[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-24d0f80c9dbc7001-qwen-3-6-plus-tops-benchmarks-in-agentic-coding-mu-summary":3,"summaries-facets-categories":79,"summary-related-24d0f80c9dbc7001-qwen-3-6-plus-tops-benchmarks-in-agentic-coding-mu-summary":3649},{"id":4,"title":5,"ai":6,"body":13,"categories":54,"created_at":55,"date_modified":55,"description":56,"extension":57,"faq":55,"featured":58,"kicker_label":55,"meta":59,"navigation":60,"path":61,"published_at":62,"question":55,"scraped_at":63,"seo":64,"sitemap":65,"source_id":66,"source_name":67,"source_type":68,"source_url":69,"stem":70,"tags":71,"thumbnail_url":55,"tldr":76,"tweet":55,"unknown_tags":77,"__hash__":78},"summaries\u002Fsummaries\u002F24d0f80c9dbc7001-qwen-3-6-plus-tops-benchmarks-in-agentic-coding-mu-summary.md","Qwen 3.6 Plus Tops Benchmarks in Agentic Coding & Multimodal",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",6172,1350,12408,0.00144215,{"type":14,"value":15,"toc":46},"minimark",[16,21,25,29,32,36,39,43],[17,18,20],"h2",{"id":19},"agentic-coding-excels-at-repo-level-and-terminal-tasks","Agentic Coding Excels at Repo-Level and Terminal Tasks",[22,23,24],"p",{},"Qwen 3.6 Plus handles full project repositories, terminal commands, and automation workflows via strong agentic capabilities, including long-horizon planning and tool use. Its 1 million token context window enables detailed generations like a browser-based Mac OS clone with functional Finder, Safari, Mail, Photos, Music, Calendar, Terminal, Calculator, and System Settings apps—complete with SVG icons, light\u002Fdark themes, and interactive displays. This outperforms Claude Opus 4.6, which failed similar tasks. On benchmarks, it surpasses or ties top models: leading Terminal Bench, competitive on Su Bench against Claude Opus 4.5 and Gemini 3 Pro. Trade-off: generates long code slowly due to extended reasoning, making it less ideal for quick outputs but superior for complex projects like 3D scenes, games, or F1 drift simulations with RPM controls, camera angles, and resets.",[17,26,28],{"id":27},"front-end-generation-matches-pro-models","Front-End Generation Matches Pro Models",[22,30,31],{},"For web development, Qwen 3.6 Plus produces high-fidelity UIs rivaling Claude Opus, such as TikTok mobile clones with scrolling, likes, and accurate components; three polished landing pages with dynamic typography, animations, and pricing sections (third iteration flawless); and a Minecraft clone featuring block breaking\u002Fplacing, textures, water, cave systems, ores, lava (health drain on contact), and infinite terrain elements. SVG outputs shine: animated butterfly (fixed wings after iteration, better than Gemini 2.5), moonlight water painting with gradients. Use Kilo CLI for free access via its open-source AI agent to prompt these—e.g., 'create browser-based OS cloning Mac OS' yields production-ready code.",[17,33,35],{"id":34},"multimodal-reasoning-handles-real-world-media","Multimodal Reasoning Handles Real-World Media",[22,37,38],{},"Advanced multimodal processing covers images (scrapes all content, reasons visually), documents, videos (condenses 29-minute video to 23-second edit; turns videos into lectures), and visual coding (generates Excel interactions, PowerPoints, spreadsheets). In their chatbot, it built a Lord of the Rings slide deck with accurate logo, story summary, key locations, and scenes—ideal for work presentations or notes. Computer-use agent automates desktop tasks. Benchmarks show breakthroughs in MMU, complex document understanding, visual analysis, video reasoning, and visual coding.",[17,40,42],{"id":41},"affordable-access-beats-proprietary-costs","Affordable Access Beats Proprietary Costs",[22,44,45],{},"API pricing: $0.50 per 1M input tokens, $3 per 1M output—reasonable for capabilities. Free options: their chatbot, OpenRouter API, Kilo Code free API\u002FCLI. Open-source variants arrive later this week. Integrate into workflows for sway tasks, debugging, automation; test via Kilo CLI for agentic prompts without cost.",{"title":47,"searchDepth":48,"depth":48,"links":49},"",2,[50,51,52,53],{"id":19,"depth":48,"text":20},{"id":27,"depth":48,"text":28},{"id":34,"depth":48,"text":35},{"id":41,"depth":48,"text":42},[],null,"Download Wispr Flow on Android - https:\u002F\u002Fref.wisprflow.ai\u002Fworldofai\n\nQwen 3.6 Plus just dropped—and it might be the BEST open-source AI model we’ve ever seen.\n\n🔗 My Links:\nSponsor a Video or Do a Demo of Your Product, Contact me: intheworldzofai@gmail.com\n🔥 Become a Patron (Private Discord): https:\u002F\u002Fpatreon.com\u002FWorldofAi\n🧠 Follow me on Twitter: https:\u002F\u002Ftwitter.com\u002Fintheworldofai \n🚨 Subscribe To The SECOND Channel: https:\u002F\u002Fwww.youtube.com\u002F@UCYwLV1gDwzGbg7jXQ52bVnQ \n👩🏻‍🏫 Learn to code with Scrimba – from fullstack to AI https:\u002F\u002Fscrimba.com\u002F?via=worldofai (20% OFF)\n🚨 Subscribe To The FREE AI Newsletter For Regular AI Updates: https:\u002F\u002Fintheworldofai.com\u002F\n👾 Join the World of AI Discord! : https:\u002F\u002Fdiscord.gg\u002FNPf8FCn4cD\n\nSomething coming soon :) https:\u002F\u002Fwww.skool.com\u002Fworldofai-automation\n\n[Must Watch]:\nClaude Code Computer Use Can Control Your ENTIRE Computer! Automate Your Life!: https:\u002F\u002Fyoutu.be\u002FKiywNP4b0aw?si=HuJnvik0AgLjIkCb\nTurn Antigravity Into AN AI Autonomous Engineering Team! Automate Your Code with Subagents!: https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=yuaBPLNdNSU\nGemini 3.5? NEW Gemini Stealth Model Is POWERFUL & Fast! (Fully Tested): https:\u002F\u002Fyoutu.be\u002F1abLcL33eKA?si=H50xRhJxVYM7HFPK\n\n📌 LINKS & RESOURCES\nBlog: https:\u002F\u002Fqwen.ai\u002Fblog?id=qwen3.6\nQwen Chat: https:\u002F\u002Fchat.qwen.ai\u002F\nKilo (Free API): https:\u002F\u002Fkilo.ai\u002Fcli\nAPI Portal: https:\u002F\u002Fmodelstudio.console.alibabacloud.com\u002Fap-southeast-1?tab=doc#\u002Fdoc\u002F?type=model&url=2840914_2&modelId=qwen3.6-plus\nOpenRouter: https:\u002F\u002Fopenrouter.ai\u002Fqwen\u002Fqwen3.6-plus:free\n\nIn this video, I fully test Qwen 3.6 Plus, a brand new agentic coding model with a massive 1 MILLION token context window. This model is built for real-world tasks, from full-stack development to complex automation workflows—and honestly, it’s competing directly with top-tier models like Claude Opus 4.5 and Gemini 3.\n\nWe’ll break down:\n• Agentic coding performance (SWE tasks, debugging, automation)\n• Frontend capabilities (including 3D scenes and advanced UI generation)\n• Benchmark comparisons vs Opus 4.5, Kimi K2.5, and more\n• Multimodal reasoning (images, documents, video understanding)\n• Real-world use cases + integrations with tools like Claude Code\n\nIf you’re into AI coding, vibe coding, or building with next-gen LLMs, this is a model you NEED to know about.\n\nThis might genuinely be the closest we’ve gotten to fully autonomous AI agents.\n\n[Time Stamp]:\n0:00 - Introduction\n1:21 - Benchmarks\n3:14 - Web Dev + Video Understanding\n4:03 - Pricing\u002FTech Specs\n4:29 - How To Use\n5:18 - Macos Clone Demo\n6:54 - F1 Drift Demo\n7:22 - SVG Demo\n8:23 - Frontend Demo\n10:10 - Video Understanding\n10:41 - Slide Deck\n11:32 - Minecraft Clone\n\n\nTags (comma-separated):\nqwen 3.6 plus, qwen ai, qwen open source, best open source ai, ai coding model, agentic ai, agentic coding, vibe coding, ai automation, llm coding, claude opus 4.5, gemini 3 ai, kimi k2.5, ai comparison, ai benchmarks, swe bench, terminal bench, ai frontend development, ai web dev, ai tools 2026, open source llm, coding ai assistant, ai developer tools, multimodal ai, ai agents, autonomous ai, qwen 3.6 review, qwen coding model, ai workflow automation, ai software engineer 🚀\n\nHashtags:\n#Qwen3_6Plus #OpenSourceAI #AICoding #AgenticAI #VibeCoding #AIAutomation #AIFrontend #LLM #NextGenAI #ClaudeOpus #Gemini3 #CodingAI #AutonomousAI #AIWorkflow #AI2026 #MultimodalAI #SoftwareEngineerAI","md",false,{},true,"\u002Fsummaries\u002F24d0f80c9dbc7001-qwen-3-6-plus-tops-benchmarks-in-agentic-coding-mu-summary","2026-04-03 05:21:24","2026-04-03 21:19:32",{"title":5,"description":56},{"loc":61},"24d0f80c9dbc7001","WorldofAI","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=FuUISGqIC3k","summaries\u002F24d0f80c9dbc7001-qwen-3-6-plus-tops-benchmarks-in-agentic-coding-mu-summary",[72,73,74,75],"llm","agents","frontend","coding","Qwen 3.6 Plus beats or matches Claude Opus 4.5 and Gemini 3 Pro on Su Bench, Terminal Bench, and MMU, excelling in repo-level coding, front-end generation, and video reasoning with 1M context window.",[],"cVNuKFpmoDzBTbhxKK5Z5I3Y5Opvyq-L2_LBH-qZIZg",[80,83,86,89,92,95,97,99,101,103,105,107,110,112,114,116,118,120,122,124,126,128,131,134,136,138,141,143,145,148,150,152,154,156,158,160,162,164,166,168,170,172,174,176,178,180,182,184,186,188,190,192,194,196,198,200,202,204,206,208,210,212,214,216,218,220,222,224,226,228,230,232,234,236,238,240,242,244,246,248,250,252,254,256,258,260,262,264,266,268,270,272,274,276,278,280,282,284,286,288,290,292,294,296,298,300,302,304,306,308,310,312,314,316,318,320,322,324,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,368,370,372,374,376,378,380,382,384,386,388,390,392,394,396,398,400,403,405,407,409,411,413,415,417,419,421,423,425,427,429,431,433,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,465,467,469,471,473,475,477,479,481,483,485,487,489,491,493,495,497,499,501,503,505,507,509,511,513,515,517,519,521,523,525,527,529,531,533,535,537,539,541,543,545,547,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,709,711,713,715,717,719,721,723,725,727,729,731,733,735,737,739,741,743,745,747,749,751,753,755,757,759,761,763,765,767,769,771,773,775,777,779,781,783,785,787,789,791,793,795,797,799,801,803,805,807,809,811,813,815,817,819,821,823,825,827,829,831,833,835,837,839,841,843,845,847,849,851,853,855,857,859,861,863,865,867,869,871,873,875,877,879,881,883,885,887,889,891,893,895,897,899,901,903,905,907,909,911,913,915,917,919,921,923,925,927,929,931,933,935,937,939,941,943,945,947,949,951,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1199,1201,1203,1205,1207,1209,1211,1213,1215,1217,1219,1221,1223,1225,1227,1229,1231,1233,1235,1237,1239,1241,1243,1245,1247,1249,1251,1253,1255,1257,1259,1261,1263,1265,1267,1269,1271,1273,1275,1277,1279,1281,1283,1285,1287,1289,1291,1293,1295,1297,1299,1301,1303,1305,1307,1309,1311,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1431,1433,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1461,1463,1465,1467,1469,1471,1473,1475,1477,1479,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1507,1509,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1781,1783,1785,1787,1789,1791,1793,1795,1797,1799,1801,1803,1805,1807,1809,1811,1813,1815,1817,1819,1821,1823,1825,1827,1829,1831,1833,1835,1837,1839,1841,1843,1845,1847,1849,1851,1853,1855,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1925,1927,1929,1931,1933,1935,1937,1939,1941,1943,1945,1947,1949,1951,1953,1955,1957,1959,1961,1963,1965,1967,1969,1971,1973,1975,1977,1979,1981,1983,1985,1987,1989,1991,1993,1995,1997,1999,2001,2003,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2513,2515,2517,2519,2521,2523,2525,2527,2529,2531,2533,2535,2537,2539,2541,2543,2545,2547,2549,2551,2553,2555,2557,2559,2561,2563,2565,2567,2569,2571,2573,2575,2577,2579,2581,2583,2585,2587,2589,2591,2593,2595,2597,2599,2601,2603,2605,2607,2609,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2697,2699,2701,2703,2705,2707,2709,2711,2713,2715,2717,2719,2721,2723,2725,2727,2729,2731,2733,2735,2737,2739,2741,2743,2745,2747,2749,2751,2753,2755,2757,2759,2761,2763,2765,2767,2769,2771,2773,2775,2777,2779,2781,2783,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3643,3645,3647],{"categories":81},[82],"Developer Productivity",{"categories":84},[85],"Business & SaaS",{"categories":87},[88],"AI & LLMs",{"categories":90},[91],"AI Automation",{"categories":93},[94],"Product Strategy",{"categories":96},[88],{"categories":98},[82],{"categories":100},[85],{"categories":102},[],{"categories":104},[88],{"categories":106},[],{"categories":108},[109],"AI News & Trends",{"categories":111},[91],{"categories":113},[109],{"categories":115},[91],{"categories":117},[91],{"categories":119},[88],{"categories":121},[88],{"categories":123},[109],{"categories":125},[88],{"categories":127},[],{"categories":129},[130],"Design & Frontend",{"categories":132},[133],"Data Science & Visualization",{"categories":135},[109],{"categories":137},[],{"categories":139},[140],"Software Engineering",{"categories":142},[88],{"categories":144},[91],{"categories":146},[147],"Marketing & Growth",{"categories":149},[88],{"categories":151},[91],{"categories":153},[],{"categories":155},[],{"categories":157},[130],{"categories":159},[91],{"categories":161},[82],{"categories":163},[130],{"categories":165},[88],{"categories":167},[91],{"categories":169},[109],{"categories":171},[],{"categories":173},[],{"categories":175},[91],{"categories":177},[140],{"categories":179},[],{"categories":181},[85],{"categories":183},[],{"categories":185},[],{"categories":187},[91],{"categories":189},[91],{"categories":191},[88],{"categories":193},[],{"categories":195},[140],{"categories":197},[],{"categories":199},[],{"categories":201},[],{"categories":203},[88],{"categories":205},[147],{"categories":207},[130],{"categories":209},[130],{"categories":211},[88],{"categories":213},[91],{"categories":215},[88],{"categories":217},[88],{"categories":219},[91],{"categories":221},[91],{"categories":223},[133],{"categories":225},[109],{"categories":227},[91],{"categories":229},[147],{"categories":231},[91],{"categories":233},[94],{"categories":235},[],{"categories":237},[91],{"categories":239},[],{"categories":241},[91],{"categories":243},[140],{"categories":245},[130],{"categories":247},[88],{"categories":249},[],{"categories":251},[],{"categories":253},[91],{"categories":255},[],{"categories":257},[88],{"categories":259},[],{"categories":261},[82],{"categories":263},[140],{"categories":265},[85],{"categories":267},[109],{"categories":269},[88],{"categories":271},[],{"categories":273},[88],{"categories":275},[],{"categories":277},[140],{"categories":279},[133],{"categories":281},[],{"categories":283},[88],{"categories":285},[130],{"categories":287},[],{"categories":289},[130],{"categories":291},[91],{"categories":293},[],{"categories":295},[91],{"categories":297},[109],{"categories":299},[88],{"categories":301},[],{"categories":303},[91],{"categories":305},[88],{"categories":307},[94],{"categories":309},[],{"categories":311},[88],{"categories":313},[91],{"categories":315},[91],{"categories":317},[],{"categories":319},[133],{"categories":321},[88],{"categories":323},[],{"categories":325},[82],{"categories":327},[85],{"categories":329},[88],{"categories":331},[91],{"categories":333},[140],{"categories":335},[88],{"categories":337},[],{"categories":339},[],{"categories":341},[88],{"categories":343},[],{"categories":345},[130],{"categories":347},[],{"categories":349},[88],{"categories":351},[],{"categories":353},[91],{"categories":355},[88],{"categories":357},[130],{"categories":359},[],{"categories":361},[88],{"categories":363},[88],{"categories":365},[85],{"categories":367},[91],{"categories":369},[88],{"categories":371},[130],{"categories":373},[91],{"categories":375},[],{"categories":377},[],{"categories":379},[109],{"categories":381},[],{"categories":383},[88],{"categories":385},[85,147],{"categories":387},[],{"categories":389},[88],{"categories":391},[],{"categories":393},[],{"categories":395},[88],{"categories":397},[],{"categories":399},[88],{"categories":401},[402],"DevOps & Cloud",{"categories":404},[],{"categories":406},[109],{"categories":408},[130],{"categories":410},[],{"categories":412},[109],{"categories":414},[109],{"categories":416},[88],{"categories":418},[147],{"categories":420},[],{"categories":422},[85],{"categories":424},[],{"categories":426},[88,402],{"categories":428},[88],{"categories":430},[88],{"categories":432},[91],{"categories":434},[88,140],{"categories":436},[133],{"categories":438},[88],{"categories":440},[147],{"categories":442},[91],{"categories":444},[91],{"categories":446},[],{"categories":448},[91],{"categories":450},[88,85],{"categories":452},[],{"categories":454},[130],{"categories":456},[130],{"categories":458},[],{"categories":460},[],{"categories":462},[109],{"categories":464},[],{"categories":466},[82],{"categories":468},[140],{"categories":470},[88],{"categories":472},[130],{"categories":474},[91],{"categories":476},[140],{"categories":478},[109],{"categories":480},[130],{"categories":482},[],{"categories":484},[88],{"categories":486},[88],{"categories":488},[88],{"categories":490},[109],{"categories":492},[82],{"categories":494},[88],{"categories":496},[91],{"categories":498},[402],{"categories":500},[130],{"categories":502},[91],{"categories":504},[],{"categories":506},[],{"categories":508},[130],{"categories":510},[109],{"categories":512},[133],{"categories":514},[],{"categories":516},[88],{"categories":518},[88],{"categories":520},[85],{"categories":522},[88],{"categories":524},[88],{"categories":526},[109],{"categories":528},[],{"categories":530},[91],{"categories":532},[140],{"categories":534},[],{"categories":536},[88],{"categories":538},[88],{"categories":540},[91],{"categories":542},[],{"categories":544},[],{"categories":546},[88],{"categories":548},[],{"categories":550},[85],{"categories":552},[91],{"categories":554},[],{"categories":556},[82],{"categories":558},[88],{"categories":560},[85],{"categories":562},[109],{"categories":564},[],{"categories":566},[],{"categories":568},[],{"categories":570},[109],{"categories":572},[109],{"categories":574},[],{"categories":576},[],{"categories":578},[85],{"categories":580},[],{"categories":582},[],{"categories":584},[82],{"categories":586},[],{"categories":588},[147],{"categories":590},[91],{"categories":592},[85],{"categories":594},[91],{"categories":596},[],{"categories":598},[94],{"categories":600},[130],{"categories":602},[140],{"categories":604},[88],{"categories":606},[91],{"categories":608},[85],{"categories":610},[88],{"categories":612},[],{"categories":614},[],{"categories":616},[140],{"categories":618},[133],{"categories":620},[94],{"categories":622},[91],{"categories":624},[88],{"categories":626},[],{"categories":628},[402],{"categories":630},[],{"categories":632},[91],{"categories":634},[],{"categories":636},[],{"categories":638},[88],{"categories":640},[130],{"categories":642},[147],{"categories":644},[91],{"categories":646},[],{"categories":648},[82],{"categories":650},[],{"categories":652},[109],{"categories":654},[88,402],{"categories":656},[109],{"categories":658},[88],{"categories":660},[85],{"categories":662},[88],{"categories":664},[],{"categories":666},[85],{"categories":668},[],{"categories":670},[140],{"categories":672},[130],{"categories":674},[109],{"categories":676},[133],{"categories":678},[82],{"categories":680},[88],{"categories":682},[140],{"categories":684},[],{"categories":686},[],{"categories":688},[94],{"categories":690},[],{"categories":692},[88],{"categories":694},[],{"categories":696},[130],{"categories":698},[130],{"categories":700},[130],{"categories":702},[],{"categories":704},[],{"categories":706},[109],{"categories":708},[91],{"categories":710},[88],{"categories":712},[88],{"categories":714},[88],{"categories":716},[85],{"categories":718},[88],{"categories":720},[],{"categories":722},[140],{"categories":724},[140],{"categories":726},[85],{"categories":728},[],{"categories":730},[88],{"categories":732},[88],{"categories":734},[85],{"categories":736},[109],{"categories":738},[147],{"categories":740},[91],{"categories":742},[],{"categories":744},[130],{"categories":746},[],{"categories":748},[88],{"categories":750},[],{"categories":752},[85],{"categories":754},[91],{"categories":756},[],{"categories":758},[402],{"categories":760},[133],{"categories":762},[140],{"categories":764},[147],{"categories":766},[140],{"categories":768},[91],{"categories":770},[],{"categories":772},[],{"categories":774},[91],{"categories":776},[82],{"categories":778},[91],{"categories":780},[94],{"categories":782},[85],{"categories":784},[],{"categories":786},[88],{"categories":788},[94],{"categories":790},[88],{"categories":792},[88],{"categories":794},[147],{"categories":796},[130],{"categories":798},[91],{"categories":800},[],{"categories":802},[],{"categories":804},[402],{"categories":806},[140],{"categories":808},[],{"categories":810},[91],{"categories":812},[88],{"categories":814},[130,88],{"categories":816},[82],{"categories":818},[],{"categories":820},[88],{"categories":822},[82],{"categories":824},[130],{"categories":826},[91],{"categories":828},[140],{"categories":830},[],{"categories":832},[88],{"categories":834},[],{"categories":836},[82],{"categories":838},[],{"categories":840},[91],{"categories":842},[94],{"categories":844},[88],{"categories":846},[88],{"categories":848},[130],{"categories":850},[91],{"categories":852},[402],{"categories":854},[130],{"categories":856},[91],{"categories":858},[88],{"categories":860},[88],{"categories":862},[88],{"categories":864},[109],{"categories":866},[],{"categories":868},[94],{"categories":870},[91],{"categories":872},[130],{"categories":874},[91],{"categories":876},[140],{"categories":878},[130],{"categories":880},[91],{"categories":882},[109],{"categories":884},[],{"categories":886},[88],{"categories":888},[130],{"categories":890},[88],{"categories":892},[82],{"categories":894},[109],{"categories":896},[88],{"categories":898},[147],{"categories":900},[88],{"categories":902},[88],{"categories":904},[91],{"categories":906},[91],{"categories":908},[88],{"categories":910},[91],{"categories":912},[130],{"categories":914},[88],{"categories":916},[],{"categories":918},[],{"categories":920},[140],{"categories":922},[],{"categories":924},[82],{"categories":926},[402],{"categories":928},[],{"categories":930},[82],{"categories":932},[85],{"categories":934},[147],{"categories":936},[],{"categories":938},[85],{"categories":940},[],{"categories":942},[],{"categories":944},[],{"categories":946},[],{"categories":948},[],{"categories":950},[88],{"categories":952},[91],{"categories":954},[402],{"categories":956},[82],{"categories":958},[88],{"categories":960},[140],{"categories":962},[94],{"categories":964},[88],{"categories":966},[147],{"categories":968},[88],{"categories":970},[88],{"categories":972},[88],{"categories":974},[88,82],{"categories":976},[140],{"categories":978},[140],{"categories":980},[130],{"categories":982},[88],{"categories":984},[],{"categories":986},[],{"categories":988},[],{"categories":990},[140],{"categories":992},[133],{"categories":994},[109],{"categories":996},[130],{"categories":998},[],{"categories":1000},[88],{"categories":1002},[88],{"categories":1004},[],{"categories":1006},[],{"categories":1008},[91],{"categories":1010},[88],{"categories":1012},[85],{"categories":1014},[],{"categories":1016},[82],{"categories":1018},[88],{"categories":1020},[82],{"categories":1022},[88],{"categories":1024},[140],{"categories":1026},[147],{"categories":1028},[88,130],{"categories":1030},[109],{"categories":1032},[130],{"categories":1034},[],{"categories":1036},[402],{"categories":1038},[130],{"categories":1040},[91],{"categories":1042},[],{"categories":1044},[],{"categories":1046},[],{"categories":1048},[],{"categories":1050},[140],{"categories":1052},[91],{"categories":1054},[91],{"categories":1056},[88],{"categories":1058},[88],{"categories":1060},[],{"categories":1062},[130],{"categories":1064},[],{"categories":1066},[],{"categories":1068},[91],{"categories":1070},[],{"categories":1072},[],{"categories":1074},[147],{"categories":1076},[147],{"categories":1078},[91],{"categories":1080},[],{"categories":1082},[88],{"categories":1084},[88],{"categories":1086},[140],{"categories":1088},[130],{"categories":1090},[130],{"categories":1092},[91],{"categories":1094},[82],{"categories":1096},[88],{"categories":1098},[130],{"categories":1100},[130],{"categories":1102},[91],{"categories":1104},[91],{"categories":1106},[88],{"categories":1108},[],{"categories":1110},[],{"categories":1112},[88],{"categories":1114},[91],{"categories":1116},[109],{"categories":1118},[140],{"categories":1120},[82],{"categories":1122},[88],{"categories":1124},[],{"categories":1126},[91],{"categories":1128},[91],{"categories":1130},[],{"categories":1132},[82],{"categories":1134},[88],{"categories":1136},[82],{"categories":1138},[82],{"categories":1140},[],{"categories":1142},[],{"categories":1144},[91],{"categories":1146},[91],{"categories":1148},[88],{"categories":1150},[88],{"categories":1152},[109],{"categories":1154},[133],{"categories":1156},[94],{"categories":1158},[109],{"categories":1160},[130],{"categories":1162},[],{"categories":1164},[109],{"categories":1166},[],{"categories":1168},[],{"categories":1170},[],{"categories":1172},[],{"categories":1174},[140],{"categories":1176},[133],{"categories":1178},[],{"categories":1180},[88],{"categories":1182},[88],{"categories":1184},[133],{"categories":1186},[140],{"categories":1188},[],{"categories":1190},[],{"categories":1192},[91],{"categories":1194},[109],{"categories":1196},[109],{"categories":1198},[91],{"categories":1200},[82],{"categories":1202},[88,402],{"categories":1204},[],{"categories":1206},[130],{"categories":1208},[82],{"categories":1210},[91],{"categories":1212},[130],{"categories":1214},[],{"categories":1216},[91],{"categories":1218},[91],{"categories":1220},[88],{"categories":1222},[147],{"categories":1224},[140],{"categories":1226},[130],{"categories":1228},[],{"categories":1230},[91],{"categories":1232},[88],{"categories":1234},[91],{"categories":1236},[91],{"categories":1238},[91],{"categories":1240},[147],{"categories":1242},[91],{"categories":1244},[88],{"categories":1246},[],{"categories":1248},[147],{"categories":1250},[109],{"categories":1252},[91],{"categories":1254},[],{"categories":1256},[],{"categories":1258},[88],{"categories":1260},[91],{"categories":1262},[109],{"categories":1264},[91],{"categories":1266},[],{"categories":1268},[],{"categories":1270},[],{"categories":1272},[91],{"categories":1274},[],{"categories":1276},[],{"categories":1278},[133],{"categories":1280},[88],{"categories":1282},[133],{"categories":1284},[109],{"categories":1286},[88],{"categories":1288},[88],{"categories":1290},[91],{"categories":1292},[88],{"categories":1294},[],{"categories":1296},[],{"categories":1298},[402],{"categories":1300},[],{"categories":1302},[],{"categories":1304},[82],{"categories":1306},[],{"categories":1308},[],{"categories":1310},[],{"categories":1312},[],{"categories":1314},[140],{"categories":1316},[109],{"categories":1318},[147],{"categories":1320},[85],{"categories":1322},[88],{"categories":1324},[88],{"categories":1326},[85],{"categories":1328},[],{"categories":1330},[130],{"categories":1332},[91],{"categories":1334},[85],{"categories":1336},[88],{"categories":1338},[88],{"categories":1340},[82],{"categories":1342},[],{"categories":1344},[82],{"categories":1346},[88],{"categories":1348},[147],{"categories":1350},[91],{"categories":1352},[109],{"categories":1354},[85],{"categories":1356},[88],{"categories":1358},[91],{"categories":1360},[],{"categories":1362},[88],{"categories":1364},[82],{"categories":1366},[88],{"categories":1368},[],{"categories":1370},[109],{"categories":1372},[88],{"categories":1374},[],{"categories":1376},[85],{"categories":1378},[88],{"categories":1380},[],{"categories":1382},[],{"categories":1384},[],{"categories":1386},[88],{"categories":1388},[],{"categories":1390},[402],{"categories":1392},[88],{"categories":1394},[],{"categories":1396},[88],{"categories":1398},[88],{"categories":1400},[88],{"categories":1402},[88,402],{"categories":1404},[88],{"categories":1406},[88],{"categories":1408},[130],{"categories":1410},[91],{"categories":1412},[],{"categories":1414},[91],{"categories":1416},[88],{"categories":1418},[88],{"categories":1420},[88],{"categories":1422},[82],{"categories":1424},[82],{"categories":1426},[140],{"categories":1428},[130],{"categories":1430},[91],{"categories":1432},[],{"categories":1434},[88],{"categories":1436},[109],{"categories":1438},[88],{"categories":1440},[85],{"categories":1442},[],{"categories":1444},[402],{"categories":1446},[130],{"categories":1448},[130],{"categories":1450},[91],{"categories":1452},[109],{"categories":1454},[91],{"categories":1456},[88],{"categories":1458},[],{"categories":1460},[88],{"categories":1462},[],{"categories":1464},[],{"categories":1466},[88],{"categories":1468},[88],{"categories":1470},[88],{"categories":1472},[91],{"categories":1474},[88],{"categories":1476},[],{"categories":1478},[133],{"categories":1480},[91],{"categories":1482},[],{"categories":1484},[88],{"categories":1486},[109],{"categories":1488},[],{"categories":1490},[130],{"categories":1492},[402],{"categories":1494},[109],{"categories":1496},[140],{"categories":1498},[140],{"categories":1500},[109],{"categories":1502},[109],{"categories":1504},[402],{"categories":1506},[],{"categories":1508},[109],{"categories":1510},[88],{"categories":1512},[82],{"categories":1514},[109],{"categories":1516},[],{"categories":1518},[133],{"categories":1520},[109],{"categories":1522},[140],{"categories":1524},[109],{"categories":1526},[402],{"categories":1528},[88],{"categories":1530},[88],{"categories":1532},[],{"categories":1534},[85],{"categories":1536},[],{"categories":1538},[],{"categories":1540},[88],{"categories":1542},[88],{"categories":1544},[88],{"categories":1546},[88],{"categories":1548},[],{"categories":1550},[133],{"categories":1552},[82],{"categories":1554},[],{"categories":1556},[88],{"categories":1558},[88],{"categories":1560},[402],{"categories":1562},[402],{"categories":1564},[],{"categories":1566},[91],{"categories":1568},[109],{"categories":1570},[109],{"categories":1572},[88],{"categories":1574},[91],{"categories":1576},[],{"categories":1578},[130],{"categories":1580},[88],{"categories":1582},[88],{"categories":1584},[],{"categories":1586},[],{"categories":1588},[402],{"categories":1590},[88],{"categories":1592},[140],{"categories":1594},[85],{"categories":1596},[88],{"categories":1598},[],{"categories":1600},[91],{"categories":1602},[82],{"categories":1604},[82],{"categories":1606},[],{"categories":1608},[88],{"categories":1610},[130],{"categories":1612},[91],{"categories":1614},[],{"categories":1616},[88],{"categories":1618},[88],{"categories":1620},[91],{"categories":1622},[],{"categories":1624},[91],{"categories":1626},[140],{"categories":1628},[],{"categories":1630},[88],{"categories":1632},[],{"categories":1634},[88],{"categories":1636},[],{"categories":1638},[88],{"categories":1640},[88],{"categories":1642},[],{"categories":1644},[88],{"categories":1646},[109],{"categories":1648},[88],{"categories":1650},[88],{"categories":1652},[82],{"categories":1654},[88],{"categories":1656},[109],{"categories":1658},[91],{"categories":1660},[],{"categories":1662},[88],{"categories":1664},[147],{"categories":1666},[],{"categories":1668},[],{"categories":1670},[],{"categories":1672},[82],{"categories":1674},[109],{"categories":1676},[91],{"categories":1678},[88],{"categories":1680},[130],{"categories":1682},[91],{"categories":1684},[],{"categories":1686},[91],{"categories":1688},[],{"categories":1690},[88],{"categories":1692},[91],{"categories":1694},[88],{"categories":1696},[],{"categories":1698},[88],{"categories":1700},[88],{"categories":1702},[109],{"categories":1704},[130],{"categories":1706},[91],{"categories":1708},[130],{"categories":1710},[85],{"categories":1712},[],{"categories":1714},[],{"categories":1716},[88],{"categories":1718},[82],{"categories":1720},[109],{"categories":1722},[],{"categories":1724},[],{"categories":1726},[140],{"categories":1728},[130],{"categories":1730},[],{"categories":1732},[88],{"categories":1734},[],{"categories":1736},[147],{"categories":1738},[88],{"categories":1740},[402],{"categories":1742},[140],{"categories":1744},[],{"categories":1746},[91],{"categories":1748},[88],{"categories":1750},[91],{"categories":1752},[91],{"categories":1754},[88],{"categories":1756},[],{"categories":1758},[82],{"categories":1760},[88],{"categories":1762},[85],{"categories":1764},[140],{"categories":1766},[130],{"categories":1768},[],{"categories":1770},[],{"categories":1772},[],{"categories":1774},[91],{"categories":1776},[130],{"categories":1778},[109],{"categories":1780},[88],{"categories":1782},[109],{"categories":1784},[130],{"categories":1786},[],{"categories":1788},[130],{"categories":1790},[109],{"categories":1792},[85],{"categories":1794},[88],{"categories":1796},[109],{"categories":1798},[147],{"categories":1800},[],{"categories":1802},[],{"categories":1804},[133],{"categories":1806},[88,140],{"categories":1808},[109],{"categories":1810},[88],{"categories":1812},[91],{"categories":1814},[91],{"categories":1816},[88],{"categories":1818},[],{"categories":1820},[140],{"categories":1822},[88],{"categories":1824},[133],{"categories":1826},[91],{"categories":1828},[147],{"categories":1830},[402],{"categories":1832},[],{"categories":1834},[82],{"categories":1836},[91],{"categories":1838},[91],{"categories":1840},[140],{"categories":1842},[88],{"categories":1844},[88],{"categories":1846},[],{"categories":1848},[],{"categories":1850},[],{"categories":1852},[402],{"categories":1854},[109],{"categories":1856},[88],{"categories":1858},[88],{"categories":1860},[88],{"categories":1862},[],{"categories":1864},[133],{"categories":1866},[85],{"categories":1868},[],{"categories":1870},[91],{"categories":1872},[402],{"categories":1874},[],{"categories":1876},[130],{"categories":1878},[130],{"categories":1880},[],{"categories":1882},[140],{"categories":1884},[130],{"categories":1886},[88],{"categories":1888},[],{"categories":1890},[109],{"categories":1892},[88],{"categories":1894},[130],{"categories":1896},[91],{"categories":1898},[109],{"categories":1900},[],{"categories":1902},[91],{"categories":1904},[130],{"categories":1906},[88],{"categories":1908},[],{"categories":1910},[88],{"categories":1912},[88],{"categories":1914},[402],{"categories":1916},[109],{"categories":1918},[133],{"categories":1920},[133],{"categories":1922},[],{"categories":1924},[],{"categories":1926},[],{"categories":1928},[91],{"categories":1930},[140],{"categories":1932},[140],{"categories":1934},[],{"categories":1936},[],{"categories":1938},[88],{"categories":1940},[],{"categories":1942},[91],{"categories":1944},[88],{"categories":1946},[],{"categories":1948},[88],{"categories":1950},[85],{"categories":1952},[88],{"categories":1954},[147],{"categories":1956},[91],{"categories":1958},[88],{"categories":1960},[140],{"categories":1962},[109],{"categories":1964},[91],{"categories":1966},[],{"categories":1968},[109],{"categories":1970},[91],{"categories":1972},[91],{"categories":1974},[],{"categories":1976},[85],{"categories":1978},[91],{"categories":1980},[],{"categories":1982},[88],{"categories":1984},[82],{"categories":1986},[109],{"categories":1988},[402],{"categories":1990},[91],{"categories":1992},[91],{"categories":1994},[82],{"categories":1996},[88],{"categories":1998},[],{"categories":2000},[],{"categories":2002},[130],{"categories":2004},[88,85],{"categories":2006},[],{"categories":2008},[82],{"categories":2010},[133],{"categories":2012},[88],{"categories":2014},[140],{"categories":2016},[88],{"categories":2018},[91],{"categories":2020},[88],{"categories":2022},[88],{"categories":2024},[109],{"categories":2026},[91],{"categories":2028},[],{"categories":2030},[],{"categories":2032},[91],{"categories":2034},[88],{"categories":2036},[402],{"categories":2038},[],{"categories":2040},[88],{"categories":2042},[91],{"categories":2044},[],{"categories":2046},[88],{"categories":2048},[147],{"categories":2050},[133],{"categories":2052},[91],{"categories":2054},[88],{"categories":2056},[402],{"categories":2058},[],{"categories":2060},[88],{"categories":2062},[147],{"categories":2064},[130],{"categories":2066},[88],{"categories":2068},[],{"categories":2070},[147],{"categories":2072},[109],{"categories":2074},[88],{"categories":2076},[88],{"categories":2078},[82],{"categories":2080},[],{"categories":2082},[],{"categories":2084},[130],{"categories":2086},[88],{"categories":2088},[133],{"categories":2090},[147],{"categories":2092},[147],{"categories":2094},[109],{"categories":2096},[],{"categories":2098},[],{"categories":2100},[88],{"categories":2102},[],{"categories":2104},[88,140],{"categories":2106},[109],{"categories":2108},[91],{"categories":2110},[140],{"categories":2112},[88],{"categories":2114},[82],{"categories":2116},[],{"categories":2118},[],{"categories":2120},[82],{"categories":2122},[147],{"categories":2124},[88],{"categories":2126},[],{"categories":2128},[130,88],{"categories":2130},[402],{"categories":2132},[82],{"categories":2134},[],{"categories":2136},[85],{"categories":2138},[85],{"categories":2140},[88],{"categories":2142},[140],{"categories":2144},[91],{"categories":2146},[109],{"categories":2148},[147],{"categories":2150},[130],{"categories":2152},[88],{"categories":2154},[88],{"categories":2156},[88],{"categories":2158},[82],{"categories":2160},[88],{"categories":2162},[91],{"categories":2164},[109],{"categories":2166},[],{"categories":2168},[],{"categories":2170},[133],{"categories":2172},[140],{"categories":2174},[88],{"categories":2176},[130],{"categories":2178},[133],{"categories":2180},[88],{"categories":2182},[88],{"categories":2184},[91],{"categories":2186},[91],{"categories":2188},[88,85],{"categories":2190},[],{"categories":2192},[130],{"categories":2194},[],{"categories":2196},[88],{"categories":2198},[109],{"categories":2200},[82],{"categories":2202},[82],{"categories":2204},[91],{"categories":2206},[88],{"categories":2208},[85],{"categories":2210},[140],{"categories":2212},[147],{"categories":2214},[],{"categories":2216},[109],{"categories":2218},[88],{"categories":2220},[88],{"categories":2222},[109],{"categories":2224},[140],{"categories":2226},[88],{"categories":2228},[91],{"categories":2230},[109],{"categories":2232},[88],{"categories":2234},[130],{"categories":2236},[88],{"categories":2238},[88],{"categories":2240},[402],{"categories":2242},[94],{"categories":2244},[91],{"categories":2246},[88],{"categories":2248},[109],{"categories":2250},[91],{"categories":2252},[147],{"categories":2254},[88],{"categories":2256},[],{"categories":2258},[88],{"categories":2260},[],{"categories":2262},[],{"categories":2264},[],{"categories":2266},[85],{"categories":2268},[88],{"categories":2270},[91],{"categories":2272},[109],{"categories":2274},[109],{"categories":2276},[109],{"categories":2278},[109],{"categories":2280},[],{"categories":2282},[82],{"categories":2284},[91],{"categories":2286},[109],{"categories":2288},[82],{"categories":2290},[91],{"categories":2292},[88],{"categories":2294},[88,91],{"categories":2296},[91],{"categories":2298},[402],{"categories":2300},[109],{"categories":2302},[109],{"categories":2304},[91],{"categories":2306},[88],{"categories":2308},[],{"categories":2310},[109],{"categories":2312},[147],{"categories":2314},[82],{"categories":2316},[88],{"categories":2318},[88],{"categories":2320},[],{"categories":2322},[140],{"categories":2324},[],{"categories":2326},[82],{"categories":2328},[91],{"categories":2330},[109],{"categories":2332},[88],{"categories":2334},[109],{"categories":2336},[82],{"categories":2338},[109],{"categories":2340},[109],{"categories":2342},[],{"categories":2344},[85],{"categories":2346},[91],{"categories":2348},[109],{"categories":2350},[109],{"categories":2352},[109],{"categories":2354},[109],{"categories":2356},[109],{"categories":2358},[109],{"categories":2360},[109],{"categories":2362},[109],{"categories":2364},[109],{"categories":2366},[109],{"categories":2368},[133],{"categories":2370},[82],{"categories":2372},[88],{"categories":2374},[88],{"categories":2376},[],{"categories":2378},[88,82],{"categories":2380},[],{"categories":2382},[91],{"categories":2384},[109],{"categories":2386},[91],{"categories":2388},[88],{"categories":2390},[88],{"categories":2392},[88],{"categories":2394},[88],{"categories":2396},[88],{"categories":2398},[91],{"categories":2400},[85],{"categories":2402},[130],{"categories":2404},[109],{"categories":2406},[88],{"categories":2408},[],{"categories":2410},[],{"categories":2412},[91],{"categories":2414},[130],{"categories":2416},[88],{"categories":2418},[],{"categories":2420},[],{"categories":2422},[147],{"categories":2424},[88],{"categories":2426},[],{"categories":2428},[],{"categories":2430},[82],{"categories":2432},[85],{"categories":2434},[88],{"categories":2436},[85],{"categories":2438},[130],{"categories":2440},[],{"categories":2442},[109],{"categories":2444},[],{"categories":2446},[130],{"categories":2448},[88],{"categories":2450},[147],{"categories":2452},[],{"categories":2454},[147],{"categories":2456},[],{"categories":2458},[],{"categories":2460},[91],{"categories":2462},[],{"categories":2464},[85],{"categories":2466},[82],{"categories":2468},[130],{"categories":2470},[140],{"categories":2472},[],{"categories":2474},[],{"categories":2476},[88],{"categories":2478},[82],{"categories":2480},[147],{"categories":2482},[],{"categories":2484},[91],{"categories":2486},[91],{"categories":2488},[109],{"categories":2490},[88],{"categories":2492},[91],{"categories":2494},[88],{"categories":2496},[91],{"categories":2498},[88],{"categories":2500},[94],{"categories":2502},[109],{"categories":2504},[],{"categories":2506},[147],{"categories":2508},[140],{"categories":2510},[91],{"categories":2512},[],{"categories":2514},[88],{"categories":2516},[91],{"categories":2518},[85],{"categories":2520},[82],{"categories":2522},[88],{"categories":2524},[130],{"categories":2526},[140],{"categories":2528},[140],{"categories":2530},[88],{"categories":2532},[133],{"categories":2534},[88],{"categories":2536},[91],{"categories":2538},[85],{"categories":2540},[91],{"categories":2542},[88],{"categories":2544},[88],{"categories":2546},[91],{"categories":2548},[109],{"categories":2550},[],{"categories":2552},[82],{"categories":2554},[88],{"categories":2556},[91],{"categories":2558},[88],{"categories":2560},[88],{"categories":2562},[],{"categories":2564},[130],{"categories":2566},[85],{"categories":2568},[109],{"categories":2570},[88],{"categories":2572},[88],{"categories":2574},[130],{"categories":2576},[147],{"categories":2578},[133],{"categories":2580},[88],{"categories":2582},[109],{"categories":2584},[88],{"categories":2586},[91],{"categories":2588},[402],{"categories":2590},[88],{"categories":2592},[91],{"categories":2594},[133],{"categories":2596},[],{"categories":2598},[91],{"categories":2600},[140],{"categories":2602},[130],{"categories":2604},[88],{"categories":2606},[82],{"categories":2608},[85],{"categories":2610},[140],{"categories":2612},[],{"categories":2614},[91],{"categories":2616},[88],{"categories":2618},[],{"categories":2620},[109],{"categories":2622},[],{"categories":2624},[109],{"categories":2626},[88],{"categories":2628},[91],{"categories":2630},[91],{"categories":2632},[91],{"categories":2634},[],{"categories":2636},[],{"categories":2638},[88],{"categories":2640},[88],{"categories":2642},[],{"categories":2644},[130],{"categories":2646},[91],{"categories":2648},[147],{"categories":2650},[82],{"categories":2652},[],{"categories":2654},[],{"categories":2656},[109],{"categories":2658},[140],{"categories":2660},[88],{"categories":2662},[88],{"categories":2664},[88],{"categories":2666},[140],{"categories":2668},[109],{"categories":2670},[130],{"categories":2672},[88],{"categories":2674},[88],{"categories":2676},[88],{"categories":2678},[109],{"categories":2680},[88],{"categories":2682},[109],{"categories":2684},[91],{"categories":2686},[91],{"categories":2688},[140],{"categories":2690},[91],{"categories":2692},[88],{"categories":2694},[140],{"categories":2696},[130],{"categories":2698},[],{"categories":2700},[91],{"categories":2702},[],{"categories":2704},[],{"categories":2706},[85],{"categories":2708},[88],{"categories":2710},[91],{"categories":2712},[82],{"categories":2714},[91],{"categories":2716},[147],{"categories":2718},[],{"categories":2720},[91],{"categories":2722},[],{"categories":2724},[82],{"categories":2726},[91],{"categories":2728},[],{"categories":2730},[91],{"categories":2732},[88],{"categories":2734},[109],{"categories":2736},[88],{"categories":2738},[91],{"categories":2740},[109],{"categories":2742},[91],{"categories":2744},[140],{"categories":2746},[130],{"categories":2748},[82],{"categories":2750},[],{"categories":2752},[91],{"categories":2754},[130],{"categories":2756},[109],{"categories":2758},[88],{"categories":2760},[130],{"categories":2762},[82],{"categories":2764},[],{"categories":2766},[91],{"categories":2768},[91],{"categories":2770},[88],{"categories":2772},[],{"categories":2774},[91],{"categories":2776},[94],{"categories":2778},[109],{"categories":2780},[91],{"categories":2782},[85],{"categories":2784},[],{"categories":2786},[88],{"categories":2788},[94],{"categories":2790},[88],{"categories":2792},[91],{"categories":2794},[109],{"categories":2796},[82],{"categories":2798},[402],{"categories":2800},[88],{"categories":2802},[88],{"categories":2804},[88],{"categories":2806},[109],{"categories":2808},[85],{"categories":2810},[88],{"categories":2812},[130],{"categories":2814},[109],{"categories":2816},[402],{"categories":2818},[88],{"categories":2820},[],{"categories":2822},[],{"categories":2824},[402],{"categories":2826},[133],{"categories":2828},[91],{"categories":2830},[91],{"categories":2832},[109],{"categories":2834},[88],{"categories":2836},[82],{"categories":2838},[130],{"categories":2840},[91],{"categories":2842},[88],{"categories":2844},[147],{"categories":2846},[88],{"categories":2848},[91],{"categories":2850},[],{"categories":2852},[88],{"categories":2854},[88],{"categories":2856},[109],{"categories":2858},[82],{"categories":2860},[],{"categories":2862},[88],{"categories":2864},[88],{"categories":2866},[140],{"categories":2868},[130],{"categories":2870},[88,91],{"categories":2872},[147,85],{"categories":2874},[88],{"categories":2876},[],{"categories":2878},[91],{"categories":2880},[],{"categories":2882},[140],{"categories":2884},[88],{"categories":2886},[109],{"categories":2888},[],{"categories":2890},[91],{"categories":2892},[],{"categories":2894},[91],{"categories":2896},[82],{"categories":2898},[91],{"categories":2900},[88],{"categories":2902},[402],{"categories":2904},[147],{"categories":2906},[85],{"categories":2908},[85],{"categories":2910},[82],{"categories":2912},[82],{"categories":2914},[88],{"categories":2916},[91],{"categories":2918},[88],{"categories":2920},[88],{"categories":2922},[82],{"categories":2924},[88],{"categories":2926},[147],{"categories":2928},[109],{"categories":2930},[88],{"categories":2932},[91],{"categories":2934},[88],{"categories":2936},[],{"categories":2938},[140],{"categories":2940},[],{"categories":2942},[91],{"categories":2944},[82],{"categories":2946},[],{"categories":2948},[402],{"categories":2950},[88],{"categories":2952},[],{"categories":2954},[109],{"categories":2956},[91],{"categories":2958},[140],{"categories":2960},[88],{"categories":2962},[91],{"categories":2964},[140],{"categories":2966},[91],{"categories":2968},[109],{"categories":2970},[82],{"categories":2972},[109],{"categories":2974},[140],{"categories":2976},[88],{"categories":2978},[130],{"categories":2980},[88],{"categories":2982},[88],{"categories":2984},[88],{"categories":2986},[88],{"categories":2988},[91],{"categories":2990},[88],{"categories":2992},[91],{"categories":2994},[88],{"categories":2996},[82],{"categories":2998},[88],{"categories":3000},[91],{"categories":3002},[130],{"categories":3004},[82],{"categories":3006},[91],{"categories":3008},[130],{"categories":3010},[],{"categories":3012},[88],{"categories":3014},[88],{"categories":3016},[140],{"categories":3018},[],{"categories":3020},[91],{"categories":3022},[147],{"categories":3024},[88],{"categories":3026},[109],{"categories":3028},[147],{"categories":3030},[91],{"categories":3032},[85],{"categories":3034},[85],{"categories":3036},[88],{"categories":3038},[82],{"categories":3040},[],{"categories":3042},[88],{"categories":3044},[],{"categories":3046},[82],{"categories":3048},[88],{"categories":3050},[91],{"categories":3052},[91],{"categories":3054},[],{"categories":3056},[140],{"categories":3058},[140],{"categories":3060},[147],{"categories":3062},[130],{"categories":3064},[],{"categories":3066},[88],{"categories":3068},[82],{"categories":3070},[88],{"categories":3072},[140],{"categories":3074},[82],{"categories":3076},[109],{"categories":3078},[109],{"categories":3080},[],{"categories":3082},[109],{"categories":3084},[91],{"categories":3086},[130],{"categories":3088},[133],{"categories":3090},[88],{"categories":3092},[],{"categories":3094},[109],{"categories":3096},[140],{"categories":3098},[85],{"categories":3100},[88],{"categories":3102},[82],{"categories":3104},[402],{"categories":3106},[82],{"categories":3108},[],{"categories":3110},[],{"categories":3112},[109],{"categories":3114},[],{"categories":3116},[91],{"categories":3118},[91],{"categories":3120},[91],{"categories":3122},[],{"categories":3124},[88],{"categories":3126},[],{"categories":3128},[109],{"categories":3130},[82],{"categories":3132},[130],{"categories":3134},[88],{"categories":3136},[109],{"categories":3138},[109],{"categories":3140},[],{"categories":3142},[109],{"categories":3144},[82],{"categories":3146},[88],{"categories":3148},[],{"categories":3150},[91],{"categories":3152},[91],{"categories":3154},[82],{"categories":3156},[],{"categories":3158},[],{"categories":3160},[],{"categories":3162},[130],{"categories":3164},[91],{"categories":3166},[88],{"categories":3168},[],{"categories":3170},[],{"categories":3172},[],{"categories":3174},[130],{"categories":3176},[],{"categories":3178},[82],{"categories":3180},[],{"categories":3182},[],{"categories":3184},[130],{"categories":3186},[88],{"categories":3188},[109],{"categories":3190},[],{"categories":3192},[147],{"categories":3194},[109],{"categories":3196},[147],{"categories":3198},[88],{"categories":3200},[],{"categories":3202},[],{"categories":3204},[91],{"categories":3206},[],{"categories":3208},[],{"categories":3210},[91],{"categories":3212},[88],{"categories":3214},[],{"categories":3216},[91],{"categories":3218},[109],{"categories":3220},[147],{"categories":3222},[133],{"categories":3224},[91],{"categories":3226},[91],{"categories":3228},[],{"categories":3230},[],{"categories":3232},[],{"categories":3234},[109],{"categories":3236},[],{"categories":3238},[],{"categories":3240},[130],{"categories":3242},[82],{"categories":3244},[],{"categories":3246},[85],{"categories":3248},[147],{"categories":3250},[88],{"categories":3252},[140],{"categories":3254},[82],{"categories":3256},[133],{"categories":3258},[85],{"categories":3260},[140],{"categories":3262},[],{"categories":3264},[],{"categories":3266},[91],{"categories":3268},[82],{"categories":3270},[130],{"categories":3272},[82],{"categories":3274},[91],{"categories":3276},[402],{"categories":3278},[91],{"categories":3280},[],{"categories":3282},[88],{"categories":3284},[109],{"categories":3286},[140],{"categories":3288},[],{"categories":3290},[130],{"categories":3292},[109],{"categories":3294},[82],{"categories":3296},[91],{"categories":3298},[88],{"categories":3300},[85],{"categories":3302},[91,402],{"categories":3304},[91],{"categories":3306},[140],{"categories":3308},[88],{"categories":3310},[133],{"categories":3312},[147],{"categories":3314},[91],{"categories":3316},[],{"categories":3318},[91],{"categories":3320},[88],{"categories":3322},[85],{"categories":3324},[],{"categories":3326},[],{"categories":3328},[88],{"categories":3330},[133],{"categories":3332},[88],{"categories":3334},[],{"categories":3336},[109],{"categories":3338},[],{"categories":3340},[109],{"categories":3342},[140],{"categories":3344},[91],{"categories":3346},[88],{"categories":3348},[147],{"categories":3350},[140],{"categories":3352},[],{"categories":3354},[109],{"categories":3356},[88],{"categories":3358},[],{"categories":3360},[88],{"categories":3362},[91],{"categories":3364},[88],{"categories":3366},[91],{"categories":3368},[88],{"categories":3370},[88],{"categories":3372},[88],{"categories":3374},[88],{"categories":3376},[85],{"categories":3378},[],{"categories":3380},[94],{"categories":3382},[109],{"categories":3384},[88],{"categories":3386},[],{"categories":3388},[140],{"categories":3390},[88],{"categories":3392},[88],{"categories":3394},[91],{"categories":3396},[109],{"categories":3398},[88],{"categories":3400},[88],{"categories":3402},[85],{"categories":3404},[91],{"categories":3406},[130],{"categories":3408},[],{"categories":3410},[133],{"categories":3412},[88],{"categories":3414},[],{"categories":3416},[109],{"categories":3418},[147],{"categories":3420},[],{"categories":3422},[],{"categories":3424},[109],{"categories":3426},[109],{"categories":3428},[147],{"categories":3430},[82],{"categories":3432},[91],{"categories":3434},[91],{"categories":3436},[88],{"categories":3438},[85],{"categories":3440},[],{"categories":3442},[],{"categories":3444},[109],{"categories":3446},[133],{"categories":3448},[140],{"categories":3450},[91],{"categories":3452},[130],{"categories":3454},[133],{"categories":3456},[133],{"categories":3458},[],{"categories":3460},[109],{"categories":3462},[88],{"categories":3464},[88],{"categories":3466},[140],{"categories":3468},[],{"categories":3470},[109],{"categories":3472},[109],{"categories":3474},[109],{"categories":3476},[],{"categories":3478},[91],{"categories":3480},[88],{"categories":3482},[],{"categories":3484},[82],{"categories":3486},[85],{"categories":3488},[],{"categories":3490},[88],{"categories":3492},[88],{"categories":3494},[],{"categories":3496},[140],{"categories":3498},[],{"categories":3500},[],{"categories":3502},[],{"categories":3504},[],{"categories":3506},[88],{"categories":3508},[109],{"categories":3510},[],{"categories":3512},[],{"categories":3514},[88],{"categories":3516},[88],{"categories":3518},[88],{"categories":3520},[133],{"categories":3522},[88],{"categories":3524},[133],{"categories":3526},[],{"categories":3528},[133],{"categories":3530},[133],{"categories":3532},[402],{"categories":3534},[91],{"categories":3536},[140],{"categories":3538},[],{"categories":3540},[],{"categories":3542},[133],{"categories":3544},[140],{"categories":3546},[140],{"categories":3548},[140],{"categories":3550},[],{"categories":3552},[82],{"categories":3554},[140],{"categories":3556},[140],{"categories":3558},[82],{"categories":3560},[140],{"categories":3562},[85],{"categories":3564},[140],{"categories":3566},[140],{"categories":3568},[140],{"categories":3570},[133],{"categories":3572},[109],{"categories":3574},[109],{"categories":3576},[88],{"categories":3578},[140],{"categories":3580},[133],{"categories":3582},[402],{"categories":3584},[133],{"categories":3586},[133],{"categories":3588},[133],{"categories":3590},[],{"categories":3592},[85],{"categories":3594},[],{"categories":3596},[402],{"categories":3598},[140],{"categories":3600},[140],{"categories":3602},[140],{"categories":3604},[91],{"categories":3606},[109,85],{"categories":3608},[133],{"categories":3610},[],{"categories":3612},[],{"categories":3614},[133],{"categories":3616},[],{"categories":3618},[133],{"categories":3620},[109],{"categories":3622},[91],{"categories":3624},[],{"categories":3626},[140],{"categories":3628},[88],{"categories":3630},[130],{"categories":3632},[],{"categories":3634},[88],{"categories":3636},[],{"categories":3638},[109],{"categories":3640},[82],{"categories":3642},[133],{"categories":3644},[],{"categories":3646},[140],{"categories":3648},[109],[3650,3735,3813,3876],{"id":3651,"title":3652,"ai":3653,"body":3658,"categories":3695,"created_at":55,"date_modified":55,"description":47,"extension":57,"faq":55,"featured":58,"kicker_label":55,"meta":3696,"navigation":60,"path":3722,"published_at":55,"question":55,"scraped_at":3723,"seo":3724,"sitemap":3725,"source_id":3726,"source_name":3727,"source_type":3728,"source_url":3729,"stem":3730,"tags":3731,"thumbnail_url":55,"tldr":3732,"tweet":55,"unknown_tags":3733,"__hash__":3734},"summaries\u002Fsummaries\u002F5dc48731884521dd-glm-5-1-excels-in-long-horizon-agentic-coding-summary.md","GLM-5.1 Excels in Long-Horizon Agentic Coding",{"provider":7,"model":8,"input_tokens":3654,"output_tokens":3655,"processing_time_ms":3656,"cost_usd":3657},7818,1969,9224,0.00252545,{"type":14,"value":3659,"toc":3690},[3660,3664,3667,3670,3673,3677,3680,3683,3687],[17,3661,3663],{"id":3662},"sustains-optimization-over-extended-horizons-for-superior-results","Sustains Optimization Over Extended Horizons for Superior Results",[22,3665,3666],{},"GLM-5.1 breaks through short-session limits by maintaining productivity across hundreds of iterations and thousands of tool calls, revising strategies based on benchmarks and self-analysis. On VectorDBBench, it optimizes a Rust vector database for SIFT-1M (Recall ≥95%), starting from a skeleton with HTTP endpoints. Over 655 iterations and 6,000+ tool calls, it hits 21.5k QPS—6x the prior 3.5k QPS best from Claude Opus 4.6 in 50 turns. Progress follows a staircase: incremental tuning plateaus, then structural shifts like IVF probing with f16 compression (iteration ~90, 6.4k QPS) or u8 prescoring + f16 reranking (iteration ~240, 13.4k QPS) unlock jumps, with temporary Recall dips during exploration.",[22,3668,3669],{},"On KernelBench Level 3 (50 full-model optimizations like MobileNet, VGG), GLM-5.1 delivers 3.6x geometric mean speedup vs. PyTorch baseline (torch.compile max-autotune: 1.49x), sustaining gains over 1,200 turns per problem in isolated H100 Docker. It outlasts GLM-5 (early plateau) and Claude Opus 4.5, trailing only Opus 4.6 (4.2x) but showing more headroom. Audits confirm no benchmark exploits.",[22,3671,3672],{},"For open-ended tasks without metrics, GLM-5.1 builds a Linux desktop web app from scratch over 8 hours: starts with taskbar\u002Fwindows, iterates to add file browser, terminal, editor, monitor, calculator, games—polishing UI, interactions, and edge cases via self-review loops.",[17,3674,3676],{"id":3675},"tops-coding-and-agentic-benchmarks-with-precise-judgment","Tops Coding and Agentic Benchmarks with Precise Judgment",[22,3678,3679],{},"GLM-5.1 leads SWE-Bench Pro at 58.4% (vs. GLM-5 55.1%, GPT-5.4 57.7%), NL2Repo at 42.7% (vs. GLM-5 35.9%), Terminal-Bench 2.0 Terminus-2 at 63.5%, and CyberGym at 68.7% (Claude Code harness). In agentic evals: BrowseComp w\u002F Context Manage 79.3%, τ³-Bench 70.6%, MCP-Atlas 71.8%, Tool-Decathlon 40.7%, Vending Bench 2 $5,634 revenue. Reasoning holds strong: HLE w\u002F Tools 52.3%, AIME 2026 95.3%, GPQA-Diamond 86.2%. Settings emphasize long contexts (up to 202k tokens) and tool use without hacking (rule + model detection).",[22,3681,3682],{},"Trade-offs: Higher quota use (2-3x), challenges remain in escaping local optima, trace coherence over thousands of calls, and metric-free self-eval.",[17,3684,3686],{"id":3685},"deploy-immediately-for-agentic-workflows","Deploy Immediately for Agentic Workflows",[22,3688,3689],{},"Open-source (MIT) on GitHub\u002FHuggingFace\u002FModelScope; infer with vLLM\u002FSGLang. API on api.z.ai\u002FBigModel.cn; compatible with Claude Code\u002FOpenClaw. GLM Coding Plan: update to \"GLM-5.1\" (1-3x quota, promo 1x off-peak); GUI via Z Code for multi-agent SSH\u002Fphone tasks. Z.ai chat rollout soon.",{"title":47,"searchDepth":48,"depth":48,"links":3691},[3692,3693,3694],{"id":3662,"depth":48,"text":3663},{"id":3675,"depth":48,"text":3676},{"id":3685,"depth":48,"text":3686},[88],{"content_references":3697,"triage":3717},[3698,3703,3707,3710,3715],{"type":3699,"title":3700,"url":3701,"context":3702},"other","VectorDBBench","https:\u002F\u002Fgithub.com\u002FKCORES\u002Fvector-db-bench","cited",{"type":3704,"title":3705,"url":3706,"context":3702},"paper","KernelBench","https:\u002F\u002Farxiv.org\u002Fabs\u002F2502.10517v1",{"type":3699,"title":3708,"url":3709,"context":3702},"Vending Bench 2","https:\u002F\u002Fandonlabs.com\u002Fevals\u002Fvending-bench-2",{"type":3711,"title":3712,"url":3713,"context":3714},"tool","GLM-5.1","https:\u002F\u002Fgithub.com\u002Fzai-org\u002FGLM-5","mentioned",{"type":3711,"title":3712,"url":3716,"context":3714},"https:\u002F\u002Fhuggingface.co\u002Fzai-org\u002FGLM-5.1",{"relevance":3718,"novelty":3719,"quality":3718,"actionability":48,"composite":3720,"reasoning":3721},4,3,3.4,"Category: AI & LLMs. The article discusses the performance of GLM-5.1 in coding and agentic benchmarks, which is relevant to AI engineering and software development. However, while it provides insights into the model's capabilities, it lacks concrete, actionable steps for developers looking to implement these findings in their own projects.","\u002Fsummaries\u002F5dc48731884521dd-glm-5-1-excels-in-long-horizon-agentic-coding-summary","2026-04-16 03:09:20",{"title":3652,"description":47},{"loc":3722},"5dc48731884521dd","__oneoff__","article","https:\u002F\u002Fz.ai\u002Fblog\u002Fglm-5.1","summaries\u002F5dc48731884521dd-glm-5-1-excels-in-long-horizon-agentic-coding-summary",[72,73,75],"GLM-5.1 tops SWE-Bench Pro at 58.4% and sustains gains over 600+ iterations on VectorDBBench (21.5k QPS, 6x prior best) and 1,000+ turns on KernelBench (3.6x speedup), enabling complex builds like a full Linux desktop in 8 hours.",[],"9o9PWiYh9qZfKw3Vzn915SRQ8On2LwxyJS9rRH8Td78",{"id":3736,"title":3737,"ai":3738,"body":3743,"categories":3776,"created_at":55,"date_modified":55,"description":47,"extension":57,"faq":55,"featured":58,"kicker_label":55,"meta":3777,"navigation":60,"path":3802,"published_at":55,"question":55,"scraped_at":3803,"seo":3804,"sitemap":3805,"source_id":3806,"source_name":3727,"source_type":3728,"source_url":3807,"stem":3808,"tags":3809,"thumbnail_url":55,"tldr":3810,"tweet":55,"unknown_tags":3811,"__hash__":3812},"summaries\u002Fsummaries\u002F68ffcf2c57450e50-claude-opus-4-1-reaches-74-5-on-swe-bench-for-supe-summary.md","Claude Opus 4.1 Reaches 74.5% on SWE-bench for Superior Coding",{"provider":7,"model":8,"input_tokens":3739,"output_tokens":3740,"processing_time_ms":3741,"cost_usd":3742},4521,1887,10018,0.00182505,{"type":14,"value":3744,"toc":3771},[3745,3749,3752,3756,3759,3763],[17,3746,3748],{"id":3747},"coding-gains-target-production-workflows","Coding Gains Target Production Workflows",[22,3750,3751],{},"Claude Opus 4.1 achieves 74.5% on SWE-bench Verified using only bash and file-editing tools—no planning tool—scoring across all 500 problems, outperforming prior models on multi-file refactoring. This setup equips the model for real codebase edits via string replacements, enabling precise fixes without unnecessary changes or bugs. Rakuten Group uses it for everyday debugging in large codebases, preferring its pinpoint accuracy. Windsurf's junior developer benchmark shows a one standard deviation leap over Opus 4, matching the Sonnet 3.7 to 4 jump, proving reliable junior-level code handling.",[17,3753,3755],{"id":3754},"agentic-tasks-and-research-boosted-by-extended-thinking","Agentic Tasks and Research Boosted by Extended Thinking",[22,3757,3758],{},"Opus 4.1 enhances detail tracking, in-depth research, and data analysis via agentic search. On TAU-bench (Airline\u002FRetail agents), scores improve with a prompt addendum encouraging explicit reasoning during extended thinking up to 64K tokens and 100 steps (most under 30). This leverages hybrid reasoning for multi-turn trajectories, separating thoughts from actions. Benchmarks like GPQA Diamond, MMMLU, MMMU, and AIME use extended thinking; SWE-bench and Terminal-Bench do not. GitHub reports broad gains over Opus 4, especially refactoring.",[17,3760,3762],{"id":3761},"immediate-upgrade-path-delivers-value","Immediate Upgrade Path Delivers Value",[22,3764,3765,3766,3770],{},"Switch to Opus 4.1 for all tasks via API model ",[3767,3768,3769],"code",{},"claude-opus-4-1-20250805",", Claude Code, Amazon Bedrock, or Vertex AI at Opus 4 pricing. Larger upgrades follow soon. Feedback drives iterations; check system card, model page, pricing, and docs for details. Hybrid reasoning maximizes scores, balancing tool use with chain-of-thought for complex problems.",{"title":47,"searchDepth":48,"depth":48,"links":3772},[3773,3774,3775],{"id":3747,"depth":48,"text":3748},{"id":3754,"depth":48,"text":3755},{"id":3761,"depth":48,"text":3762},[109],{"content_references":3778,"triage":3799},[3779,3783,3786,3790,3793,3796],{"type":3780,"title":3781,"url":3782,"context":3702},"dataset","SWE-bench Verified","https:\u002F\u002Fwww.swebench.com\u002F",{"type":3699,"title":3784,"url":3785,"context":3702},"o3 launch post","https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-o3-and-o4-mini\u002F",{"type":3787,"title":3788,"url":3789,"context":3702},"report","o3-and-o4-mini-system-card.pdf","https:\u002F\u002Fcdn.openai.com\u002Fpdf\u002F2221c875-02dc-4789-800b-e7758f3722c1\u002Fo3-and-o4-mini-system-card.pdf",{"type":3787,"title":3791,"url":3792,"context":3702},"2.5 Pro model card","https:\u002F\u002Fstorage.googleapis.com\u002Fmodel-cards\u002Fdocuments\u002Fgemini-2.5-pro.pdf",{"type":3699,"title":3794,"url":3795,"context":3702},"Sonnet 3.7 launch post","https:\u002F\u002Fwww.anthropic.com\u002Fnews\u002Fclaude-3-7-sonnet",{"type":3699,"title":3797,"url":3798,"context":3702},"Claude 4 launch post","https:\u002F\u002Fwww.anthropic.com\u002Fnews\u002Fclaude-4",{"relevance":3718,"novelty":3719,"quality":3718,"actionability":3719,"composite":3800,"reasoning":3801},3.6,"Category: AI & LLMs. The article discusses the capabilities of Claude Opus 4.1 in coding tasks, which is relevant to AI engineering and software development. It provides specific performance metrics and use cases, such as its application in debugging large codebases, which addresses practical concerns for developers. However, while it offers insights into the model's performance, it lacks detailed actionable steps for implementation.","\u002Fsummaries\u002F68ffcf2c57450e50-claude-opus-4-1-reaches-74-5-on-swe-bench-for-supe-summary","2026-04-16 03:07:34",{"title":3737,"description":47},{"loc":3802},"68ffcf2c57450e50","https:\u002F\u002Fwww.anthropic.com\u002Fnews\u002Fclaude-opus-4-1","summaries\u002F68ffcf2c57450e50-claude-opus-4-1-reaches-74-5-on-swe-bench-for-supe-summary",[72,73,75],"Claude Opus 4.1 upgrades agentic tasks, coding, and reasoning to 74.5% on SWE-bench Verified, with gains in multi-file refactoring and precise debugging; available now at same pricing.",[],"MhwMncz4IS_mgOHa_l1HYHmRbXKI5_VPHszvHw54SpI",{"id":3814,"title":3815,"ai":3816,"body":3821,"categories":3857,"created_at":55,"date_modified":55,"description":47,"extension":57,"faq":55,"featured":58,"kicker_label":55,"meta":3858,"navigation":60,"path":3864,"published_at":55,"question":55,"scraped_at":3865,"seo":3866,"sitemap":3867,"source_id":3868,"source_name":3869,"source_type":3728,"source_url":3870,"stem":3871,"tags":3872,"thumbnail_url":55,"tldr":3873,"tweet":55,"unknown_tags":3874,"__hash__":3875},"summaries\u002Fsummaries\u002F6ff41910e72e599f-5-llm-pitfalls-engineers-hit-building-agents-summary.md","5 LLM Pitfalls Engineers Hit Building Agents",{"provider":7,"model":8,"input_tokens":3817,"output_tokens":3818,"processing_time_ms":3819,"cost_usd":3820},9923,1337,7742,0.00263045,{"type":14,"value":3822,"toc":3851},[3823,3827,3830,3834,3837,3841,3844,3848],[17,3824,3826],{"id":3825},"budget-context-windows-like-ram-to-avoid-gradual-degradation","Budget Context Windows Like RAM to Avoid Gradual Degradation",[22,3828,3829],{},"Context windows are bounded buffers holding system prompts, conversation history, tool outputs, prior responses, and retrieval chunks—not just documents. Exceeding them truncates silently without errors, making agents lose access to key info. A coding agent reading three medium files plus tool responses burns 30-50K tokens before real work, even on 200K models. Design agents to fetch on-demand rather than stuffing everything in: prioritize what the model needs now. This scales demos to production; ignoring it causes toy-task success but real-work failure.",[17,3831,3833],{"id":3832},"tokenize-workloads-precisely-for-cost-and-limits","Tokenize Workloads Precisely for Cost and Limits",[22,3835,3836],{},"Tokens are sub-word fragments from the model's tokenizer, not words\u002Fcharacters. Code eats tokens fast—brackets, underscores, indentation, identifiers push a 200-line Python file to ~3K tokens, not 2K. Non-English (Japanese, Arabic, Hindi) uses 2-4x more tokens than English for same meaning, breaking English-based estimates. JSON\u002FXML schemas add overhead vs. prose. Always run representative samples through the exact tokenizer pre-launch: word-count guesses underestimate costs severely.",[17,3838,3840],{"id":3839},"tune-temperature-for-reproducibility-ground-hallucinations-systematically","Tune Temperature for Reproducibility, Ground Hallucinations Systematically",[22,3842,3843],{},"Temperature controls low-probability token sampling, trading reproducibility for variety—use 0 for tool-calling, extraction, classification, spec'd code gen where correctness trumps creativity. Higher suits diverse generation (variants, brainstorming) but invites irreproducible bugs. Even temperature=0 isn't fully deterministic due to API routing\u002Fbatching; true control needs seeded inference. View hallucinations as pattern continuation from training data, not recall errors: counter with retrieval grounding, output schemas\u002Ffunction calls, and post-generation validation (critical for actions). In coding agents, models invent APIs confidently—prompting\u002Ffeedback loops fail; validate rigorously.",[17,3845,3847],{"id":3846},"engineer-rag-retrieval-not-just-the-llm","Engineer RAG Retrieval, Not Just the LLM",[22,3849,3850],{},"RAG indexes data, retrieves chunks at query time for context. The LLM is easy; retrieval decides success—tune chunking, embeddings, hybrid search, reranking, query rewriting. Diagnose with recall@10 on held-out eval sets: poor retrieval, not the model, causes most failures. Teams blame LLMs without measuring this.",{"title":47,"searchDepth":48,"depth":48,"links":3852},[3853,3854,3855,3856],{"id":3825,"depth":48,"text":3826},{"id":3832,"depth":48,"text":3833},{"id":3839,"depth":48,"text":3840},{"id":3846,"depth":48,"text":3847},[],{"content_references":3859,"triage":3860},[],{"relevance":3861,"novelty":3718,"quality":3718,"actionability":3718,"composite":3862,"reasoning":3863},5,4.35,"Category: AI & LLMs. The article directly addresses common pitfalls engineers face when building AI agents, providing practical insights on managing context windows and tokenization, which are critical for production-ready AI features. It offers actionable advice on tuning parameters and validating outputs, making it highly relevant for developers looking to implement LLMs effectively.","\u002Fsummaries\u002F6ff41910e72e599f-5-llm-pitfalls-engineers-hit-building-agents-summary","2026-04-19 01:22:12",{"title":3815,"description":47},{"loc":3864},"6ff41910e72e599f","Generative AI","https:\u002F\u002Fgenerativeai.pub\u002Ffive-llm-concepts-i-keep-explaining-to-engineers-shipping-their-first-agents-87c502f3c378?source=rss----440100e76000---4","summaries\u002F6ff41910e72e599f-5-llm-pitfalls-engineers-hit-building-agents-summary",[72,73,75],"Context windows act like RAM—budget system prompts, history, tools, and retrieval tightly or agents degrade silently. Tokenize code\u002Fnon-English workloads early; set temperature=0 for reproducibility; ground hallucinations with RAG\u002Fschemas\u002Fvalidation; measure RAG recall@10.",[],"VfRNIenBuwdRZlBDaBdU7mmrUrZCRezKKYwx6VA-caQ",{"id":3877,"title":3878,"ai":3879,"body":3884,"categories":4113,"created_at":55,"date_modified":55,"description":47,"extension":57,"faq":55,"featured":58,"kicker_label":55,"meta":4114,"navigation":60,"path":4132,"published_at":4133,"question":55,"scraped_at":4134,"seo":4135,"sitemap":4136,"source_id":4137,"source_name":4127,"source_type":3728,"source_url":4138,"stem":4139,"tags":4140,"thumbnail_url":55,"tldr":4142,"tweet":4143,"unknown_tags":4144,"__hash__":4145},"summaries\u002Fsummaries\u002F797d07e1b185b527-use-claude-code-codex-together-for-best-ai-coding-summary.md","Use Claude Code + Codex Together for Best AI Coding",{"provider":7,"model":8,"input_tokens":3880,"output_tokens":3881,"processing_time_ms":3882,"cost_usd":3883},8504,2410,42143,0.0028833,{"type":14,"value":3885,"toc":4105},[3886,3890,3893,3896,3899,3903,3910,3913,3966,3969,3973,3976,4009,4012,4015,4019,4022,4028,4034,4040,4050,4053,4056,4060,4063,4066,4069,4072,4076],[17,3887,3889],{"id":3888},"ditch-tool-tribalism-leverage-both-claude-code-and-codex","Ditch Tool Tribalism: Leverage Both Claude Code and Codex",[22,3891,3892],{},"Claude Code dominated AI coding discussions due to its lead over alternatives, but Codex (powered by GPT-5.5 or 5.5 Pro) has closed the gap with generous usage limits, cost efficiency, and a polished desktop app. The speaker argues against choosing one: \"you are hamstringing yourself if you are trying to choose between claude code or codeex.\" Instead, use both for complementary strengths—Claude's depth pairs with Codex's speed and quotas. Key principle: Tool agnosticism prevents vendor lock-in; companies deserve no loyalty. Overlap in interfaces (99% Venn diagram) makes mastery easy—learn one, adapt to the other instantly.",[22,3894,3895],{},"Pricing favors OpenAI for most: GPT-5.5 matches or beats Opus token efficiency despite similar per-million costs, with Pro plans ($100-200\u002Fmo) unlocking superior models that outperform Mythos in benchmarks. Start cheap ($20\u002Fmo) to test. Anthropic's doubled 5-hour limits still lag weekly caps. Quote: \"big picture you get more with OpenAI.\"",[22,3897,3898],{},"Common mistake: Pigeonholing into one ecosystem, losing access during outages or limits. Solution: Dual setup takes seconds, yields second opinions on plans\u002Fcode, reducing blind spots—vital for non-technical users who can't vet AI outputs alone.",[17,3900,3902],{"id":3901},"quick-codex-desktop-app-setup-for-dual-workflow","Quick Codex Desktop App Setup for Dual Workflow",[22,3904,3905,3906,3909],{},"Download from openai.com\u002Fcodex (2-second install). UI mirrors ChatGPT: prompt window, file uploads, plan mode toggle, permissions (bypass\u002Fauto\u002Ffull access), intelligence levels, model selector. Projects show current folder\u002Fbranch (local\u002Fcloud\u002Fwork trees). Open terminal inside app, run ",[3767,3907,3908],{},"claude","—now both agents share the directory.",[22,3911,3912],{},"Key settings:",[3914,3915,3916,3924,3930,3936,3942,3948,3954,3960],"ul",{},[3917,3918,3919,3923],"li",{},[3920,3921,3922],"strong",{},"Work mode",": Coding for technical detail.",[3917,3925,3926,3929],{},[3920,3927,3928],{},"Permissions",": Enable full access.",[3917,3931,3932,3935],{},[3920,3933,3934],{},"Follow-up",": Q (query) mode initially.",[3917,3937,3938,3941],{},[3920,3939,3940],{},"Pets",": Visual\u002Fstatus indicator (overlay shows activity\u002Ftext stream)—prevents task abandonment. Quote: \"I probably lose more time with a genting from just like not getting back to the task after I tell it to do something.\"",[3917,3943,3944,3947],{},[3920,3945,3946],{},"Configuration",": Enable Codex dependencies, approval policies, sandbox.",[3917,3949,3950,3953],{},[3920,3951,3952],{},"Personalization",": agents.mmd (Codex's claude.md equivalent), memory (disable if distracting).",[3917,3955,3956,3959],{},[3920,3957,3958],{},"Plugins\u002FSkills",": One-click installs (Supabase MCP, Chrome, spreadsheets); auto-imports from Claude Code\u002FOpen Code. Slash (@\u002Ffile) commands invoke them.",[3917,3961,3962,3965],{},[3920,3963,3964],{},"Automations",": Visual editor or natural language creation, like Claude routines.",[22,3967,3968],{},"Navigation: Chats per project (fork\u002Fcopy\u002Fpin\u002Frename); in-app browser\u002Fdiff viewer\u002Freadme previews beat terminal alone. Context: 258K window (auto-compacts); mitigate by new chats (equivalent to \u002Fclear). Pro: Snappier chat, slower tool calls vs. Opus.",[17,3970,3972],{"id":3971},"tandem-workflow-plan-review-build-across-agents","Tandem Workflow: Plan, Review, Build Across Agents",[22,3974,3975],{},"Process for any project:",[3977,3978,3979,3985,3991,3997,4003],"ol",{},[3917,3980,3981,3984],{},[3920,3982,3983],{},"Plan in one",": Toggle plan mode; it probes with questions (5.5 Pro asks more on extra-high effort).",[3917,3986,3987,3990],{},[3920,3988,3989],{},"Cross-review",": Copy plan to second agent for critiques\u002Fgaps. E.g., Claude flags Codex's missing trend ranking\u002Fcompetitor checks.",[3917,3992,3993,3996],{},[3920,3994,3995],{},"Iterate",": Paste feedback back—refines without endless loops.",[3917,3998,3999,4002],{},[3920,4000,4001],{},"Execute",": Build, verify files\u002Fdiffs, spin dev server (in-app browser auto-opens).",[3917,4004,4005,4008],{},[3920,4006,4007],{},"Second review",": Have other agent inspect code\u002FUI for issues (e.g., Claude spots Llama integration bug).",[22,4010,4011],{},"Dependencies: Existing folder\u002Fproject; import Claude settings. Voice\u002Fslash commands reduce typing. Fits broader workflow post-prompt engineering: Use for ideation-to-production, especially non-devs needing validation.",[22,4013,4014],{},"Assumed level: Claude Code users (beginner-to-experienced); no deep tech prereqs—UI intuitive. Quote: \"if you learn how to use one of these you can very easily learn how to use the other.\"",[17,4016,4018],{"id":4017},"demo-building-ai-trend-planner-web-app","Demo: Building AI Trend Planner Web App",[22,4020,4021],{},"Task: Single-page Next.js\u002FTS\u002FSQL app—scan 24h AI news (RSS\u002FYouTube\u002FTwitter), report + content ideas (titles\u002Foutlines\u002Fhooks), mini Kanban scheduler.",[22,4023,4024,4027],{},[3920,4025,4026],{},"Codex Plan (Plan Mode)",": Green-field local app; RSS\u002Flocal gen (no paid APIs); dashboard for scan\u002Freport\u002Fideas\u002Fschedule. Time: Detailed questions, ~vibes slower on tools.",[22,4029,4030,4033],{},[3920,4031,4032],{},"Claude Review",": \"the plan solid but has some gaps... needs trend signals ranking and competitor saturation checks.\" Addresses non-technical pitfall: Blind AI plans.",[22,4035,4036,4039],{},[3920,4037,4038],{},"Codex Update",": Incorporates—adds ranking\u002Fsaturation. Executes (23min): Full app, README, files verified. Brutalist UI: Scan button fetches sources, generates ideas, drag? Kanban (non-drag initially).",[22,4041,4042,4045,4046,4049],{},[3920,4043,4044],{},"Run\u002FReview",": ",[3767,4047,4048],{},"spin up the dev server... open in sidebar browser",". Claude inspects: Spots Llama issues, praises structure. Annotate UI in-app for fixes.",[22,4051,4052],{},"Before: Solo agent risks oversights. After: Dual eyes = robust app faster. Quality criteria: Multiple AI validations, working dev server, README diffs.",[22,4054,4055],{},"Practice: Replicate on your machine; bounce plans on simple apps (todo list → full CRUD).",[17,4057,4059],{"id":4058},"stay-tool-agnostic-for-long-term-wins","Stay Tool Agnostic for Long-Term Wins",[22,4061,4062],{},"Ecosystems evolve—Codex CLI exists but desktop + terminal wins for QoL (browser\u002Fpets). Plugins auto-migrate skills. Apply dual approach anywhere: Planning, debugging, ideation. Avoids context bloat, quota exhaustion. Future-proof: Swap agents as models improve.",[22,4064,4065],{},"Quote: \"the best play isn't to sit here and try to choose which one of these two good options is better the best play is to use both.\"",[22,4067,4068],{},"Quote: \"multiple AI experts are telling me it's a solid plan.\"",[22,4070,4071],{},"Quote: \"the infrastructure is here really easy to do we have the best of both worlds.\"",[17,4073,4075],{"id":4074},"key-takeaways","Key Takeaways",[3914,4077,4078,4084,4087,4090,4093,4096,4099,4102],{},[3917,4079,4080,4081,4083],{},"Install Codex desktop app, open terminal, run ",[3767,4082,3908],{},"—instant dual setup in shared directory.",[3917,4085,4086],{},"Always cross-review plans\u002Fcode between agents to catch gaps like missing trend analysis.",[3917,4088,4089],{},"Use plan mode + feedback loops for non-devs; validates without expertise.",[3917,4091,4092],{},"Enable pets\u002Fnotifications to avoid forgetting tasks post-AI handoff.",[3917,4094,4095],{},"Start Codex on $20\u002Fmo plan; upgrade if hooked—better quotas than Anthropic Max.",[3917,4097,4098],{},"Auto-import skills\u002Fplugins from Claude; 99% UI overlap speeds learning.",[3917,4100,4101],{},"New chats manage 258K context; in-app browser\u002Fdiffs boost DX over terminal-only.",[3917,4103,4104],{},"Practice: Build iteratively—plan in Codex, critique in Claude, execute\u002Freview vice versa.",{"title":47,"searchDepth":48,"depth":48,"links":4106},[4107,4108,4109,4110,4111,4112],{"id":3888,"depth":48,"text":3889},{"id":3901,"depth":48,"text":3902},{"id":3971,"depth":48,"text":3972},{"id":4017,"depth":48,"text":4018},{"id":4058,"depth":48,"text":4059},{"id":4074,"depth":48,"text":4075},[88],{"content_references":4115,"triage":4129},[4116,4120,4123,4126],{"type":3711,"title":4117,"url":4118,"context":4119},"Codex Desktop App","https:\u002F\u002Fopenai.com\u002Fcodex","recommended",{"type":3699,"title":4121,"url":4122,"context":4119},"Master Claude Code & Codex","https:\u002F\u002Fwww.skool.com\u002Fchase-ai",{"type":3699,"title":4124,"url":4125,"context":4119},"Chase AI Community","https:\u002F\u002Fwww.skool.com\u002Fchase-ai-community",{"type":3711,"title":4127,"url":4128,"context":3714},"Chase AI","https:\u002F\u002Fchaseai.io",{"relevance":3861,"novelty":3718,"quality":3718,"actionability":3861,"composite":4130,"reasoning":4131},4.55,"Category: AI & LLMs. The article provides a practical guide on using Claude Code and Codex together, addressing the pain point of tool tribalism by offering a dual-agent coding strategy. It includes specific setup instructions and key settings, making it immediately actionable for developers looking to enhance their coding workflow.","\u002Fsummaries\u002F797d07e1b185b527-use-claude-code-codex-together-for-best-ai-coding-summary","2026-05-08 01:21:59","2026-05-08 11:23:33",{"title":3878,"description":47},{"loc":4132},"b68bb351621ffb08","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=VdxUKiF8CWI","summaries\u002F797d07e1b185b527-use-claude-code-codex-together-for-best-ai-coding-summary",[4141,75,73,72],"ai-tools","Reject AI tool tribalism: Run Claude Code inside Codex's desktop app terminal for seamless dual-agent coding—plan in one, review\u002Fbuild in the other, leveraging both models' strengths without loyalty to any vendor.","Walkthrough of the Codex desktop app (OpenAI's coding tool), covering setup, UI, pricing, settings, plugins\u002Fskills, and a demo running Claude Code in its built-in terminal to use both together; includes pitches for the creator's paid masterclass and free community.",[],"2u9PVfXbHPFzUBpM9LNrBCg-F-8S73PG4bK5k5TcAMg"]