4109,"sitemap":4110,"source_id":4111,"source_name":4112,"source_type":4113,"source_url":4114,"stem":4115,"tags":4116,"thumbnail_url":140,"tldr":4117,"tweet":140,"unknown_tags":4118,"__hash__":4119},"summaries\u002Fsummaries\u002F941741f2e1ae4f3e-google-s-auto-diagnose-llm-diagnoses-test-failures-summary.md","Google's Auto-Diagnose: LLM Diagnoses Test Failures at 90% Accuracy",{"provider":7,"model":4062,"input_tokens":4063,"output_tokens":4064,"processing_time_ms":4065,"cost_usd":4066},"x-ai\u002Fgrok-4.1-fast",7775,1678,12431,0.00237135,{"type":14,"value":4068,"toc":4090},[4069,4073,4076,4080,4083,4087],[17,4070,4072],{"id":4071},"slash-integration-test-debug-time-with-llm-log-analysis","Slash Integration Test Debug Time with LLM Log Analysis",[22,4074,4075],{},"Integration tests at Google, which are 78% functional per a 239-developer survey, often fail with generic symptoms like timeouts while root causes hide in SUT component logs amid noise. Developers report 38.4% of failures take over an hour to diagnose (vs. 2.7% for unit tests), and 8.9% exceed a day—top complaint in a 6,059-developer EngSat survey. Auto-Diagnose triggers on failure via pub\u002Fsub, aggregates INFO+ logs across data centers\u002Fprocesses\u002Fthreads, joins and sorts them by timestamp into one stream, adds component metadata, and feeds to Gemini 2.5 Flash (temperature=0.1, topp=0.8). This yields p50 latency of 56s and p90 of 346s, with 110k input\u002F6k output tokens per run, letting devs act before context-switching.",[17,4077,4079],{"id":4078},"step-by-step-prompting-ensures-reliable-root-causes","Step-by-Step Prompting Ensures Reliable Root Causes",[22,4081,4082],{},"No fine-tuning needed—pure prompt engineering guides the LLM: scan sections, read context, locate failure, summarize errors, conclude only with evidence, and apply hard negatives like 'no conclusion if missing component logs.' Output post-processes to markdown with ==Conclusion== (root cause), ==Investigation Steps==, and ==Most Relevant Log Lines== (clickable links), auto-posted to Critique code reviews. Manual eval on 71 failures from 39 teams hit 90.14% root cause accuracy; failures exposed infra bugs like unsaved crash logs, fixed via feedback loop.",[17,4084,4086],{"id":4085},"production-feedback-ranks-it-top-38-of-tools","Production Feedback Ranks It Top 3.8% of Tools",[22,4088,4089],{},"Deployed on 52,635 failing tests across 224,782 executions and 91,130 changes by 22,962 devs. Of 517 feedbacks from 437 devs, 84.3% were reviewer 'Please fix' requests; dev helpfulness 63%, 'Not helpful' just 5.8% (under 10% live threshold), #14 of 370 Critique tools (top 3.78%). Replicate by building similar pipelines: aggregate\u002Fsort logs, chain-of-thought prompt general LLMs, integrate with review tools for instant value.",{"title":130,"searchDepth":131,"depth":131,"links":4091},[4092,4093,4094],{"id":4071,"depth":131,"text":4072},{"id":4078,"depth":131,"text":4079},{"id":4085,"depth":131,"text":4086},[139],{"content_references":4097,"triage":4103},[4098],{"type":4099,"title":4100,"url":4101,"context":4102},"paper","Auto-Diagnose Pre-Print","https:\u002F\u002Farxiv.org\u002Fpdf\u002F2604.12108","recommended",{"relevance":153,"novelty":154,"quality":154,"actionability":153,"composite":4104,"reasoning":4105},4.55,"Category: AI & LLMs. The article provides a detailed overview of Google's Auto-Diagnose system, which uses LLMs to improve integration test debugging, directly addressing the pain point of long diagnosis times for developers. It includes specific steps for replicating the system, making it highly actionable for the target audience.","\u002Fsummaries\u002F941741f2e1ae4f3e-google-s-auto-diagnose-llm-diagnoses-test-failures-summary","2026-04-18 06:00:41","2026-04-19 01:22:38",{"title":4060,"description":130},{"loc":4106},"941741f2e1ae4f3e","MarkTechPost","article","https:\u002F\u002Fwww.marktechpost.com\u002F2026\u002F04\u002F17\u002Fgoogle-ai-releases-auto-diagnose-an-large-language-model-llm-based-system-to-diagnose-integration-test-failures-at-scale\u002F","summaries\u002F941741f2e1ae4f3e-google-s-auto-diagnose-llm-diagnoses-test-failures-summary",[169,170,172],"Prompt-engineer Gemini 2.5 Flash on timestamp-sorted logs to auto-diagnose integration test root causes, posting fixes to code reviews—90.14% accurate on 71 real failures, 5.8% 'Not helpful' in production across 52k+ tests.",[172],"5z_FYqr6PVfUMXcxaSSuLOcSDdpfdwoN6syFaCpzipE",{"id":4121,"title":4122,"ai":4123,"body":4128,"categories":4308,"created_at":140,"date_modified":140,"description":4309,"extension":141,"faq":140,"featured":142,"kicker_label":140,"meta":4310,"navigation":157,"path":4311,"published_at":4312,"question":140,"scraped_at":4313,"seo":4314,"sitemap":4315,"source_id":4316,"source_name":4317,"source_type":165,"source_url":4318,"stem":4319,"tags":4320,"thumbnail_url":140,"tldr":4321,"tweet":140,"unknown_tags":4322,"__hash__":4323},"summaries\u002Fsummaries\u002Ff932400d9db7252e-slash-llm-token-costs-10x-by-fixing-6-bad-habits-summary.md","Slash LLM Token Costs 10x by Fixing 6 Bad Habits",{"provider":7,"model":4062,"input_tokens":4124,"output_tokens":4125,"processing_time_ms":4126,"cost_usd":4127},8213,2447,18362,0.00257525,{"type":14,"value":4129,"toc":4299},[4130,4134,4137,4143,4149,4153,4156,4161,4164,4169,4173,4176,4181,4184,4188,4191,4197,4200,4205,4209,4212,4218,4221,4226,4230,4233,4254,4257,4260,4265,4267],[17,4131,4133],{"id":4132},"file-formats-are-your-biggest-beginner-token-trap","File Formats Are Your Biggest Beginner Token Trap",[22,4135,4136],{},"Raw PDFs, images, and screenshots explode token counts because LLMs encode binary structure, headers, footers, fonts, and layout metadata. A newbie drags in three 1,500-word PDFs (4,500 words total) and asks Claude to \"Summarize these.\" What should be ~5,000 tokens balloons to 100,000+ due to formatting overhead. This waste compounds as the bloated context bounces back in every turn, filling your window fast.",[22,4138,4139,4142],{},[39,4140,4141],{},"Fix:"," Convert to markdown first. Free web tools or a quick Claude prompt strips junk, yielding 4-6,000 clean tokens—a 20x saving. The speaker built a plugin for Open Brain ecosystem: ingest file, hit \"transform,\" get markdown. For 99% of cases, you only need text, not style. Trade-off: Lose visual fidelity, but gain speed and cost control. He calls file formats \"designed to be human readable, not AI readable.\"",[4144,4145,4146],"blockquote",{},[22,4147,4148],{},"\"4500 words of content can become a 100 plus thousand tokens if you're not careful all you have to do to avoid that is just think in terms of markdown... saving you 20x on the memory.\"\n(Context: Explaining PDF bloat; this quote shows why rookies hit limits in one chat.)",[17,4150,4152],{"id":4151},"conversation-sprawl-wastes-more-than-you-think","Conversation Sprawl Wastes More Than You Think",[22,4154,4155],{},"Intermediate users sprawl chats to 20-40 turns, diluting original instructions amid noise. Models compress history but still resend the full context each turn—every reply costs the entire prior exchange. Mixing research, ideation, and execution in one thread confuses the model and burns tokens.",[22,4157,4158,4160],{},[39,4159,4141],{}," Separate modes. Use short, focused chats (10-15 turns max) for heavy work: gather intel in dedicated threads (Grok for X sentiment, ChatGPT for earnings, Perplexity for research, Claude for blogs), then synthesize in a final crisp prompt. Mark evolving chats upfront: \"Our goal is to evolve and conclude together.\" End with \"Summarize this.\" Start fresh often—long threads correlate with \"LLM psychosis\" as models drift.",[22,4162,4163],{},"Trade-off: More chats mean manual synthesis, but you avoid context dilution and get clearer outputs. Every turn resends history, so sprawling is like \"filling up the context window with croft.\"",[4144,4165,4166],{},[22,4167,4168],{},"\"Why make them suffer... why not just ask for what you want upfront... your objective... should be to be so clear that the AI needs to do nothing else and it just goes and gets the work done.\"\n(Context: Critiquing multi-mode sprawl; highlights single-turn design of LLMs.)",[17,4170,4172],{"id":4171},"plugins-and-preloads-the-silent-context-tax","Plugins and Preloads: The Silent Context Tax",[22,4174,4175],{},"Loading 10+ plugins (e.g., Google Drive you never use) adds 50,000+ tokens before you type—every chat. It's like dumping every workshop tool on the bench before picking a hammer. Hype drives additions, but they barnacle on forever.",[22,4177,4178,4180],{},[39,4179,4141],{}," Audit ruthlessly. Use \u002Fcontext in Claude Code to check loads; disable unused connectors. Only equip 3-5 per task. For advanced setups, prune system prompts weekly—ditch lines from Claude 3.5 era.",[22,4182,4183],{},"Trade-off: Lose convenience for rarely used tools, but gain focus. Models pick wrong tools amid clutter.",[17,4185,4187],{"id":4186},"model-tiering-delivers-8-10x-savings-without-losing-quality","Model Tiering Delivers 8-10x Savings Without Losing Quality",[22,4189,4190],{},"Using Opus (or GPT-4o) for everything—formatting, proofreading, execution—is overkill. A production pipeline the speaker reviewed analyzes long conversations across dozens of dimensions on frontier models, yet costs \u003C25¢\u002Fuser because they tier: Opus for reasoning, Sonnet for execution, Haiku for polish.",[22,4192,4193,4196],{},[39,4194,4195],{},"Example math (5-hour session, same output):"," Sloppy (raw PDFs, 30-turn sprawl, all-Opus): 800k-1M input tokens + 150-200k output = $8-10 ($5\u002FM input, $25\u002FM output). Clean (markdown, fresh chats every 10-15 turns, tiered models, scoped context): 100-150k input + 50-80k output = ~$1. Scale to 10-person team API: $2,000 vs. $250\u002Fmonth.",[22,4198,4199],{},"Trade-off: Test cheaper models per task; Haiku shines on polish but flops on complex reasoning. As models improve, lean out context—trust retrieval over frontloading.",[4144,4201,4202],{},[22,4203,4204],{},"\"Don't bring a Ferrari to the grocery store.\"\n(Context: Model tiering; punchy metaphor for using Opus everywhere.)",[17,4206,4208],{"id":4207},"production-levers-caching-search-and-auditing","Production Levers: Caching, Search, and Auditing",[22,4210,4211],{},"Advanced users screw up at scale (millions of tokens). Ignore prompt caching? Miss 90% discounts (Opus: $0.50\u002FM cached vs. $5\u002FM). System prompts bloat from unpruned cruft. Web search via native Claude burns 10-50k tokens\u002Fquery vs. Perplexity (5x faster, structured citations).",[22,4213,4214,4217],{},[39,4215,4216],{},"Fixes:"," Cache stable context (prompts, tools, docs). Use MCP connectors for cheap search (e.g., Perplexity service). For agents\u002Frepos, test context needs per model gen—dumber models needed fat windows; now trim.",[22,4219,4220],{},"Jen-Hsun Huang pegs engineer token spend at $250k\u002Fyear—don't be that person. With Mythos\u002FGPT-next\u002FGemini (GB300-trained, 10x Opus pricing rumored: $50\u002FM in, $250\u002FM out), sloppy habits scale painfully.",[4144,4222,4223],{},[22,4224,4225],{},"\"The models are not expensive it's your habits that cost a lot... your mistakes scale with the price of intelligence.\"\n(Context: Thesis opener and closer; frames costs as behavioral, not inherent.)",[17,4227,4229],{"id":4228},"tools-to-diagnose-and-fix-your-usage","Tools to Diagnose and Fix Your Usage",[22,4231,4232],{},"Speaker built a \"stupid button\" (Open Brain plugin\u002Fskill\u002Fguardrails):",[4234,4235,4236,4242,4248],"ol",{},[36,4237,4238,4241],{},[39,4239,4240],{},"Audit prompt:"," Paste recent chat; flags raw docs, sprawl, model misuse, redundant loads—prioritizes fixes.",[36,4243,4244,4247],{},[39,4245,4246],{},"Gas tank skill:"," Measures per-session overhead (system prompts, plugins); before\u002Fafter baselines.",[36,4249,4250,4253],{},[39,4251,4252],{},"Guardrails:"," Blocks token-waste on knowledge stores.",[22,4255,4256],{},"Run it: Answers 6 questions (raw files? Fresh chats? All-Opus? Preloads? Caching? Cheap search?). No setup for prompt version.",[22,4258,4259],{},"Real pipeline proves frontier AI viability: Dozens of analysis dimensions on long convos, personalized output, \u003C25¢\u002Fuser.",[4144,4261,4262],{},[22,4263,4264],{},"\"Frontier AI can be absurdly cheap when you know what you're doing... most of us are spending more than we need to on AI.\"\n(Context: Production example; counters \"AI is too expensive\" narrative.)",[17,4266,78],{"id":77},[33,4268,4269,4272,4275,4278,4281,4284,4287,4290,4293,4296],{},[36,4270,4271],{},"Convert all inputs to markdown: 20x token savings on docs\u002Fimages; use free tools or Claude.",[36,4273,4274],{},"Cap chats at 10-15 turns; separate research from execution for clarity and cost.",[36,4276,4277],{},"Audit plugins\u002Fpreloads weekly: Disable barnacles adding 50k+ tokens\u002Fchat.",[36,4279,4280],{},"Tier models: Opus reasoning, Sonnet execution, Haiku polish—8-10x cheaper same output.",[36,4282,4283],{},"Cache stable context: 90% off repeated inputs; essential for agents\u002Fproduction.",[36,4285,4286],{},"Use cheap search (Perplexity\u002FMCP): 10-50k fewer tokens\u002Fquery, faster results.",[36,4288,4289],{},"Prune system prompts biweekly; trim context as models smarten.",[36,4291,4292],{},"Baseline usage with audits: Turn $10\u002Fday slop into $1\u002Fday efficiency.",[36,4294,4295],{},"Prep for 10x pricier models: Habits today dictate ROI tomorrow.",[36,4297,4298],{},"Build token smarts: $250k\u002Fyear engineer spend is avoidable skill gap.",{"title":130,"searchDepth":131,"depth":131,"links":4300},[4301,4302,4303,4304,4305,4306,4307],{"id":4132,"depth":131,"text":4133},{"id":4151,"depth":131,"text":4152},{"id":4171,"depth":131,"text":4172},{"id":4186,"depth":131,"text":4187},{"id":4207,"depth":131,"text":4208},{"id":4228,"depth":131,"text":4229},{"id":77,"depth":131,"text":78},[139],"My site: https:\u002F\u002Fnatebjones.com\nFull Story w\u002F Prompts: https:\u002F\u002Fnatesnewsletter.substack.com\u002Fp\u002Fyour-claude-sessions-cost-10x-what?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true\n___________________\nWhat's really happening inside your AI costs when Jensen Hwang says engineers will spend $250,000 a year on tokens?\n\nThe common story is that frontier models are expensive — but the reality is that your habits cost more than the models ever will, and most users burn 8-10x what they need to.\n\nIn this video, I share the inside scoop on token efficiency before Mythos pricing hits:\n\n • Why raw PDFs can turn 4,500 words into 100,000 tokens\n • How conversation sprawl compounds waste with every turn\n • What plugin overhead costs you before you type a word\n • Where model mixing drops a $10 session to $1\n\nBuilders who keep burning tokens as a badge of honor will face a reckoning when cutting-edge models cost 10x what Opus costs today — the habits you build now determine whether you scale or stall.\n\nChapters\n00:00 Stop burning tokens and blaming the model\n02:30 A real pipeline that costs less than 25 cents per user\n04:30 Rookie mistake: document ingestion and PDFs\n07:00 Convert to Markdown, always\n09:00 Conversation sprawl and context compression\n11:30 The plugin and connector tax\n14:00 Advanced users have the most expensive mistakes\n16:30 The 8-10x cost reduction breakdown\n19:00 What Mythos pricing will do to your mistakes\n21:00 The stupid button: six questions to audit yourself\n23:30 Five commandments for agent token management\n26:00 Use your tokens well, not wastefully\n\nSubscribe for daily AI strategy and news.\nFor deeper playbooks and analysis: https:\u002F\u002Fnatesnewsletter.substack.com\u002F\n\nListen to this video as a podcast.\n- Spotify: https:\u002F\u002Fopen.spotify.com\u002Fshow\u002F0gkFdjd1wptEKJKLu9LbZ4\n- Apple Podcasts: https:\u002F\u002Fpodcasts.apple.com\u002Fus\u002Fpodcast\u002Fai-news-strategy-daily-with-nate-b-jones\u002Fid1877109372",{},"\u002Fsummaries\u002Ff932400d9db7252e-slash-llm-token-costs-10x-by-fixing-6-bad-habits-summary","2026-04-02 14:00:06","2026-04-03 21:11:38",{"title":4122,"description":4309},{"loc":4311},"f932400d9db7252e","AI News & Strategy Daily | Nate B Jones","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=5ztI_dbj6ek","summaries\u002Ff932400d9db7252e-slash-llm-token-costs-10x-by-fixing-6-bad-habits-summary",[169,170,172],"Upcoming frontier models like Claude Mythos will cost 10x more—fix habits like raw PDFs, conversation sprawl, and overusing Opus to drop daily costs from $10 to $1 while getting the same output.",[172],"P_zaT8VyQum6hcxq8OX28jk4OI1NmCnKGvRnX42P8CU",{"id":4325,"title":4326,"ai":4327,"body":4332,"categories":4376,"created_at":140,"date_modified":140,"description":130,"extension":141,"faq":140,"featured":142,"kicker_label":140,"meta":4377,"navigation":157,"path":4381,"published_at":4382,"question":140,"scraped_at":4383,"seo":4384,"sitemap":4385,"source_id":4386,"source_name":4387,"source_type":4113,"source_url":4388,"stem":4389,"tags":4390,"thumbnail_url":140,"tldr":4392,"tweet":140,"unknown_tags":4393,"__hash__":4394},"summaries\u002Fsummaries\u002Fd06783b2b3933858-optimize-claude-limits-plan-remember-pick-models-w-summary.md","Optimize Claude Limits: Plan, Remember, Pick Models Wisely",{"provider":7,"model":4062,"input_tokens":4328,"output_tokens":4329,"processing_time_ms":4330,"cost_usd":4331},3845,1059,13739,0.00127585,{"type":14,"value":4333,"toc":4371},[4334,4338,4341,4345,4364,4368],[17,4335,4337],{"id":4336},"token-waste-drives-limits-not-prompt-count","Token Waste Drives Limits, Not Prompt Count",[22,4339,4340],{},"Claude's usage limits hit unexpectedly because they measure total input\u002Foutput tokens, not just prompt volume. Vague prompts trigger clarifying follow-ups, bloating conversations. Long chats retain irrelevant prior context, forcing reprocessing. Absent memory means repeating instructions across sessions. Overkill models waste tokens on trivial tasks; mismatched tools inflate simple jobs into token-heavy workflows. Anthropic advises planning conversations, being specific, using memory\u002Fprojects, batching related requests, and reviewing prompts pre-send—shifting focus from chat volume to structured efficiency.",[17,4342,4344],{"id":4343},"build-a-work-system-with-four-core-tactics","Build a Work System with Four Core Tactics",[22,4346,4347,4348,4351,4352,4355,4356,4359,4360,4363],{},"Treat Claude as an engineered system, not a casual chat. ",[39,4349,4350],{},"Planning"," structures dialogues upfront to avoid meandering—outline goals, steps, and outputs before starting. ",[39,4353,4354],{},"Memory"," persists key facts via projects or explicit summaries, eliminating repeats; inject summaries into new chats instead of full histories. ",[39,4357,4358],{},"Model selection"," matches task to model: use lighter\u002Fcheaper ones (e.g., Haiku) for simple parsing\u002Fformatting, reserving Opus\u002FSonnet for complex reasoning. ",[39,4361,4362],{},"Tool splitting"," decomposes workflows—handle routine steps with cheaper tools or models first, chaining only when needed, preventing one bloated prompt from exhausting limits.",[17,4365,4367],{"id":4366},"outcomes-sustainable-high-volume-usage","Outcomes: Sustainable High-Volume Usage",[22,4369,4370],{},"This approach scales serious Claude use without hitting walls. Blaming external factors (plans, Anthropic, timing) misses the root: inefficient prompting. Readers gain a repeatable framework—plan\u002Freview\u002Fbatch\u002Fmemory\u002Fmodel—to sustain heavy workloads, turning Claude into a reliable production tool rather than a fragile chat interface.",{"title":130,"searchDepth":131,"depth":131,"links":4372},[4373,4374,4375],{"id":4336,"depth":131,"text":4337},{"id":4343,"depth":131,"text":4344},{"id":4366,"depth":131,"text":4367},[139],{"content_references":4378,"triage":4379},[],{"relevance":153,"novelty":154,"quality":154,"actionability":153,"composite":4104,"reasoning":4380},"Category: AI & LLMs. The article provides a detailed framework for optimizing the use of Claude, addressing specific pain points like token waste and inefficient prompting, which are crucial for developers integrating AI into their products. It offers actionable strategies such as planning conversations and selecting appropriate models, making it immediately applicable for the target audience.","\u002Fsummaries\u002Fd06783b2b3933858-optimize-claude-limits-plan-remember-pick-models-w-summary","2026-05-13 14:43:15","2026-05-14 23:00:46",{"title":4326,"description":130},{"loc":4381},"d06783b2b3933858","Level Up Coding","https:\u002F\u002Flevelup.gitconnected.com\u002Fnever-hit-claude-usage-limits-ever-again-2665f7099b14?source=rss----5517fd7b58a6---4","summaries\u002Fd06783b2b3933858-optimize-claude-limits-plan-remember-pick-models-w-summary",[169,170,4391,172],"ai-tools","Claude limits stem from unnecessary token waste via vague prompts, retained context, repeats, wrong models\u002Ftools—fix by planning convos, adding memory, batching, and model selection to treat it as a work system.",[172],"JCGC4QIX-ubNJYjD1fdD1VSOgajHXiTUOPzkB1UmPvI",{"id":4396,"title":4397,"ai":4398,"body":4403,"categories":4464,"created_at":140,"date_modified":140,"description":130,"extension":141,"faq":140,"featured":142,"kicker_label":140,"meta":4465,"navigation":157,"path":4478,"published_at":4479,"question":140,"scraped_at":4480,"seo":4481,"sitemap":4482,"source_id":4483,"source_name":4484,"source_type":4113,"source_url":4485,"stem":4486,"tags":4487,"thumbnail_url":140,"tldr":4489,"tweet":140,"unknown_tags":4490,"__hash__":4491},"summaries\u002Fsummaries\u002Fa99451de2de64e60-claude-md-patterns-for-bulletproof-ai-coding-summary.md","Claude.md Patterns for Bulletproof AI Coding",{"provider":7,"model":4062,"input_tokens":4399,"output_tokens":4400,"processing_time_ms":4401,"cost_usd":4402},7402,1645,34494,0.00179605,{"type":14,"value":4404,"toc":4459},[4405,4409,4412,4415,4418,4421,4424,4428,4431,4434,4437,4440,4443,4447,4450,4453,4456],[17,4406,4408],{"id":4407},"karpathy-inspired-rules-to-align-claude-with-your-intent","Karpathy-Inspired Rules to Align Claude with Your Intent",[22,4410,4411],{},"Start every claude.md with a project description at the top so Claude grasps the app's structure, services, dependencies, and runtime before diving in—this prevents deduction from code alone and cuts misalignment. Add explicit 'think before coding': Claude must state assumptions, list multiple interpretations if ambiguous, and confirm your choice, slashing course-corrections by forcing clarification over training-data guesses.",[22,4413,4414],{},"Prioritize simplicity: Instruct Claude to solve in minimal lines (e.g., refactor if >200 lines when 50 suffice), add only requested features with proper error handling, and iterate toward conciseness. This avoids verbose overhead that bloats tokens, delays refactoring, and hinders scaling in large apps.",[22,4416,4417],{},"Enforce surgical changes: Touch only task-tracing code; flag unrelated issues (dead code, formatting) without fixing unless asked, as agents scatter focus on 'improvements.' Every edit must link directly to your request, listing other findings for your triage.",[22,4419,4420],{},"Drive goal execution: For each task, Claude defines verifiable success criteria upfront—like writing passing tests for validation inputs\u002Foutputs—then plans, implements, iterates until verified. For UI, pair with tools like Claude Chrome extension or Puppeteer MCP to visually confirm changes, as code alone misleads.",[22,4422,4423],{},"These patterns from Andrej Karpathy's skills repo transform vague tasks into precise, testable outcomes, ensuring behavior matches intent without wild implementations.",[17,4425,4427],{"id":4426},"tool-overrides-safety-and-iterative-refinement","Tool Overrides, Safety, and Iterative Refinement",[22,4429,4430],{},"Override defaults: Skip init-generated commands (e.g., npm run dev) Claude already knows; specify custom tools like GitHub CLI over git, PNPM over npm, or non-standard run instructions to leverage your stack without fallbacks.",[22,4432,4433],{},"Update dynamically: After user corrections, Claude applies fixes then logs learnings to a dedicated file, building a knowledge base of pitfalls and preferences for future tasks—treat claude.md as living, not static.",[22,4435,4436],{},"Embed git safety: Ban irreversible commands (force-push, reset --hard, rm -rf) without confirmation; if unsure, always ask. This guards production from accidents like unwanted merges.",[22,4438,4439],{},"Use path-scoped rule files: Create e.g., api-rules.md (first line declares scope) for file-type rules, referenced in root claude.md. This avoids bloat—Claude loads only relevant rules, staying focused without interference.",[22,4441,4442],{},"For monorepos, add scoped claude.md per subfolder for module-specific guidance; root holds global rules only, preventing divergence from irrelevant instructions.",[17,4444,4446],{"id":4445},"prioritized-structure-and-verification-for-peak-performance","Prioritized Structure and Verification for Peak Performance",[22,4448,4449],{},"Order by priority: Hard rules first (non-negotiable, e.g., safety, scoping), then medium (key principles like simplicity), finally low (references). Burying criticals dilutes impact.",[22,4451,4452],{},"Mandate full verification before completion: Don't just add code—run builds, tests, linting, type checks to confirm functionality. Report only when all pass, using every mechanism for fidelity.",[22,4454,4455],{},"Cap at 300 lines: Beyond this, performance drops; trim ruthlessly for focus.",[22,4457,4458],{},"This setup, refined from community testing and shipping, eliminates agent fights: Claude reasons correctly, changes precisely, verifies rigorously, and adapts—saving hours on real projects.",{"title":130,"searchDepth":131,"depth":131,"links":4460},[4461,4462,4463],{"id":4407,"depth":131,"text":4408},{"id":4426,"depth":131,"text":4427},{"id":4445,"depth":131,"text":4446},[139],{"content_references":4466,"triage":4476},[4467,4473],{"type":4468,"title":4469,"author":4470,"url":4471,"context":4472},"other","andrej-karpathy-skills","forrestchang","https:\u002F\u002Fgithub.com\u002Fforrestchang\u002Fandrej-karpathy-skills\u002F","cited",{"type":146,"title":4474,"url":4475,"context":149},"Klaus","https:\u002F\u002Fklausai.com\u002Fr\u002FMv1e2",{"relevance":153,"novelty":154,"quality":154,"actionability":153,"composite":4104,"reasoning":4477},"Category: AI & LLMs. The article provides practical patterns for using Claude.md effectively, addressing the pain points of AI-Curious Developers and Technical Founders by offering concrete strategies for coding with AI. It emphasizes actionable steps like starting with a project description and defining success criteria, making it immediately applicable for building AI-powered products.","\u002Fsummaries\u002Fa99451de2de64e60-claude-md-patterns-for-bulletproof-ai-coding-summary","2026-04-28 14:30:29","2026-05-03 16:44:39",{"title":4397,"description":130},{"loc":4478},"c6527f0f4e352415","AI LABS","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=fMY5Sdj2DMk","summaries\u002Fa99451de2de64e60-claude-md-patterns-for-bulletproof-ai-coding-summary",[169,4488,170,172],"agents","Craft claude.md with project description first, Karpathy rules like 'think before coding' and simplicity, tool overrides, git safety, scoped files, verification steps, and priority-ordered instructions under 300 lines to make Claude ship exact implementations without guesswork or bloat.",[172],"aSUZZ1N9_uYmZbJKhVlN4jk82uo4tI6cro4gCyHSS4w"]