[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-25544e9965dc4dae-gpu-orchestrated-multi-agent-sustainability-intell-summary":3,"summaries-facets-categories":226,"summary-related-25544e9965dc4dae-gpu-orchestrated-multi-agent-sustainability-intell-summary":3795},{"id":4,"title":5,"ai":6,"body":13,"categories":173,"created_at":175,"date_modified":175,"description":165,"extension":176,"faq":175,"featured":177,"kicker_label":175,"meta":178,"navigation":205,"path":206,"published_at":207,"question":175,"scraped_at":208,"seo":209,"sitemap":210,"source_id":211,"source_name":212,"source_type":213,"source_url":214,"stem":215,"tags":216,"thumbnail_url":221,"tldr":222,"tweet":223,"unknown_tags":224,"__hash__":225},"summaries\u002Fsummaries\u002F25544e9965dc4dae-gpu-orchestrated-multi-agent-sustainability-intell-summary.md","GPU-Orchestrated Multi-Agent Sustainability Intelligence Blueprint",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",9206,2577,37454,0.0031072,{"type":14,"value":15,"toc":164},"minimark",[16,21,25,28,31,35,38,41,44,47,51,54,77,80,83,86,90,93,96,122,125,128,132],[17,18,20],"h2",{"id":19},"agentic-workloads-demand-elastic-secure-infrastructure","Agentic Workloads Demand Elastic, Secure Infrastructure",[22,23,24],"p",{},"Chelsie Czop emphasizes that AI agents optimize for outcomes over outputs, enabling cross-platform automation, asynchronous productivity, and real-world transactions. An agent is \"a service that autonomously reasons to solve a task using tools and data,\" but must meet compliance, CI\u002FCD, security, cost, and performance standards like latency SLOs.",[22,26,27],{},"Agents stress infrastructure with bursty traffic, latency sensitivity, long-running tasks, idle cycles, and memory hunger. Three core challenges emerge: (1) latency and throughput amid constrained accelerators; (2) compute efficiency to boost density and cut idle resources; (3) security and governance for debugging, auditing, and controlling complex tasks.",[22,29,30],{},"\"Your agentic workloads need to be treated as untrusted,\" Czop warns. They require scaling for elasticity while securing against breaches. Google Cloud's AI Hypercomputer addresses this via purpose-built hardware (NVIDIA GPUs from Hopper to Blackwell), open software, and flexible models.",[17,32,34],{"id":33},"g4-gpus-and-cloud-run-unlock-serverless-agentic-inference","G4 GPUs and Cloud Run Unlock Serverless Agentic Inference",[22,36,37],{},"Czop spotlights G4 instances powered by NVIDIA RTX PRO 6000 Blackwell GPUs: 7x more performant than prior L4s, 4x GPU memory, 3x host memory. Optimized for peer-to-peer multi-GPU workloads, they deliver 2x NVLink collective performance on full VMs (up to 8 GPUs) via a simple environment flag.",[22,39,40],{},"Cloud Run GPU integrates this stack serverlessly for real-time multimodal inference, fine-tuning, or batch jobs. Design patterns include: on-demand inference (Cloud CDN → Cloud Run GPU with Gemma 4 weights from Cloud Storage over VPC); batch fine-tuning (async LoRA\u002FPEFT on domain data). Pros: background execution without management. Fine-tune Gemma for domain knowledge (e.g., SEC filings for finance), task behaviors (customer service), or personas (NPC styles).",[22,42,43],{},"Production win: Flipkart uses G4 for AI-led catalog enrichment, generating videos from images via agents. P2P communication yielded 50% latency and cost reductions versus PCIe.",[22,45,46],{},"Mitesh Patel reinforces: \"Latency is very important, and throughput is very important. And cost effectiveness is also important because when you're scaling the systems out at production level, cost is the primary factor.\"",[17,48,50],{"id":49},"multi-agent-architecture-for-multimodal-sustainability-analysis","Multi-Agent Architecture for Multimodal Sustainability Analysis",[22,52,53],{},"Patel demos a sustainability intelligence app orchestrating specialist agents for urban heat risk: satellite imagery (Phoenix urban heat island dataset), live telemetry, and policy PDFs. Main orchestrator (Google ADK) delegates to three sub-agents:",[55,56,57,65,71],"ul",{},[58,59,60,64],"li",{},[61,62,63],"strong",{},"Satellite Agent",": Analyzes baseline vs. current heat maps.",[58,66,67,70],{},[61,68,69],{},"Telemetry Agent",": Processes weather station data.",[58,72,73,76],{},[61,74,75],{},"Policy Agent",": Retrieves relevant embeddings from Milvus vector DB (pre-embedded via Gemma 3B gn-fp4).",[22,78,79],{},"Inference uses quantized Gemma 4 (31B params, gn-fp4) on VLM engine (swappable with SGLang or NVIDIA Dynamo), served on Cloud Run GPUs. ADK streamlines plugging agents, retrieval (Milvus), and future MCP servers.",[22,81,82],{},"Demo flow: User query triggers task dispatch; agents process modalities in parallel; orchestrator synthesizes into executive summary and mitigation strategies (e.g., cooling tactics). \"The main orchestrator will combine all this information... and generate a report for you,\" Patel explains.",[22,84,85],{},"This blueprint generalizes to any multimodal app: ADK handles orchestration, GPUs accelerate inference, Milvus enables RAG. Avoid coding from scratch—toolkits slash time-to-market.",[17,87,89],{"id":88},"production-insights-avoiding-loops-transitioning-to-autonomy-and-security","Production Insights: Avoiding Loops, Transitioning to Autonomy, and Security",[22,91,92],{},"Agents shine in real-time voice, encoding, and research (e.g., code base analysis via chain-of-thought). Fine-tuning boosts productivity, per Base10 insights.",[22,94,95],{},"Q&A highlights:",[55,97,98,104,110,116],{},[58,99,100,103],{},[61,101,102],{},"Loop Prevention",": Strong orchestration (like ADK) and tools break cycles.",[58,105,106,109],{},[61,107,108],{},"Human-to-Agent Transition",": When tasks are structured, reliable, and low-risk.",[58,111,112,115],{},[61,113,114],{},"Policy Retrieval Challenges",": Accurate RAG via embeddings\u002FMilvus; multimodal grounding.",[58,117,118,121],{},[61,119,120],{},"Security\u002FPrivacy",": VPCs, guardrails, auditability in Cloud Run.",[22,123,124],{},"Patel shares: Used agents for similar multimodal orchestration. Czop notes a friend's MVP failed on unoptimized agent demands, forcing re-architecture for cost\u002Flatency.",[22,126,127],{},"\"If you try to code it yourself, it's not impossible. But your time to market will just be way longer. And that is where these orchestration toolkits becomes very easy to use.\"",[17,129,131],{"id":130},"key-takeaways","Key Takeaways",[55,133,134,137,140,143,146,149,152,155,158,161],{},[58,135,136],{},"Treat agents as untrusted: Build with security, elasticity, and governance from day one.",[58,138,139],{},"Use Cloud Run GPUs for serverless inference\u002Ffine-tuning: Pull Gemma weights via VPC, scale elastically.",[58,141,142],{},"Orchestrate multi-agents with Google ADK: Delegate modalities to specialists, integrate Milvus RAG.",[58,144,145],{},"Quantize models (gn-fp4) on RTX PRO 6000 for 50%+ latency\u002Fcost wins, as in Flipkart's video gen.",[58,147,148],{},"Fine-tune for domains\u002Fpersonas via PEFT\u002FLoRA: Efficient on smaller datasets.",[58,150,151],{},"Pre-embed policies offline; runtime retrieval via vector DBs.",[58,153,154],{},"Start with multimodal demos like sustainability: Satellite + telemetry + docs → actionable reports.",[58,156,157],{},"Enable P2P multi-GPU with one flag for 2x NVLink gains.",[58,159,160],{},"Monitor KPIs: Latency, throughput, cost drive production scaling.",[58,162,163],{},"Get started: Join Google Cloud & NVIDIA community for blueprints.",{"title":165,"searchDepth":166,"depth":166,"links":167},"",2,[168,169,170,171,172],{"id":19,"depth":166,"text":20},{"id":33,"depth":166,"text":34},{"id":49,"depth":166,"text":50},{"id":88,"depth":166,"text":89},{"id":130,"depth":166,"text":131},[174],"AI & LLMs",null,"md",false,{"content_references":179,"triage":200},[180,184,186,188,190,192,195],{"type":181,"title":182,"context":183},"tool","Google Agent Development Kit (ADK)","mentioned",{"type":181,"title":185,"context":183},"Gemma 4",{"type":181,"title":187,"context":183},"Cloud Run",{"type":181,"title":189,"context":183},"Milvus",{"type":181,"title":191,"context":183},"NVIDIA RTX PRO 6000 GPUs",{"type":193,"title":194,"context":183},"dataset","Phoenix urban heat island risk dataset",{"type":196,"title":197,"url":198,"context":199},"other","Google Cloud & NVIDIA community","https:\u002F\u002Fgoo.gle\u002Fgoogle-nvidia-programs","recommended",{"relevance":201,"novelty":202,"quality":202,"actionability":202,"composite":203,"reasoning":204},5,4,4.35,"Category: AI Automation. The article provides a detailed exploration of using AI agents in a serverless architecture, addressing specific challenges and solutions relevant to product builders. It includes practical examples, such as Flipkart's use of G4 GPUs for AI-led catalog enrichment, which demonstrates real-world application.",true,"\u002Fsummaries\u002F25544e9965dc4dae-gpu-orchestrated-multi-agent-sustainability-intell-summary","2026-05-12 17:00:50","2026-05-13 12:00:34",{"title":5,"description":165},{"loc":206},"25544e9965dc4dae","Google Cloud Tech","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=vIyhQGBkn34","summaries\u002F25544e9965dc4dae-gpu-orchestrated-multi-agent-sustainability-intell-summary",[217,218,219,220],"agents","llm","cloud","ai-automation","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FvIyhQGBkn34\u002Fhqdefault.jpg","Chelsie Czop and Mitesh Patel demo a serverless multi-agent app using Google ADK, Gemma 4 on NVIDIA RTX PRO 6000 GPUs via Cloud Run, and Milvus RAG for real-time environmental risk reports from satellite, telemetry, and policy data.","Livestream talk by Google Cloud PM Chelsie Czop and NVIDIA's Jay Rodge demoing a multi-agent sustainability app orchestrated with Agent Development Kit, running Gemma 4 on Cloud Run with RTX PRO 6000 GPUs, and using Milvus for policy retrieval, followed by audience Q&A on agent challenges.",[220],"-kVMzSLa9FYK5ixBk7a96OVeuA3rRBdX79ixI_1snjQ",[227,230,233,235,238,241,243,245,247,249,251,253,256,258,260,262,264,266,268,270,272,274,277,280,282,284,287,289,291,294,296,298,300,302,304,306,308,310,312,314,316,318,320,322,324,326,328,330,332,334,336,338,340,342,344,346,348,350,352,354,356,358,360,362,364,366,368,370,372,374,376,378,380,382,384,386,388,390,392,394,396,398,400,402,404,406,408,410,412,414,416,418,420,422,424,426,428,430,432,434,436,438,440,442,444,446,448,450,452,454,456,458,460,462,464,466,468,470,472,474,476,478,480,482,484,486,488,490,492,494,496,498,500,502,504,506,508,510,512,514,516,518,520,522,524,526,528,530,532,534,536,538,540,542,544,546,549,551,553,555,557,559,561,563,565,567,569,571,573,575,577,579,581,583,585,587,589,591,593,595,597,599,601,603,605,607,609,611,613,615,617,619,621,623,625,627,629,631,633,635,637,639,641,643,645,647,649,651,653,655,657,659,661,663,665,667,669,671,673,675,677,679,681,683,685,687,689,691,693,695,697,699,701,703,705,707,709,711,713,715,717,719,721,723,725,727,729,731,733,735,737,739,741,743,745,747,749,751,753,755,757,759,761,763,765,767,769,771,773,775,777,779,781,783,785,787,789,791,793,795,797,799,801,803,805,807,809,811,813,815,817,819,821,823,825,827,829,831,833,835,837,839,841,843,845,847,849,851,853,855,857,859,861,863,865,867,869,871,873,875,877,879,881,883,885,887,889,891,893,895,897,899,901,903,905,907,909,911,913,915,917,919,921,923,925,927,929,931,933,935,937,939,941,943,945,947,949,951,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1137,1139,1141,1143,1145,1147,1149,1151,1153,1155,1157,1159,1161,1163,1165,1167,1169,1171,1173,1175,1177,1179,1181,1183,1185,1187,1189,1191,1193,1195,1197,1199,1201,1203,1205,1207,1209,1211,1213,1215,1217,1219,1221,1223,1225,1227,1229,1231,1233,1235,1237,1239,1241,1243,1245,1247,1249,1251,1253,1255,1257,1259,1261,1263,1265,1267,1269,1271,1273,1275,1277,1279,1281,1283,1285,1287,1289,1291,1293,1295,1297,1299,1301,1303,1305,1307,1309,1311,1313,1315,1317,1319,1321,1323,1325,1327,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1431,1433,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1461,1463,1465,1467,1469,1471,1473,1475,1477,1479,1481,1483,1485,1487,1489,1491,1493,1495,1497,1499,1501,1503,1505,1507,1509,1511,1513,1515,1517,1519,1521,1523,1525,1527,1529,1531,1533,1535,1537,1539,1541,1543,1545,1547,1549,1551,1553,1555,1557,1559,1561,1563,1565,1567,1569,1571,1573,1575,1577,1579,1581,1583,1585,1587,1589,1591,1593,1595,1597,1599,1601,1603,1605,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1667,1669,1671,1673,1675,1677,1679,1681,1683,1685,1687,1689,1691,1693,1695,1697,1699,1701,1703,1705,1707,1709,1711,1713,1715,1717,1719,1721,1723,1725,1727,1729,1731,1733,1735,1737,1739,1741,1743,1745,1747,1749,1751,1753,1755,1757,1759,1761,1763,1765,1767,1769,1771,1773,1775,1777,1779,1781,1783,1785,1787,1789,1791,1793,1795,1797,1799,1801,1803,1805,1807,1809,1811,1813,1815,1817,1819,1821,1823,1825,1827,1829,1831,1833,1835,1837,1839,1841,1843,1845,1847,1849,1851,1853,1855,1857,1859,1861,1863,1865,1867,1869,1871,1873,1875,1877,1879,1881,1883,1885,1887,1889,1891,1893,1895,1897,1899,1901,1903,1905,1907,1909,1911,1913,1915,1917,1919,1921,1923,1925,1927,1929,1931,1933,1935,1937,1939,1941,1943,1945,1947,1949,1951,1953,1955,1957,1959,1961,1963,1965,1967,1969,1971,1973,1975,1977,1979,1981,1983,1985,1987,1989,1991,1993,1995,1997,1999,2001,2003,2005,2007,2009,2011,2013,2015,2017,2019,2021,2023,2025,2027,2029,2031,2033,2035,2037,2039,2041,2043,2045,2047,2049,2051,2053,2055,2057,2059,2061,2063,2065,2067,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2151,2153,2155,2157,2159,2161,2163,2165,2167,2169,2171,2173,2175,2177,2179,2181,2183,2185,2187,2189,2191,2193,2195,2197,2199,2201,2203,2205,2207,2209,2211,2213,2215,2217,2219,2221,2223,2225,2227,2229,2231,2233,2235,2237,2239,2241,2243,2245,2247,2249,2251,2253,2255,2257,2259,2261,2263,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2305,2307,2309,2311,2313,2315,2317,2319,2321,2323,2325,2327,2329,2331,2333,2335,2337,2339,2341,2343,2345,2347,2349,2351,2353,2355,2357,2359,2361,2363,2365,2367,2369,2371,2373,2375,2377,2379,2381,2383,2385,2387,2389,2391,2393,2395,2397,2399,2401,2403,2405,2407,2409,2411,2413,2415,2417,2419,2421,2423,2425,2427,2429,2431,2433,2435,2437,2439,2441,2443,2445,2447,2449,2451,2453,2455,2457,2459,2461,2463,2465,2467,2469,2471,2473,2475,2477,2479,2481,2483,2485,2487,2489,2491,2493,2495,2497,2499,2501,2503,2505,2507,2509,2511,2513,2515,2517,2519,2521,2523,2525,2527,2529,2531,2533,2535,2537,2539,2541,2543,2545,2547,2549,2551,2553,2555,2557,2559,2561,2563,2565,2567,2569,2571,2573,2575,2577,2579,2581,2583,2585,2587,2589,2591,2593,2595,2597,2599,2601,2603,2605,2607,2609,2611,2613,2615,2617,2619,2621,2623,2625,2627,2629,2631,2633,2635,2637,2639,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677,2679,2681,2683,2685,2687,2689,2691,2693,2695,2697,2699,2701,2703,2705,2707,2709,2711,2713,2715,2717,2719,2721,2723,2725,2727,2729,2731,2733,2735,2737,2739,2741,2743,2745,2747,2749,2751,2753,2755,2757,2759,2761,2763,2765,2767,2769,2771,2773,2775,2777,2779,2781,2783,2785,2787,2789,2791,2793,2795,2797,2799,2801,2803,2805,2807,2809,2811,2813,2815,2817,2819,2821,2823,2825,2827,2829,2831,2833,2835,2837,2839,2841,2843,2845,2847,2849,2851,2853,2855,2857,2859,2861,2863,2865,2867,2869,2871,2873,2875,2877,2879,2881,2883,2885,2887,2889,2891,2893,2895,2897,2899,2901,2903,2905,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3021,3023,3025,3027,3029,3031,3033,3035,3037,3039,3041,3043,3045,3047,3049,3051,3053,3055,3057,3059,3061,3063,3065,3067,3069,3071,3073,3075,3077,3079,3081,3083,3085,3087,3089,3091,3093,3095,3097,3099,3101,3103,3105,3107,3109,3111,3113,3115,3117,3119,3121,3123,3125,3127,3129,3131,3133,3135,3137,3139,3141,3143,3145,3147,3149,3151,3153,3155,3157,3159,3161,3163,3165,3167,3169,3171,3173,3175,3177,3179,3181,3183,3185,3187,3189,3191,3193,3195,3197,3199,3201,3203,3205,3207,3209,3211,3213,3215,3217,3219,3221,3223,3225,3227,3229,3231,3233,3235,3237,3239,3241,3243,3245,3247,3249,3251,3253,3255,3257,3259,3261,3263,3265,3267,3269,3271,3273,3275,3277,3279,3281,3283,3285,3287,3289,3291,3293,3295,3297,3299,3301,3303,3305,3307,3309,3311,3313,3315,3317,3319,3321,3323,3325,3327,3329,3331,3333,3335,3337,3339,3341,3343,3345,3347,3349,3351,3353,3355,3357,3359,3361,3363,3365,3367,3369,3371,3373,3375,3377,3379,3381,3383,3385,3387,3389,3391,3393,3395,3397,3399,3401,3403,3405,3407,3409,3411,3413,3415,3417,3419,3421,3423,3425,3427,3429,3431,3433,3435,3437,3439,3441,3443,3445,3447,3449,3451,3453,3455,3457,3459,3461,3463,3465,3467,3469,3471,3473,3475,3477,3479,3481,3483,3485,3487,3489,3491,3493,3495,3497,3499,3501,3503,3505,3507,3509,3511,3513,3515,3517,3519,3521,3523,3525,3527,3529,3531,3533,3535,3537,3539,3541,3543,3545,3547,3549,3551,3553,3555,3557,3559,3561,3563,3565,3567,3569,3571,3573,3575,3577,3579,3581,3583,3585,3587,3589,3591,3593,3595,3597,3599,3601,3603,3605,3607,3609,3611,3613,3615,3617,3619,3621,3623,3625,3627,3629,3631,3633,3635,3637,3639,3641,3643,3645,3647,3649,3651,3653,3655,3657,3659,3661,3663,3665,3667,3669,3671,3673,3675,3677,3679,3681,3683,3685,3687,3689,3691,3693,3695,3697,3699,3701,3703,3705,3707,3709,3711,3713,3715,3717,3719,3721,3723,3725,3727,3729,3731,3733,3735,3737,3739,3741,3743,3745,3747,3749,3751,3753,3755,3757,3759,3761,3763,3765,3767,3769,3771,3773,3775,3777,3779,3781,3783,3785,3787,3789,3791,3793],{"categories":228},[229],"Developer Productivity",{"categories":231},[232],"Business & SaaS",{"categories":234},[174],{"categories":236},[237],"AI Automation",{"categories":239},[240],"Product Strategy",{"categories":242},[174],{"categories":244},[229],{"categories":246},[232],{"categories":248},[],{"categories":250},[174],{"categories":252},[],{"categories":254},[255],"AI News & Trends",{"categories":257},[237],{"categories":259},[255],{"categories":261},[237],{"categories":263},[237],{"categories":265},[174],{"categories":267},[174],{"categories":269},[255],{"categories":271},[174],{"categories":273},[],{"categories":275},[276],"Design & Frontend",{"categories":278},[279],"Data Science & Visualization",{"categories":281},[255],{"categories":283},[],{"categories":285},[286],"Software Engineering",{"categories":288},[174],{"categories":290},[237],{"categories":292},[293],"Marketing & Growth",{"categories":295},[174],{"categories":297},[237],{"categories":299},[],{"categories":301},[],{"categories":303},[276],{"categories":305},[237],{"categories":307},[229],{"categories":309},[276],{"categories":311},[174],{"categories":313},[237],{"categories":315},[255],{"categories":317},[],{"categories":319},[],{"categories":321},[237],{"categories":323},[286],{"categories":325},[],{"categories":327},[232],{"categories":329},[],{"categories":331},[],{"categories":333},[237],{"categories":335},[237],{"categories":337},[174],{"categories":339},[],{"categories":341},[286],{"categories":343},[],{"categories":345},[],{"categories":347},[],{"categories":349},[174],{"categories":351},[293],{"categories":353},[276],{"categories":355},[276],{"categories":357},[174],{"categories":359},[237],{"categories":361},[174],{"categories":363},[174],{"categories":365},[237],{"categories":367},[237],{"categories":369},[279],{"categories":371},[255],{"categories":373},[237],{"categories":375},[293],{"categories":377},[237],{"categories":379},[240],{"categories":381},[],{"categories":383},[237],{"categories":385},[],{"categories":387},[237],{"categories":389},[286],{"categories":391},[276],{"categories":393},[174],{"categories":395},[],{"categories":397},[],{"categories":399},[237],{"categories":401},[],{"categories":403},[174],{"categories":405},[],{"categories":407},[229],{"categories":409},[286],{"categories":411},[232],{"categories":413},[255],{"categories":415},[174],{"categories":417},[],{"categories":419},[174],{"categories":421},[],{"categories":423},[286],{"categories":425},[279],{"categories":427},[],{"categories":429},[174],{"categories":431},[276],{"categories":433},[],{"categories":435},[276],{"categories":437},[237],{"categories":439},[],{"categories":441},[237],{"categories":443},[255],{"categories":445},[174],{"categories":447},[],{"categories":449},[237],{"categories":451},[174],{"categories":453},[240],{"categories":455},[],{"categories":457},[174],{"categories":459},[237],{"categories":461},[237],{"categories":463},[],{"categories":465},[279],{"categories":467},[174],{"categories":469},[],{"categories":471},[229],{"categories":473},[232],{"categories":475},[174],{"categories":477},[237],{"categories":479},[286],{"categories":481},[174],{"categories":483},[],{"categories":485},[],{"categories":487},[174],{"categories":489},[],{"categories":491},[276],{"categories":493},[],{"categories":495},[174],{"categories":497},[],{"categories":499},[237],{"categories":501},[174],{"categories":503},[276],{"categories":505},[],{"categories":507},[174],{"categories":509},[174],{"categories":511},[232],{"categories":513},[237],{"categories":515},[174],{"categories":517},[276],{"categories":519},[237],{"categories":521},[],{"categories":523},[],{"categories":525},[255],{"categories":527},[],{"categories":529},[174],{"categories":531},[232,293],{"categories":533},[],{"categories":535},[174],{"categories":537},[],{"categories":539},[],{"categories":541},[174],{"categories":543},[],{"categories":545},[174],{"categories":547},[548],"DevOps & Cloud",{"categories":550},[],{"categories":552},[255],{"categories":554},[276],{"categories":556},[],{"categories":558},[255],{"categories":560},[255],{"categories":562},[174],{"categories":564},[293],{"categories":566},[],{"categories":568},[232],{"categories":570},[],{"categories":572},[174,548],{"categories":574},[174],{"categories":576},[174],{"categories":578},[237],{"categories":580},[174,286],{"categories":582},[279],{"categories":584},[174],{"categories":586},[293],{"categories":588},[237],{"categories":590},[237],{"categories":592},[],{"categories":594},[237],{"categories":596},[174,232],{"categories":598},[],{"categories":600},[276],{"categories":602},[276],{"categories":604},[],{"categories":606},[],{"categories":608},[255],{"categories":610},[],{"categories":612},[229],{"categories":614},[286],{"categories":616},[174],{"categories":618},[276],{"categories":620},[237],{"categories":622},[286],{"categories":624},[255],{"categories":626},[276],{"categories":628},[],{"categories":630},[174],{"categories":632},[174],{"categories":634},[174],{"categories":636},[255],{"categories":638},[229],{"categories":640},[174],{"categories":642},[237],{"categories":644},[548],{"categories":646},[276],{"categories":648},[237],{"categories":650},[],{"categories":652},[],{"categories":654},[276],{"categories":656},[255],{"categories":658},[279],{"categories":660},[],{"categories":662},[174],{"categories":664},[174],{"categories":666},[232],{"categories":668},[174],{"categories":670},[174],{"categories":672},[255],{"categories":674},[],{"categories":676},[237],{"categories":678},[286],{"categories":680},[],{"categories":682},[174],{"categories":684},[174],{"categories":686},[237],{"categories":688},[],{"categories":690},[],{"categories":692},[174],{"categories":694},[],{"categories":696},[232],{"categories":698},[237],{"categories":700},[],{"categories":702},[229],{"categories":704},[174],{"categories":706},[232],{"categories":708},[255],{"categories":710},[],{"categories":712},[],{"categories":714},[],{"categories":716},[255],{"categories":718},[255],{"categories":720},[],{"categories":722},[],{"categories":724},[232],{"categories":726},[],{"categories":728},[],{"categories":730},[229],{"categories":732},[],{"categories":734},[293],{"categories":736},[237],{"categories":738},[232],{"categories":740},[237],{"categories":742},[],{"categories":744},[240],{"categories":746},[276],{"categories":748},[286],{"categories":750},[174],{"categories":752},[237],{"categories":754},[232],{"categories":756},[174],{"categories":758},[],{"categories":760},[],{"categories":762},[286],{"categories":764},[279],{"categories":766},[240],{"categories":768},[237],{"categories":770},[174],{"categories":772},[],{"categories":774},[548],{"categories":776},[],{"categories":778},[237],{"categories":780},[],{"categories":782},[],{"categories":784},[174],{"categories":786},[276],{"categories":788},[293],{"categories":790},[237],{"categories":792},[],{"categories":794},[229],{"categories":796},[],{"categories":798},[255],{"categories":800},[174,548],{"categories":802},[255],{"categories":804},[174],{"categories":806},[232],{"categories":808},[174],{"categories":810},[],{"categories":812},[232],{"categories":814},[],{"categories":816},[286],{"categories":818},[276],{"categories":820},[255],{"categories":822},[279],{"categories":824},[229],{"categories":826},[174],{"categories":828},[286],{"categories":830},[],{"categories":832},[],{"categories":834},[240],{"categories":836},[],{"categories":838},[174],{"categories":840},[],{"categories":842},[276],{"categories":844},[276],{"categories":846},[276],{"categories":848},[],{"categories":850},[],{"categories":852},[255],{"categories":854},[237],{"categories":856},[174],{"categories":858},[174],{"categories":860},[174],{"categories":862},[232],{"categories":864},[174],{"categories":866},[],{"categories":868},[286],{"categories":870},[286],{"categories":872},[232],{"categories":874},[],{"categories":876},[174],{"categories":878},[174],{"categories":880},[232],{"categories":882},[255],{"categories":884},[293],{"categories":886},[237],{"categories":888},[],{"categories":890},[276],{"categories":892},[],{"categories":894},[174],{"categories":896},[],{"categories":898},[232],{"categories":900},[237],{"categories":902},[],{"categories":904},[548],{"categories":906},[279],{"categories":908},[286],{"categories":910},[293],{"categories":912},[286],{"categories":914},[237],{"categories":916},[],{"categories":918},[],{"categories":920},[237],{"categories":922},[229],{"categories":924},[237],{"categories":926},[240],{"categories":928},[232],{"categories":930},[],{"categories":932},[174],{"categories":934},[240],{"categories":936},[174],{"categories":938},[174],{"categories":940},[293],{"categories":942},[276],{"categories":944},[237],{"categories":946},[],{"categories":948},[],{"categories":950},[548],{"categories":952},[286],{"categories":954},[],{"categories":956},[237],{"categories":958},[174],{"categories":960},[276,174],{"categories":962},[229],{"categories":964},[],{"categories":966},[174],{"categories":968},[229],{"categories":970},[276],{"categories":972},[237],{"categories":974},[286],{"categories":976},[],{"categories":978},[174],{"categories":980},[],{"categories":982},[229],{"categories":984},[],{"categories":986},[237],{"categories":988},[240],{"categories":990},[174],{"categories":992},[174],{"categories":994},[276],{"categories":996},[237],{"categories":998},[548],{"categories":1000},[276],{"categories":1002},[237],{"categories":1004},[174],{"categories":1006},[174],{"categories":1008},[174],{"categories":1010},[255],{"categories":1012},[],{"categories":1014},[240],{"categories":1016},[237],{"categories":1018},[276],{"categories":1020},[237],{"categories":1022},[286],{"categories":1024},[276],{"categories":1026},[237],{"categories":1028},[255],{"categories":1030},[],{"categories":1032},[174],{"categories":1034},[276],{"categories":1036},[174],{"categories":1038},[229],{"categories":1040},[255],{"categories":1042},[174],{"categories":1044},[293],{"categories":1046},[174],{"categories":1048},[174],{"categories":1050},[237],{"categories":1052},[237],{"categories":1054},[174],{"categories":1056},[237],{"categories":1058},[276],{"categories":1060},[174],{"categories":1062},[],{"categories":1064},[],{"categories":1066},[286],{"categories":1068},[],{"categories":1070},[229],{"categories":1072},[548],{"categories":1074},[],{"categories":1076},[229],{"categories":1078},[232],{"categories":1080},[293],{"categories":1082},[],{"categories":1084},[232],{"categories":1086},[],{"categories":1088},[],{"categories":1090},[],{"categories":1092},[],{"categories":1094},[],{"categories":1096},[174],{"categories":1098},[237],{"categories":1100},[548],{"categories":1102},[229],{"categories":1104},[174],{"categories":1106},[286],{"categories":1108},[240],{"categories":1110},[174],{"categories":1112},[293],{"categories":1114},[174],{"categories":1116},[174],{"categories":1118},[174],{"categories":1120},[174,229],{"categories":1122},[286],{"categories":1124},[286],{"categories":1126},[276],{"categories":1128},[174],{"categories":1130},[],{"categories":1132},[],{"categories":1134},[],{"categories":1136},[286],{"categories":1138},[279],{"categories":1140},[255],{"categories":1142},[276],{"categories":1144},[],{"categories":1146},[174],{"categories":1148},[174],{"categories":1150},[],{"categories":1152},[],{"categories":1154},[237],{"categories":1156},[174],{"categories":1158},[232],{"categories":1160},[],{"categories":1162},[229],{"categories":1164},[174],{"categories":1166},[229],{"categories":1168},[174],{"categories":1170},[286],{"categories":1172},[293],{"categories":1174},[174,276],{"categories":1176},[255],{"categories":1178},[276],{"categories":1180},[],{"categories":1182},[548],{"categories":1184},[276],{"categories":1186},[237],{"categories":1188},[],{"categories":1190},[],{"categories":1192},[],{"categories":1194},[],{"categories":1196},[286],{"categories":1198},[237],{"categories":1200},[237],{"categories":1202},[174],{"categories":1204},[174],{"categories":1206},[],{"categories":1208},[276],{"categories":1210},[],{"categories":1212},[],{"categories":1214},[237],{"categories":1216},[],{"categories":1218},[],{"categories":1220},[293],{"categories":1222},[293],{"categories":1224},[237],{"categories":1226},[],{"categories":1228},[174],{"categories":1230},[174],{"categories":1232},[286],{"categories":1234},[276],{"categories":1236},[276],{"categories":1238},[237],{"categories":1240},[229],{"categories":1242},[174],{"categories":1244},[276],{"categories":1246},[276],{"categories":1248},[237],{"categories":1250},[237],{"categories":1252},[174],{"categories":1254},[],{"categories":1256},[],{"categories":1258},[174],{"categories":1260},[237],{"categories":1262},[255],{"categories":1264},[286],{"categories":1266},[229],{"categories":1268},[174],{"categories":1270},[],{"categories":1272},[237],{"categories":1274},[237],{"categories":1276},[],{"categories":1278},[229],{"categories":1280},[174],{"categories":1282},[229],{"categories":1284},[229],{"categories":1286},[],{"categories":1288},[],{"categories":1290},[237],{"categories":1292},[237],{"categories":1294},[174],{"categories":1296},[174],{"categories":1298},[255],{"categories":1300},[279],{"categories":1302},[240],{"categories":1304},[255],{"categories":1306},[276],{"categories":1308},[],{"categories":1310},[255],{"categories":1312},[],{"categories":1314},[],{"categories":1316},[],{"categories":1318},[],{"categories":1320},[286],{"categories":1322},[279],{"categories":1324},[],{"categories":1326},[174],{"categories":1328},[174],{"categories":1330},[279],{"categories":1332},[286],{"categories":1334},[],{"categories":1336},[],{"categories":1338},[237],{"categories":1340},[255],{"categories":1342},[255],{"categories":1344},[237],{"categories":1346},[229],{"categories":1348},[174,548],{"categories":1350},[],{"categories":1352},[276],{"categories":1354},[229],{"categories":1356},[237],{"categories":1358},[276],{"categories":1360},[],{"categories":1362},[237],{"categories":1364},[237],{"categories":1366},[174],{"categories":1368},[293],{"categories":1370},[286],{"categories":1372},[276],{"categories":1374},[],{"categories":1376},[237],{"categories":1378},[174],{"categories":1380},[237],{"categories":1382},[237],{"categories":1384},[237],{"categories":1386},[293],{"categories":1388},[237],{"categories":1390},[174],{"categories":1392},[],{"categories":1394},[293],{"categories":1396},[255],{"categories":1398},[237],{"categories":1400},[],{"categories":1402},[],{"categories":1404},[174],{"categories":1406},[237],{"categories":1408},[255],{"categories":1410},[237],{"categories":1412},[],{"categories":1414},[],{"categories":1416},[],{"categories":1418},[237],{"categories":1420},[],{"categories":1422},[],{"categories":1424},[279],{"categories":1426},[174],{"categories":1428},[279],{"categories":1430},[255],{"categories":1432},[174],{"categories":1434},[174],{"categories":1436},[237],{"categories":1438},[174],{"categories":1440},[],{"categories":1442},[],{"categories":1444},[548],{"categories":1446},[],{"categories":1448},[],{"categories":1450},[229],{"categories":1452},[],{"categories":1454},[],{"categories":1456},[],{"categories":1458},[],{"categories":1460},[286],{"categories":1462},[255],{"categories":1464},[293],{"categories":1466},[232],{"categories":1468},[174],{"categories":1470},[174],{"categories":1472},[232],{"categories":1474},[],{"categories":1476},[276],{"categories":1478},[237],{"categories":1480},[232],{"categories":1482},[174],{"categories":1484},[174],{"categories":1486},[229],{"categories":1488},[],{"categories":1490},[229],{"categories":1492},[174],{"categories":1494},[293],{"categories":1496},[237],{"categories":1498},[255],{"categories":1500},[232],{"categories":1502},[174],{"categories":1504},[237],{"categories":1506},[],{"categories":1508},[174],{"categories":1510},[229],{"categories":1512},[174],{"categories":1514},[],{"categories":1516},[255],{"categories":1518},[174],{"categories":1520},[],{"categories":1522},[232],{"categories":1524},[174],{"categories":1526},[],{"categories":1528},[],{"categories":1530},[],{"categories":1532},[174],{"categories":1534},[],{"categories":1536},[548],{"categories":1538},[174],{"categories":1540},[],{"categories":1542},[174],{"categories":1544},[174],{"categories":1546},[174],{"categories":1548},[174,548],{"categories":1550},[174],{"categories":1552},[174],{"categories":1554},[276],{"categories":1556},[237],{"categories":1558},[],{"categories":1560},[237],{"categories":1562},[174],{"categories":1564},[174],{"categories":1566},[174],{"categories":1568},[229],{"categories":1570},[229],{"categories":1572},[286],{"categories":1574},[276],{"categories":1576},[237],{"categories":1578},[],{"categories":1580},[174],{"categories":1582},[255],{"categories":1584},[174],{"categories":1586},[232],{"categories":1588},[],{"categories":1590},[548],{"categories":1592},[276],{"categories":1594},[276],{"categories":1596},[237],{"categories":1598},[255],{"categories":1600},[237],{"categories":1602},[174],{"categories":1604},[],{"categories":1606},[174],{"categories":1608},[],{"categories":1610},[],{"categories":1612},[174],{"categories":1614},[174],{"categories":1616},[174],{"categories":1618},[237],{"categories":1620},[174],{"categories":1622},[],{"categories":1624},[279],{"categories":1626},[237],{"categories":1628},[],{"categories":1630},[174],{"categories":1632},[255],{"categories":1634},[],{"categories":1636},[276],{"categories":1638},[548],{"categories":1640},[255],{"categories":1642},[286],{"categories":1644},[286],{"categories":1646},[255],{"categories":1648},[255],{"categories":1650},[548],{"categories":1652},[],{"categories":1654},[255],{"categories":1656},[174],{"categories":1658},[229],{"categories":1660},[255],{"categories":1662},[],{"categories":1664},[279],{"categories":1666},[255],{"categories":1668},[286],{"categories":1670},[255],{"categories":1672},[548],{"categories":1674},[174],{"categories":1676},[174],{"categories":1678},[],{"categories":1680},[232],{"categories":1682},[],{"categories":1684},[],{"categories":1686},[174],{"categories":1688},[174],{"categories":1690},[174],{"categories":1692},[174],{"categories":1694},[],{"categories":1696},[279],{"categories":1698},[229],{"categories":1700},[],{"categories":1702},[174],{"categories":1704},[174],{"categories":1706},[548],{"categories":1708},[548],{"categories":1710},[],{"categories":1712},[237],{"categories":1714},[255],{"categories":1716},[255],{"categories":1718},[174],{"categories":1720},[237],{"categories":1722},[],{"categories":1724},[276],{"categories":1726},[174],{"categories":1728},[174],{"categories":1730},[],{"categories":1732},[],{"categories":1734},[548],{"categories":1736},[174],{"categories":1738},[286],{"categories":1740},[232],{"categories":1742},[174],{"categories":1744},[],{"categories":1746},[237],{"categories":1748},[229],{"categories":1750},[229],{"categories":1752},[],{"categories":1754},[174],{"categories":1756},[276],{"categories":1758},[237],{"categories":1760},[],{"categories":1762},[174],{"categories":1764},[174],{"categories":1766},[237],{"categories":1768},[],{"categories":1770},[237],{"categories":1772},[286],{"categories":1774},[],{"categories":1776},[174],{"categories":1778},[],{"categories":1780},[174],{"categories":1782},[],{"categories":1784},[174],{"categories":1786},[174],{"categories":1788},[],{"categories":1790},[174],{"categories":1792},[255],{"categories":1794},[174],{"categories":1796},[174],{"categories":1798},[229],{"categories":1800},[174],{"categories":1802},[255],{"categories":1804},[237],{"categories":1806},[],{"categories":1808},[174],{"categories":1810},[293],{"categories":1812},[],{"categories":1814},[],{"categories":1816},[],{"categories":1818},[229],{"categories":1820},[255],{"categories":1822},[237],{"categories":1824},[174],{"categories":1826},[276],{"categories":1828},[237],{"categories":1830},[],{"categories":1832},[237],{"categories":1834},[],{"categories":1836},[174],{"categories":1838},[237],{"categories":1840},[174],{"categories":1842},[],{"categories":1844},[174],{"categories":1846},[174],{"categories":1848},[255],{"categories":1850},[276],{"categories":1852},[237],{"categories":1854},[276],{"categories":1856},[232],{"categories":1858},[],{"categories":1860},[],{"categories":1862},[174],{"categories":1864},[229],{"categories":1866},[255],{"categories":1868},[],{"categories":1870},[],{"categories":1872},[286],{"categories":1874},[276],{"categories":1876},[],{"categories":1878},[174],{"categories":1880},[],{"categories":1882},[293],{"categories":1884},[174],{"categories":1886},[548],{"categories":1888},[286],{"categories":1890},[],{"categories":1892},[237],{"categories":1894},[174],{"categories":1896},[237],{"categories":1898},[237],{"categories":1900},[174],{"categories":1902},[],{"categories":1904},[229],{"categories":1906},[174],{"categories":1908},[232],{"categories":1910},[286],{"categories":1912},[276],{"categories":1914},[],{"categories":1916},[],{"categories":1918},[],{"categories":1920},[237],{"categories":1922},[276],{"categories":1924},[255],{"categories":1926},[174],{"categories":1928},[255],{"categories":1930},[276],{"categories":1932},[],{"categories":1934},[276],{"categories":1936},[255],{"categories":1938},[232],{"categories":1940},[174],{"categories":1942},[255],{"categories":1944},[293],{"categories":1946},[],{"categories":1948},[],{"categories":1950},[279],{"categories":1952},[174,286],{"categories":1954},[255],{"categories":1956},[174],{"categories":1958},[237],{"categories":1960},[237],{"categories":1962},[174],{"categories":1964},[],{"categories":1966},[286],{"categories":1968},[174],{"categories":1970},[279],{"categories":1972},[237],{"categories":1974},[293],{"categories":1976},[548],{"categories":1978},[],{"categories":1980},[229],{"categories":1982},[237],{"categories":1984},[237],{"categories":1986},[286],{"categories":1988},[174],{"categories":1990},[174],{"categories":1992},[],{"categories":1994},[],{"categories":1996},[],{"categories":1998},[548],{"categories":2000},[255],{"categories":2002},[174],{"categories":2004},[174],{"categories":2006},[174],{"categories":2008},[],{"categories":2010},[279],{"categories":2012},[232],{"categories":2014},[],{"categories":2016},[237],{"categories":2018},[548],{"categories":2020},[],{"categories":2022},[276],{"categories":2024},[276],{"categories":2026},[],{"categories":2028},[286],{"categories":2030},[276],{"categories":2032},[174],{"categories":2034},[],{"categories":2036},[255],{"categories":2038},[174],{"categories":2040},[276],{"categories":2042},[237],{"categories":2044},[255],{"categories":2046},[],{"categories":2048},[237],{"categories":2050},[276],{"categories":2052},[174],{"categories":2054},[],{"categories":2056},[174],{"categories":2058},[174],{"categories":2060},[548],{"categories":2062},[255],{"categories":2064},[279],{"categories":2066},[279],{"categories":2068},[],{"categories":2070},[],{"categories":2072},[],{"categories":2074},[237],{"categories":2076},[286],{"categories":2078},[286],{"categories":2080},[],{"categories":2082},[],{"categories":2084},[174],{"categories":2086},[],{"categories":2088},[237],{"categories":2090},[174],{"categories":2092},[],{"categories":2094},[174],{"categories":2096},[232],{"categories":2098},[174],{"categories":2100},[293],{"categories":2102},[237],{"categories":2104},[174],{"categories":2106},[286],{"categories":2108},[255],{"categories":2110},[237],{"categories":2112},[],{"categories":2114},[255],{"categories":2116},[237],{"categories":2118},[237],{"categories":2120},[],{"categories":2122},[232],{"categories":2124},[237],{"categories":2126},[],{"categories":2128},[174],{"categories":2130},[229],{"categories":2132},[255],{"categories":2134},[548],{"categories":2136},[237],{"categories":2138},[237],{"categories":2140},[229],{"categories":2142},[174],{"categories":2144},[],{"categories":2146},[],{"categories":2148},[276],{"categories":2150},[174,232],{"categories":2152},[],{"categories":2154},[229],{"categories":2156},[279],{"categories":2158},[174],{"categories":2160},[286],{"categories":2162},[174],{"categories":2164},[237],{"categories":2166},[174],{"categories":2168},[174],{"categories":2170},[255],{"categories":2172},[237],{"categories":2174},[],{"categories":2176},[],{"categories":2178},[237],{"categories":2180},[174],{"categories":2182},[548],{"categories":2184},[],{"categories":2186},[174],{"categories":2188},[237],{"categories":2190},[],{"categories":2192},[174],{"categories":2194},[293],{"categories":2196},[279],{"categories":2198},[237],{"categories":2200},[174],{"categories":2202},[548],{"categories":2204},[],{"categories":2206},[174],{"categories":2208},[293],{"categories":2210},[276],{"categories":2212},[174],{"categories":2214},[],{"categories":2216},[293],{"categories":2218},[255],{"categories":2220},[174],{"categories":2222},[174],{"categories":2224},[229],{"categories":2226},[],{"categories":2228},[],{"categories":2230},[276],{"categories":2232},[174],{"categories":2234},[279],{"categories":2236},[293],{"categories":2238},[293],{"categories":2240},[255],{"categories":2242},[],{"categories":2244},[],{"categories":2246},[174],{"categories":2248},[],{"categories":2250},[174,286],{"categories":2252},[255],{"categories":2254},[237],{"categories":2256},[286],{"categories":2258},[174],{"categories":2260},[229],{"categories":2262},[],{"categories":2264},[],{"categories":2266},[229],{"categories":2268},[293],{"categories":2270},[174],{"categories":2272},[],{"categories":2274},[276,174],{"categories":2276},[548],{"categories":2278},[229],{"categories":2280},[],{"categories":2282},[232],{"categories":2284},[232],{"categories":2286},[174],{"categories":2288},[286],{"categories":2290},[237],{"categories":2292},[255],{"categories":2294},[293],{"categories":2296},[276],{"categories":2298},[174],{"categories":2300},[174],{"categories":2302},[174],{"categories":2304},[229],{"categories":2306},[174],{"categories":2308},[237],{"categories":2310},[255],{"categories":2312},[],{"categories":2314},[],{"categories":2316},[279],{"categories":2318},[286],{"categories":2320},[174],{"categories":2322},[276],{"categories":2324},[279],{"categories":2326},[174],{"categories":2328},[174],{"categories":2330},[237],{"categories":2332},[237],{"categories":2334},[174,232],{"categories":2336},[],{"categories":2338},[276],{"categories":2340},[],{"categories":2342},[174],{"categories":2344},[255],{"categories":2346},[229],{"categories":2348},[229],{"categories":2350},[237],{"categories":2352},[174],{"categories":2354},[232],{"categories":2356},[286],{"categories":2358},[293],{"categories":2360},[],{"categories":2362},[255],{"categories":2364},[174],{"categories":2366},[174],{"categories":2368},[255],{"categories":2370},[286],{"categories":2372},[174],{"categories":2374},[237],{"categories":2376},[255],{"categories":2378},[174],{"categories":2380},[276],{"categories":2382},[174],{"categories":2384},[174],{"categories":2386},[548],{"categories":2388},[240],{"categories":2390},[237],{"categories":2392},[174],{"categories":2394},[255],{"categories":2396},[237],{"categories":2398},[293],{"categories":2400},[174],{"categories":2402},[],{"categories":2404},[174],{"categories":2406},[],{"categories":2408},[],{"categories":2410},[],{"categories":2412},[232],{"categories":2414},[174],{"categories":2416},[237],{"categories":2418},[255],{"categories":2420},[255],{"categories":2422},[255],{"categories":2424},[255],{"categories":2426},[],{"categories":2428},[229],{"categories":2430},[237],{"categories":2432},[255],{"categories":2434},[229],{"categories":2436},[237],{"categories":2438},[174],{"categories":2440},[174,237],{"categories":2442},[237],{"categories":2444},[548],{"categories":2446},[255],{"categories":2448},[255],{"categories":2450},[237],{"categories":2452},[174],{"categories":2454},[],{"categories":2456},[255],{"categories":2458},[293],{"categories":2460},[229],{"categories":2462},[174],{"categories":2464},[174],{"categories":2466},[],{"categories":2468},[286],{"categories":2470},[],{"categories":2472},[229],{"categories":2474},[237],{"categories":2476},[255],{"categories":2478},[174],{"categories":2480},[255],{"categories":2482},[229],{"categories":2484},[255],{"categories":2486},[255],{"categories":2488},[],{"categories":2490},[232],{"categories":2492},[237],{"categories":2494},[255],{"categories":2496},[255],{"categories":2498},[255],{"categories":2500},[255],{"categories":2502},[255],{"categories":2504},[255],{"categories":2506},[255],{"categories":2508},[255],{"categories":2510},[255],{"categories":2512},[255],{"categories":2514},[279],{"categories":2516},[229],{"categories":2518},[174],{"categories":2520},[174],{"categories":2522},[],{"categories":2524},[174,229],{"categories":2526},[],{"categories":2528},[237],{"categories":2530},[255],{"categories":2532},[237],{"categories":2534},[174],{"categories":2536},[174],{"categories":2538},[174],{"categories":2540},[174],{"categories":2542},[174],{"categories":2544},[237],{"categories":2546},[232],{"categories":2548},[276],{"categories":2550},[255],{"categories":2552},[174],{"categories":2554},[],{"categories":2556},[],{"categories":2558},[237],{"categories":2560},[276],{"categories":2562},[174],{"categories":2564},[],{"categories":2566},[],{"categories":2568},[293],{"categories":2570},[174],{"categories":2572},[],{"categories":2574},[],{"categories":2576},[229],{"categories":2578},[232],{"categories":2580},[174],{"categories":2582},[232],{"categories":2584},[276],{"categories":2586},[],{"categories":2588},[255],{"categories":2590},[],{"categories":2592},[276],{"categories":2594},[174],{"categories":2596},[293],{"categories":2598},[],{"categories":2600},[293],{"categories":2602},[],{"categories":2604},[],{"categories":2606},[237],{"categories":2608},[],{"categories":2610},[232],{"categories":2612},[229],{"categories":2614},[276],{"categories":2616},[286],{"categories":2618},[],{"categories":2620},[],{"categories":2622},[174],{"categories":2624},[229],{"categories":2626},[293],{"categories":2628},[],{"categories":2630},[237],{"categories":2632},[237],{"categories":2634},[255],{"categories":2636},[174],{"categories":2638},[237],{"categories":2640},[174],{"categories":2642},[237],{"categories":2644},[174],{"categories":2646},[240],{"categories":2648},[255],{"categories":2650},[],{"categories":2652},[293],{"categories":2654},[286],{"categories":2656},[237],{"categories":2658},[],{"categories":2660},[174],{"categories":2662},[237],{"categories":2664},[232],{"categories":2666},[229],{"categories":2668},[174],{"categories":2670},[276],{"categories":2672},[286],{"categories":2674},[286],{"categories":2676},[174],{"categories":2678},[279],{"categories":2680},[174],{"categories":2682},[237],{"categories":2684},[232],{"categories":2686},[237],{"categories":2688},[174],{"categories":2690},[174],{"categories":2692},[237],{"categories":2694},[255],{"categories":2696},[],{"categories":2698},[229],{"categories":2700},[174],{"categories":2702},[237],{"categories":2704},[174],{"categories":2706},[174],{"categories":2708},[],{"categories":2710},[276],{"categories":2712},[232],{"categories":2714},[255],{"categories":2716},[174],{"categories":2718},[174],{"categories":2720},[276],{"categories":2722},[293],{"categories":2724},[279],{"categories":2726},[174],{"categories":2728},[255],{"categories":2730},[174],{"categories":2732},[237],{"categories":2734},[548],{"categories":2736},[174],{"categories":2738},[237],{"categories":2740},[279],{"categories":2742},[],{"categories":2744},[237],{"categories":2746},[286],{"categories":2748},[276],{"categories":2750},[174],{"categories":2752},[229],{"categories":2754},[232],{"categories":2756},[286],{"categories":2758},[],{"categories":2760},[237],{"categories":2762},[174],{"categories":2764},[],{"categories":2766},[255],{"categories":2768},[],{"categories":2770},[255],{"categories":2772},[174],{"categories":2774},[237],{"categories":2776},[237],{"categories":2778},[237],{"categories":2780},[],{"categories":2782},[],{"categories":2784},[174],{"categories":2786},[174],{"categories":2788},[],{"categories":2790},[276],{"categories":2792},[237],{"categories":2794},[293],{"categories":2796},[229],{"categories":2798},[],{"categories":2800},[],{"categories":2802},[255],{"categories":2804},[286],{"categories":2806},[174],{"categories":2808},[174],{"categories":2810},[174],{"categories":2812},[286],{"categories":2814},[255],{"categories":2816},[276],{"categories":2818},[174],{"categories":2820},[174],{"categories":2822},[174],{"categories":2824},[255],{"categories":2826},[174],{"categories":2828},[255],{"categories":2830},[237],{"categories":2832},[237],{"categories":2834},[286],{"categories":2836},[237],{"categories":2838},[174],{"categories":2840},[286],{"categories":2842},[276],{"categories":2844},[],{"categories":2846},[237],{"categories":2848},[],{"categories":2850},[],{"categories":2852},[232],{"categories":2854},[174],{"categories":2856},[237],{"categories":2858},[229],{"categories":2860},[237],{"categories":2862},[293],{"categories":2864},[],{"categories":2866},[237],{"categories":2868},[],{"categories":2870},[229],{"categories":2872},[237],{"categories":2874},[],{"categories":2876},[237],{"categories":2878},[174],{"categories":2880},[255],{"categories":2882},[174],{"categories":2884},[237],{"categories":2886},[255],{"categories":2888},[237],{"categories":2890},[286],{"categories":2892},[276],{"categories":2894},[229],{"categories":2896},[],{"categories":2898},[237],{"categories":2900},[276],{"categories":2902},[255],{"categories":2904},[174],{"categories":2906},[276],{"categories":2908},[229],{"categories":2910},[],{"categories":2912},[237],{"categories":2914},[237],{"categories":2916},[174],{"categories":2918},[],{"categories":2920},[237],{"categories":2922},[240],{"categories":2924},[255],{"categories":2926},[237],{"categories":2928},[232],{"categories":2930},[],{"categories":2932},[174],{"categories":2934},[240],{"categories":2936},[174],{"categories":2938},[237],{"categories":2940},[255],{"categories":2942},[229],{"categories":2944},[548],{"categories":2946},[174],{"categories":2948},[174],{"categories":2950},[174],{"categories":2952},[255],{"categories":2954},[232],{"categories":2956},[174],{"categories":2958},[276],{"categories":2960},[255],{"categories":2962},[548],{"categories":2964},[174],{"categories":2966},[],{"categories":2968},[],{"categories":2970},[548],{"categories":2972},[279],{"categories":2974},[237],{"categories":2976},[237],{"categories":2978},[255],{"categories":2980},[174],{"categories":2982},[229],{"categories":2984},[276],{"categories":2986},[237],{"categories":2988},[174],{"categories":2990},[293],{"categories":2992},[174],{"categories":2994},[237],{"categories":2996},[],{"categories":2998},[174],{"categories":3000},[174],{"categories":3002},[255],{"categories":3004},[229],{"categories":3006},[],{"categories":3008},[174],{"categories":3010},[174],{"categories":3012},[286],{"categories":3014},[276],{"categories":3016},[174,237],{"categories":3018},[293,232],{"categories":3020},[174],{"categories":3022},[],{"categories":3024},[237],{"categories":3026},[],{"categories":3028},[286],{"categories":3030},[174],{"categories":3032},[255],{"categories":3034},[],{"categories":3036},[237],{"categories":3038},[],{"categories":3040},[237],{"categories":3042},[229],{"categories":3044},[237],{"categories":3046},[174],{"categories":3048},[548],{"categories":3050},[293],{"categories":3052},[232],{"categories":3054},[232],{"categories":3056},[229],{"categories":3058},[229],{"categories":3060},[174],{"categories":3062},[237],{"categories":3064},[174],{"categories":3066},[174],{"categories":3068},[229],{"categories":3070},[174],{"categories":3072},[293],{"categories":3074},[255],{"categories":3076},[174],{"categories":3078},[237],{"categories":3080},[174],{"categories":3082},[],{"categories":3084},[286],{"categories":3086},[],{"categories":3088},[237],{"categories":3090},[229],{"categories":3092},[],{"categories":3094},[548],{"categories":3096},[174],{"categories":3098},[],{"categories":3100},[255],{"categories":3102},[237],{"categories":3104},[286],{"categories":3106},[174],{"categories":3108},[237],{"categories":3110},[286],{"categories":3112},[237],{"categories":3114},[255],{"categories":3116},[229],{"categories":3118},[255],{"categories":3120},[286],{"categories":3122},[174],{"categories":3124},[276],{"categories":3126},[174],{"categories":3128},[174],{"categories":3130},[174],{"categories":3132},[174],{"categories":3134},[237],{"categories":3136},[174],{"categories":3138},[237],{"categories":3140},[174],{"categories":3142},[229],{"categories":3144},[174],{"categories":3146},[237],{"categories":3148},[276],{"categories":3150},[229],{"categories":3152},[237],{"categories":3154},[276],{"categories":3156},[],{"categories":3158},[174],{"categories":3160},[174],{"categories":3162},[286],{"categories":3164},[],{"categories":3166},[237],{"categories":3168},[293],{"categories":3170},[174],{"categories":3172},[255],{"categories":3174},[293],{"categories":3176},[237],{"categories":3178},[232],{"categories":3180},[232],{"categories":3182},[174],{"categories":3184},[229],{"categories":3186},[],{"categories":3188},[174],{"categories":3190},[],{"categories":3192},[229],{"categories":3194},[174],{"categories":3196},[237],{"categories":3198},[237],{"categories":3200},[],{"categories":3202},[286],{"categories":3204},[286],{"categories":3206},[293],{"categories":3208},[276],{"categories":3210},[],{"categories":3212},[174],{"categories":3214},[229],{"categories":3216},[174],{"categories":3218},[286],{"categories":3220},[229],{"categories":3222},[255],{"categories":3224},[255],{"categories":3226},[],{"categories":3228},[255],{"categories":3230},[237],{"categories":3232},[276],{"categories":3234},[279],{"categories":3236},[174],{"categories":3238},[],{"categories":3240},[255],{"categories":3242},[286],{"categories":3244},[232],{"categories":3246},[174],{"categories":3248},[229],{"categories":3250},[548],{"categories":3252},[229],{"categories":3254},[],{"categories":3256},[],{"categories":3258},[255],{"categories":3260},[],{"categories":3262},[237],{"categories":3264},[237],{"categories":3266},[237],{"categories":3268},[],{"categories":3270},[174],{"categories":3272},[],{"categories":3274},[255],{"categories":3276},[229],{"categories":3278},[276],{"categories":3280},[174],{"categories":3282},[255],{"categories":3284},[255],{"categories":3286},[],{"categories":3288},[255],{"categories":3290},[229],{"categories":3292},[174],{"categories":3294},[],{"categories":3296},[237],{"categories":3298},[237],{"categories":3300},[229],{"categories":3302},[],{"categories":3304},[],{"categories":3306},[],{"categories":3308},[276],{"categories":3310},[237],{"categories":3312},[174],{"categories":3314},[],{"categories":3316},[],{"categories":3318},[],{"categories":3320},[276],{"categories":3322},[],{"categories":3324},[229],{"categories":3326},[],{"categories":3328},[],{"categories":3330},[276],{"categories":3332},[174],{"categories":3334},[255],{"categories":3336},[],{"categories":3338},[293],{"categories":3340},[255],{"categories":3342},[293],{"categories":3344},[174],{"categories":3346},[],{"categories":3348},[],{"categories":3350},[237],{"categories":3352},[],{"categories":3354},[],{"categories":3356},[237],{"categories":3358},[174],{"categories":3360},[],{"categories":3362},[237],{"categories":3364},[255],{"categories":3366},[293],{"categories":3368},[279],{"categories":3370},[237],{"categories":3372},[237],{"categories":3374},[],{"categories":3376},[],{"categories":3378},[],{"categories":3380},[255],{"categories":3382},[],{"categories":3384},[],{"categories":3386},[276],{"categories":3388},[229],{"categories":3390},[],{"categories":3392},[232],{"categories":3394},[293],{"categories":3396},[174],{"categories":3398},[286],{"categories":3400},[229],{"categories":3402},[279],{"categories":3404},[232],{"categories":3406},[286],{"categories":3408},[],{"categories":3410},[],{"categories":3412},[237],{"categories":3414},[229],{"categories":3416},[276],{"categories":3418},[229],{"categories":3420},[237],{"categories":3422},[548],{"categories":3424},[237],{"categories":3426},[],{"categories":3428},[174],{"categories":3430},[255],{"categories":3432},[286],{"categories":3434},[],{"categories":3436},[276],{"categories":3438},[255],{"categories":3440},[229],{"categories":3442},[237],{"categories":3444},[174],{"categories":3446},[232],{"categories":3448},[237,548],{"categories":3450},[237],{"categories":3452},[286],{"categories":3454},[174],{"categories":3456},[279],{"categories":3458},[293],{"categories":3460},[237],{"categories":3462},[],{"categories":3464},[237],{"categories":3466},[174],{"categories":3468},[232],{"categories":3470},[],{"categories":3472},[],{"categories":3474},[174],{"categories":3476},[279],{"categories":3478},[174],{"categories":3480},[],{"categories":3482},[255],{"categories":3484},[],{"categories":3486},[255],{"categories":3488},[286],{"categories":3490},[237],{"categories":3492},[174],{"categories":3494},[293],{"categories":3496},[286],{"categories":3498},[],{"categories":3500},[255],{"categories":3502},[174],{"categories":3504},[],{"categories":3506},[174],{"categories":3508},[237],{"categories":3510},[174],{"categories":3512},[237],{"categories":3514},[174],{"categories":3516},[174],{"categories":3518},[174],{"categories":3520},[174],{"categories":3522},[232],{"categories":3524},[],{"categories":3526},[240],{"categories":3528},[255],{"categories":3530},[174],{"categories":3532},[],{"categories":3534},[286],{"categories":3536},[174],{"categories":3538},[174],{"categories":3540},[237],{"categories":3542},[255],{"categories":3544},[174],{"categories":3546},[174],{"categories":3548},[232],{"categories":3550},[237],{"categories":3552},[276],{"categories":3554},[],{"categories":3556},[279],{"categories":3558},[174],{"categories":3560},[],{"categories":3562},[255],{"categories":3564},[293],{"categories":3566},[],{"categories":3568},[],{"categories":3570},[255],{"categories":3572},[255],{"categories":3574},[293],{"categories":3576},[229],{"categories":3578},[237],{"categories":3580},[237],{"categories":3582},[174],{"categories":3584},[232],{"categories":3586},[],{"categories":3588},[],{"categories":3590},[255],{"categories":3592},[279],{"categories":3594},[286],{"categories":3596},[237],{"categories":3598},[276],{"categories":3600},[279],{"categories":3602},[279],{"categories":3604},[],{"categories":3606},[255],{"categories":3608},[174],{"categories":3610},[174],{"categories":3612},[286],{"categories":3614},[],{"categories":3616},[255],{"categories":3618},[255],{"categories":3620},[255],{"categories":3622},[],{"categories":3624},[237],{"categories":3626},[174],{"categories":3628},[],{"categories":3630},[229],{"categories":3632},[232],{"categories":3634},[],{"categories":3636},[174],{"categories":3638},[174],{"categories":3640},[],{"categories":3642},[286],{"categories":3644},[],{"categories":3646},[],{"categories":3648},[],{"categories":3650},[],{"categories":3652},[174],{"categories":3654},[255],{"categories":3656},[],{"categories":3658},[],{"categories":3660},[174],{"categories":3662},[174],{"categories":3664},[174],{"categories":3666},[279],{"categories":3668},[174],{"categories":3670},[279],{"categories":3672},[],{"categories":3674},[279],{"categories":3676},[279],{"categories":3678},[548],{"categories":3680},[237],{"categories":3682},[286],{"categories":3684},[],{"categories":3686},[],{"categories":3688},[279],{"categories":3690},[286],{"categories":3692},[286],{"categories":3694},[286],{"categories":3696},[],{"categories":3698},[229],{"categories":3700},[286],{"categories":3702},[286],{"categories":3704},[229],{"categories":3706},[286],{"categories":3708},[232],{"categories":3710},[286],{"categories":3712},[286],{"categories":3714},[286],{"categories":3716},[279],{"categories":3718},[255],{"categories":3720},[255],{"categories":3722},[174],{"categories":3724},[286],{"categories":3726},[279],{"categories":3728},[548],{"categories":3730},[279],{"categories":3732},[279],{"categories":3734},[279],{"categories":3736},[],{"categories":3738},[232],{"categories":3740},[],{"categories":3742},[548],{"categories":3744},[286],{"categories":3746},[286],{"categories":3748},[286],{"categories":3750},[237],{"categories":3752},[255,232],{"categories":3754},[279],{"categories":3756},[],{"categories":3758},[],{"categories":3760},[279],{"categories":3762},[],{"categories":3764},[279],{"categories":3766},[255],{"categories":3768},[237],{"categories":3770},[],{"categories":3772},[286],{"categories":3774},[174],{"categories":3776},[276],{"categories":3778},[],{"categories":3780},[174],{"categories":3782},[],{"categories":3784},[255],{"categories":3786},[229],{"categories":3788},[279],{"categories":3790},[],{"categories":3792},[286],{"categories":3794},[255],[3796,3952,4013,4274],{"id":3797,"title":3798,"ai":3799,"body":3804,"categories":3925,"created_at":175,"date_modified":175,"description":165,"extension":176,"faq":175,"featured":177,"kicker_label":175,"meta":3926,"navigation":205,"path":3937,"published_at":3938,"question":175,"scraped_at":3939,"seo":3940,"sitemap":3941,"source_id":3942,"source_name":3943,"source_type":3944,"source_url":3945,"stem":3946,"tags":3947,"thumbnail_url":175,"tldr":3948,"tweet":3949,"unknown_tags":3950,"__hash__":3951},"summaries\u002Fsummaries\u002Fd87c61d87b0d275f-claude-managed-agents-scalable-path-to-production--summary.md","Claude Managed Agents: Scalable Path to Production AI Agents",{"provider":7,"model":8,"input_tokens":3800,"output_tokens":3801,"processing_time_ms":3802,"cost_usd":3803},8361,2128,38425,0.00271355,{"type":14,"value":3805,"toc":3916},[3806,3810,3813,3816,3820,3823,3826,3830,3833,3836,3840,3843,3846,3850,3853,3857,3860,3863,3865,3891,3894],[17,3807,3809],{"id":3808},"platform-evolution-mirrors-model-autonomy","Platform Evolution Mirrors Model Autonomy",[22,3811,3812],{},"Angela Jiang, head of product for the Claude platform, traces the shift from basic completion endpoints in the GPT-3 era to stateful sessions, tool calling, and now Claude Managed Agents—a full cloud computer with memory, file systems, and persistent state. This progression chases better outcomes as Claude grows more autonomous. Early APIs enabled exploration, but production builders demanded out-of-the-box reliability for agents. \"We've moved more and more towards a slightly more stateful world... to make sure that the performance of the model is better and better,\" Jiang explains. Internally, Anthropic iterated on its own agent infrastructure enough times to productize it, sparing others the pain of Mac Minis and thousand-line Python loops, as host Dan Shipper describes Every.to's setup.",[22,3814,3815],{},"Katelyn Lesse, head of engineering, emphasizes primitives like the Messages API, built-in tools (code execution in sandboxes, web search), and skills. Managed Agents harness these into a scalable unit, handling 24\u002F7 runs without custom servers. Shipper probes the build-vs-buy tension: custom setups offer flexibility but infrastructure \"sucks,\" echoing why Anthropic built this once for everyone.",[17,3817,3819],{"id":3818},"tight-harness-model-pairing-beats-generic-swapping","Tight Harness-Model Pairing Beats Generic Swapping",[22,3821,3822],{},"Lesse argues against generic harnesses hot-swapping models like GPT-4o or Gemini. Newer models demand tailored architectures—Claude excels with file systems and skills, not arbitrary tools. \"The harness and the model get very paired... there's a lot of alpha in that construct,\" she says, citing internal evals where harness tweaks drastically boosted memory performance. Path dependencies lock in behaviors: choosing file systems shapes Claude's strengths, potentially creating model \"lanes.\"",[22,3824,3825],{},"Shipper raises lock-in fears—easy model swaps in playgrounds vs. Managed Agents. Jiang counters that Anthropic's internal products use the same APIs, minimizing divergence. Reference implementations and blog posts let builders align or extend. For edge experimentation, pair redundancy at the agent level (harness + model), not below. Lesse notes even competitors like Cursor likely harness-engineer per model to squeeze performance.",[17,3827,3829],{"id":3828},"infrastructure-wall-crushes-most-agent-projects","Infrastructure Wall Crushes Most Agent Projects",[22,3831,3832],{},"Production scaling kills agents: spinning servers, managing state, ensuring reliability. Managed Agents abstracts this—modular yet opinionated on Claude-friendly primitives. Jiang: \"Infrastructure sucks... we're doing it once in a way that's going to really work.\" For Every.to's customer-facing agents, this means no more Mac Minis; scale seamlessly.",[22,3834,3835],{},"Flexibility comes via open APIs for custom tools, though Anthropic pushes file systems and skills. Undoable path dependencies? Lesse admits primitives evolve, hitting local maxima requiring rethinking, but careful choices like computer-use focus avoid over-optimizing reasoning alone.",[17,3837,3839],{"id":3838},"team-agents-reshape-workflows-beyond-solo-tools","Team Agents Reshape Workflows Beyond Solo Tools",[22,3841,3842],{},"Managed Agents target two users: internal automators (e.g., full software dev platforms) and product builders embedding agents for customers. Quick-start chats educate on primitives, enabling non-technical setups like Shipper's Code Interpreter-driven Slackbot. Anthropic's legal team runs an agent reviewing marketing copy—autonomous, persistent, no reimplemented memory.",[22,3844,3845],{},"Team agents differ from individual tools: they orchestrate multi-agents for advisor strategies, adversarial testing, or swarms. Jiang highlights end-to-end processes where engineers focus on outcomes, not infra tweaks.",[17,3847,3849],{"id":3848},"success-metrics-outcome-budget-not-step-counting","Success Metrics: Outcome + Budget, Not Step-Counting",[22,3851,3852],{},"Measure agents by goal achievement within budget, not loop iterations. Future platforms let you specify outcome + budget; Claude handles the rest. Lesse: \"In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget.\"",[17,3854,3856],{"id":3855},"self-evolving-agents-claude-writes-its-own-code","Self-Evolving Agents: Claude Writes Its Own Code",[22,3858,3859],{},"One year out: Claude self-optimizes—picks models, spins sub-agents, writes harnesses on-the-fly. \"Claude actually gets so good at understanding itself it figures out what model you should be using... Claude is able to understand itself enough that it can write itself,\" Jiang envisions. Platform scales to match dynamic needs, minimizing human architecture decisions.",[22,3861,3862],{},"\"How close are we to Claude making me a billion dollars? That's really what I'm asking,\" Shipper jokes, capturing builder excitement.",[17,3864,131],{"id":130},[55,3866,3867,3870,3873,3876,3879,3882,3885,3888],{},[58,3868,3869],{},"Build on Managed Agents primitives (Messages API, file systems, skills) for Claude-tuned performance; generic harnesses underperform newer models.",[58,3871,3872],{},"Skip custom infra—use Anthropic's scalable cloud to avoid the \"infrastructure wall\" that kills 90% of agent projects.",[58,3874,3875],{},"Pair harness tightly with model; swap at agent level for redundancy, not below.",[58,3877,3878],{},"Target team-scale use cases like legal review or dev platforms; quick-starts accelerate prototyping.",[58,3880,3881],{},"Measure by outcome + budget; future agents self-architect via meta-understanding.",[58,3883,3884],{},"Follow Anthropic blogs for reference harnesses to align custom builds.",[58,3886,3887],{},"Internal convergence ensures playground features flow to production tools quickly.",[58,3889,3890],{},"Opinionated primitives create path dependencies—choose file systems early for Claude's strengths.",[22,3892,3893],{},"Notable quotes:",[55,3895,3896,3899,3902,3905,3913],{},[58,3897,3898],{},"\"Infrastructure sucks so much... we're doing it once.\" — Angela Jiang, on why Managed Agents exist.",[58,3900,3901],{},"\"The harness and the model are becoming a single unit... a lot of alpha in harness engineering.\" — Katelyn Lesse, on model-specific optimization.",[58,3903,3904],{},"\"In a year... Claude writes its own harness on the fly.\" — Angela Jiang, future vision.",[58,3906,3907,3908,3912],{},"\"Path dependence... such a small footnote ",[3909,3910,3911],"span",{},"but"," becomes very big.\" — Dan Shipper, on primitives shaping models.",[58,3914,3915],{},"\"Get the best outcomes out of Claude... as easy as possible.\" — Angela Jiang, platform philosophy.",{"title":165,"searchDepth":166,"depth":166,"links":3917},[3918,3919,3920,3921,3922,3923,3924],{"id":3808,"depth":166,"text":3809},{"id":3818,"depth":166,"text":3819},{"id":3828,"depth":166,"text":3829},{"id":3838,"depth":166,"text":3839},{"id":3848,"depth":166,"text":3849},{"id":3855,"depth":166,"text":3856},{"id":130,"depth":166,"text":131},[174],{"content_references":3927,"triage":3935},[3928,3931,3933],{"type":3929,"title":3930,"context":183},"event","Code with Claude developer event",{"type":181,"title":3932,"context":183},"Claude Managed Agents",{"type":181,"title":3934,"context":183},"Claude Code",{"relevance":201,"novelty":202,"quality":202,"actionability":202,"composite":203,"reasoning":3936},"Category: AI & LLMs. The article discusses Claude Managed Agents, which directly addresses the needs of product builders looking to implement scalable AI agents in production. It provides insights into the evolution of AI infrastructure and practical considerations for using managed agents, making it highly relevant and actionable.","\u002Fsummaries\u002Fd87c61d87b0d275f-claude-managed-agents-scalable-path-to-production-summary","2026-05-08 20:22:38","2026-05-09 15:15:18",{"title":3798,"description":165},{"loc":3937},"8e426f7005afa70c","Every","article","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=lLypHkIVLqc","summaries\u002Fd87c61d87b0d275f-claude-managed-agents-scalable-path-to-production--summary",[217,218,220],"Anthropic's Claude Managed Agents bundle model, harness, and cloud infra to solve production scaling pains, pairing tightly with Claude for optimal outcomes over generic model swapping.","Interview with Anthropic's Claude platform leads Angela Jiang and Katelyn Lesse on the new Managed Agents: how it evolved from basic APIs to cloud-wrapped, scalable agents with file systems, skills, and tools like code execution; production hurdles; internal uses; and visions for self-writing harnesses. Follow-up to their Code with Claude event announcement.",[220],"67a22luBBdINPpPtbA7aIuhigLe643j6QFX2vsmj5gM",{"id":3953,"title":3954,"ai":3955,"body":3960,"categories":3988,"created_at":175,"date_modified":175,"description":165,"extension":176,"faq":175,"featured":177,"kicker_label":175,"meta":3989,"navigation":205,"path":4000,"published_at":4001,"question":175,"scraped_at":4002,"seo":4003,"sitemap":4004,"source_id":4005,"source_name":4006,"source_type":3944,"source_url":4007,"stem":4008,"tags":4009,"thumbnail_url":175,"tldr":4010,"tweet":175,"unknown_tags":4011,"__hash__":4012},"summaries\u002Fsummaries\u002F4aedf925f119dc46-memento-agent-llms-learn-from-past-failures-summary.md","Memento Agent: LLMs Learn from Past Failures",{"provider":7,"model":8,"input_tokens":3956,"output_tokens":3957,"processing_time_ms":3958,"cost_usd":3959},4412,1417,26100,0.0015684,{"type":14,"value":3961,"toc":3983},[3962,3966,3969,3973,3976,3980],[17,3963,3965],{"id":3964},"semantic-memory-storage-for-contextual-recall","Semantic Memory Storage for Contextual Recall",[22,3967,3968],{},"Transform raw task data—thoughts, actions, observations—into vectors using the all-MiniLM-L6-v2 embedding model. Structure as Trajectories to capture full causality chains, not just outcomes. Retrieve relevant memories via cosine similarity on embeddings, matching conceptually similar experiences despite wording differences. This replaces vague logging with precise, vector-based recall, allowing the agent to reference exact failure paths like deprecated API_V1 errors.",[17,3970,3972],{"id":3971},"decoupled-planner-executor-loop-for-adaptive-planning","Decoupled Planner-Executor Loop for Adaptive Planning",[22,3974,3975],{},"Separate planning from execution: the Planner (powered by Grok-4.1-fast-reasoning or GPT-4.1) ingests the current task plus top retrieved successful strategies and past mistakes. It synthesizes improved plans, e.g., switching to API_V2 after reviewing a prior failure trajectory. The Executor interfaces with the environment, returning deterministic feedback (success\u002Ferror) to log new trajectories. This decoupling ensures planning evolves based on execution outcomes without contaminating the reasoning model itself.",[17,3977,3979],{"id":3978},"failure-driven-optimization-reduces-steps-to-success","Failure-Driven Optimization Reduces Steps to Success",[22,3981,3982],{},"Force an initial failure (e.g., API_V1 call) to populate memory, then observe how retrieved failure data guides the Planner to correct actions on similar tasks. Without this, static LLMs repeat errors if training data ambiguates options; with Memento, agents learn experientially, dropping average steps to success from multiple trials to one. In industrial settings, this enforces accountability by preventing repeat documented failures, enabling sovereign AI with private, persistent intelligence. Full Python implementation in MEMENTO_GROK.ipynb demonstrates the loop end-to-end.",{"title":165,"searchDepth":166,"depth":166,"links":3984},[3985,3986,3987],{"id":3964,"depth":166,"text":3965},{"id":3971,"depth":166,"text":3972},{"id":3978,"depth":166,"text":3979},[174],{"content_references":3990,"triage":3998},[3991,3994,3996],{"type":196,"title":3992,"url":3993,"context":183},"MEMENTO_GROK.ipynb","https:\u002F\u002Fgithub.com\u002Ffrank-morales2020\u002FCloud_curious\u002Fblob\u002Fmaster\u002FMEMENTO_GROK.ipynb",{"type":181,"title":3995,"context":183},"all-MiniLM-L6-v2",{"type":181,"title":3997,"context":183},"Grok-4.1-fast-reasoning",{"relevance":201,"novelty":202,"quality":202,"actionability":202,"composite":203,"reasoning":3999},"Category: AI & LLMs. The article provides a detailed exploration of a novel approach to enhancing LLMs through experiential learning, addressing a specific pain point of improving AI performance by learning from past failures. It includes practical implementation details, such as using semantic embeddings and a decoupled planner-executor loop, which can be directly applied by developers building AI-powered products.","\u002Fsummaries\u002F4aedf925f119dc46-memento-agent-llms-learn-from-past-failures-summary","2026-05-08 18:30:55","2026-05-09 15:36:56",{"title":3954,"description":165},{"loc":4000},"4aedf925f119dc46","AI Simplified in Plain English","https:\u002F\u002Fmedium.com\u002Fai-simplified-in-plain-english\u002Fthe-memento-style-agent-implementing-experiential-learning-in-autonomous-systems-c74bd9a3c92d?source=rss----f37ab7d4e76b---4","summaries\u002F4aedf925f119dc46-memento-agent-llms-learn-from-past-failures-summary",[217,218,220],"Store task trajectories as semantic embeddings to enable agents to retrieve similar past experiences via cosine similarity, avoiding repeated errors and achieving deterministic success in one step after initial failure.",[220],"WclyRkFCn3vtk011IlLHTuEHpcDUIzVMIw6jp2luHIg",{"id":4014,"title":4015,"ai":4016,"body":4021,"categories":4241,"created_at":175,"date_modified":175,"description":165,"extension":176,"faq":175,"featured":177,"kicker_label":175,"meta":4242,"navigation":205,"path":4261,"published_at":4262,"question":175,"scraped_at":4263,"seo":4264,"sitemap":4265,"source_id":4266,"source_name":4267,"source_type":3944,"source_url":4268,"stem":4269,"tags":4270,"thumbnail_url":175,"tldr":4271,"tweet":175,"unknown_tags":4272,"__hash__":4273},"summaries\u002Fsummaries\u002Faf9f66e396aa16a3-build-knowledge-bases-from-agent-failures-summary.md","Build Knowledge Bases from Agent Failures",{"provider":7,"model":8,"input_tokens":4017,"output_tokens":4018,"processing_time_ms":4019,"cost_usd":4020},8610,2337,50002,0.002868,{"type":14,"value":4022,"toc":4234},[4023,4027,4030,4038,4044,4048,4051,4065,4068,4073,4100,4103,4109,4114,4125,4130,4134,4137,4157,4163,4166,4171,4175,4178,4186,4189,4195,4201,4206,4208],[17,4024,4026],{"id":4025},"why-enterprise-ai-fails-despite-hype","Why Enterprise AI Fails Despite Hype",[22,4028,4029],{},"AI excels at reasoning, code generation, and benchmarks, but stalls on Jira tickets and business delivery because it lacks institutional knowledge—tribal, undocumented domain specifics. Enterprises dump Confluence, Jira, GitHub into RAG or MCP servers (10-20 per team), assuming retrieval fixes it. Reality: 40% tribal knowledge, 20% outdated\u002Funreliable\u002Fduplicated. Output is undeterministic, untested; no evals mean you're data-entering gaps yourself. McKinsey stat: 88% companies use AI, only 6% see value. Push strategies (build everything upfront) exhaust you; agents become knowledge consumers, not managers.",[22,4031,4032,4033,4037],{},"Relate to ",[4034,4035,4036],"em",{},"Memento",": Agent has 15-minute memory, tattoos notes to persist. Same for AI—great at computation, terrible at retaining enterprise context without structured help.",[22,4039,4040,4043],{},[61,4041,4042],{},"Quote:"," \"Why do my Jira tickets not moving? Because that defines the business delivery and ROI.\"",[17,4045,4047],{"id":4046},"demand-driven-context-pull-from-failures-like-tdd","Demand-Driven Context: Pull from Failures Like TDD",[22,4049,4050],{},"Flip to pull strategy: Treat agents like new hires. Give problems (Jira\u002Fincidents), let them fail, surface gaps, fill as domain expert, have agent curate into reusable Markdown blocks. Analogies:",[55,4052,4053,4056,4059,4062],{},[58,4054,4055],{},"Monolith → Microservices: Break knowledge into agent-usable chunks.",[58,4057,4058],{},"Waterfall → Agile: Iterative cycles.",[58,4060,4061],{},"New hire onboarding: Assign tasks, they ask\u002Ffill docs.",[58,4063,4064],{},"TDD: Write failing tests (problems), implement to pass (fill gaps), refactor (curate).",[22,4066,4067],{},"Preprint proves it: arXiv paper on demand-driven context shows accuracy jumps with cycles.",[22,4069,4070],{},[61,4071,4072],{},"Core Cycle (Repeat per Problem):",[4074,4075,4076,4082,4088,4094],"ol",{},[58,4077,4078,4081],{},[61,4079,4080],{},"Assign Problem",": Real ticket\u002Fincident (e.g., root cause analysis). Agent retrieves from monolith (Confluence\u002FSlack\u002FGitHub sim via files\u002FMCP).",[58,4083,4084,4087],{},[61,4085,4086],{},"Agent Fails & Demands",": Outputs checklist of missing info (terminologies, business logic). Scores confidence (1-5), flags critical gaps. Discovers undocumented entities.",[58,4089,4090,4093],{},[61,4091,4092],{},"Human Fills",": Provide exact knowledge (prepped answers in demo).",[58,4095,4096,4099],{},[61,4097,4098],{},"Agent Curates",": Updates knowledge base—discovers related entities, structures in Markdown (entities grow from 56 to 70+ per cycle). Persistence: Files for demo, but plug MCP\u002FConfluence.",[22,4101,4102],{},"After 14 incidents: Confidence from 1.4 (all critical) to 4.4. Agent evolves from consumer to curator.",[22,4104,4105,4108],{},[61,4106,4107],{},"Principles:"," Agents must reason post-retrieval (missing in basic RAG). Gaps surface only via problems—can't guess tribal knowledge. No one fixes your monolith; LLM providers chase models, retrieval market ($9B) ignores it.",[22,4110,4111],{},[61,4112,4113],{},"Common Mistakes Avoided:",[55,4115,4116,4119,4122],{},[58,4117,4118],{},"No evals: Check value, not just output.",[58,4120,4121],{},"Overbuild RAGs on junk data.",[58,4123,4124],{},"Manual exhaustion: Automate later.",[22,4126,4127,4129],{},[61,4128,4042],{}," \"Unless we break down that monolith knowledge base into context blocks useful for agents, it won't work.\"",[17,4131,4133],{"id":4132},"hands-on-implementation-agentic-framework","Hands-On Implementation: Agentic Framework",[22,4135,4136],{},"Uses any agent framework (Claude demo for crowd, Copilot at IKEA). Components:",[55,4138,4139,4145,4151],{},[58,4140,4141,4144],{},[61,4142,4143],{},"Skills\u002FRules\u002FAgents\u002FHooks",": Custom for failure analysis, gap checklist, curation.",[58,4146,4147,4150],{},[61,4148,4149],{},"Knowledge Base",": Markdown files (entities as sections). Live updates visible.",[58,4152,4153,4156],{},[61,4154,4155],{},"Retrieval First",": Fetches monolith, then gap-finds if low confidence.",[22,4158,4159,4162],{},[61,4160,4161],{},"Demo Flow (Terminal\u002FClaude):"," Incident: \"Root cause high latency in service X.\" Agent scans monolith, lists 6 missing entities (e.g., notification logic). Provide info → Agent adds 5-6 more discovered entities. Re-run: Succeeds.",[22,4164,4165],{},"Scale manually painful after 1-2 cycles. Quality criteria: Confidence >4, zero critical gaps, full task completion.",[22,4167,4168,4170],{},[61,4169,4042],{}," \"One problem surfaced six entities never documented... it discovers gaps, stores new info.\"",[17,4172,4174],{"id":4173},"automate-at-scale-batch-historical-tickets","Automate at Scale: Batch Historical Tickets",[22,4176,4177],{},"Grab archived Jira\u002Fincidents (JSON\u002FMD with descriptions\u002Fcomments). Platform Ops Agent validates batch (20 incidents) against knowledge base:",[55,4179,4180,4183],{},[58,4181,4182],{},"Per ticket: Retrieve, score docs (trustworthy\u002Foutdated\u002Fmissing).",[58,4184,4185],{},"Aggregate: Surfaces enterprise-wide gaps.",[22,4187,4188],{},"Run cycles on history → Builds base before live use. Agents handle knowledge management autonomously.",[22,4190,4191,4194],{},[61,4192,4193],{},"Trade-offs:"," Initial failures expected (design goal). Requires domain experts briefly. Works on cloud\u002Flocal. At IKEA (100+ eng, 6 product teams): Powers delivery services.",[22,4196,4197,4200],{},[61,4198,4199],{},"Exercise:"," Pick 5 real tickets. Run cycle in your agent (Claude\u002FCopilot). Track entity growth, confidence. Prerequisites: Agent familiarity, engineering background, Markdown for docs.",[22,4202,4203,4205],{},[61,4204,4042],{}," \"We move agent from consumer to knowledge manager... the whole knowledge management is your job.\"",[17,4207,131],{"id":130},[55,4209,4210,4213,4216,4219,4222,4225,4228,4231],{},[58,4211,4212],{},"Start with real problems, not curated context—failures pinpoint exact gaps.",[58,4214,4215],{},"One cycle: Problem → Retrieve → Gap checklist → Fill → Curate Markdown blocks.",[58,4217,4218],{},"Repeat 10-15x on incidents: Confidence scales 1.4 → 4.4+; base self-improves.",[58,4220,4221],{},"Automate batch validation on historical tickets for enterprise scale.",[58,4223,4224],{},"Eval by task completion\u002FROI (Jira velocity), not output existence.",[58,4226,4227],{},"Tools: Claude\u002FCopilot + hooks; persist via MCP\u002FConfluence.",[58,4229,4230],{},"Avoid: RAG spam on tribal knowledge—demand-driven wins.",[58,4232,4233],{},"Fits broader workflow: Pre-agentic cleanup for production autonomy.",{"title":165,"searchDepth":166,"depth":166,"links":4235},[4236,4237,4238,4239,4240],{"id":4025,"depth":166,"text":4026},{"id":4046,"depth":166,"text":4047},{"id":4132,"depth":166,"text":4133},{"id":4173,"depth":166,"text":4174},{"id":130,"depth":166,"text":131},[174,237],{"content_references":4243,"triage":4259},[4244,4249,4254,4255,4257],{"type":4245,"title":4246,"author":4247,"publisher":4248,"context":183},"paper","Demand-Driven Context","Raj Navakoti","arXiv",{"type":4250,"title":4251,"author":4252,"context":4253},"report","AI Value Creation","McKinsey","cited",{"type":196,"title":4036,"context":183},{"type":181,"title":4256,"context":183},"Claude",{"type":181,"title":4258,"context":183},"Copilot",{"relevance":201,"novelty":202,"quality":202,"actionability":202,"composite":203,"reasoning":4260},"Category: AI Automation. The article provides a practical framework for improving AI agents' performance by addressing knowledge gaps through iterative learning from failures, which directly addresses the audience's need for actionable insights in AI product development. It presents a novel approach by comparing the process to TDD and Agile methodologies, enhancing its relevance and applicability.","\u002Fsummaries\u002Faf9f66e396aa16a3-build-knowledge-bases-from-agent-failures-summary","2026-05-05 13:00:06","2026-05-05 16:04:23",{"title":4015,"description":165},{"loc":4261},"0d47bf4474e015b1","AI Engineer","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=_QAVExf_1uw","summaries\u002Faf9f66e396aa16a3-build-knowledge-bases-from-agent-failures-summary",[217,218,220],"Assign real enterprise problems to AI agents; their failures reveal exact knowledge gaps. Fill them iteratively to create a demand-driven context base that makes agents semi-autonomous—far better than dumping uncurated RAG data.",[220],"lkkxNgonHbe1jTzHeQQOb__eyspMzd8MY1_XhZv0ZJM",{"id":4275,"title":4276,"ai":4277,"body":4282,"categories":4310,"created_at":175,"date_modified":175,"description":165,"extension":176,"faq":175,"featured":177,"kicker_label":175,"meta":4311,"navigation":205,"path":4322,"published_at":4323,"question":175,"scraped_at":4324,"seo":4325,"sitemap":4326,"source_id":4327,"source_name":4328,"source_type":3944,"source_url":4329,"stem":4330,"tags":4331,"thumbnail_url":175,"tldr":4332,"tweet":175,"unknown_tags":4333,"__hash__":4334},"summaries\u002Fsummaries\u002Fd954c8a65c048e0d-6-agentic-patterns-from-claude-design-for-vertical-summary.md","6 Agentic Patterns from Claude Design for Vertical Apps",{"provider":7,"model":8,"input_tokens":4278,"output_tokens":4279,"processing_time_ms":4280,"cost_usd":4281},6491,1608,24012,0.00207955,{"type":14,"value":4283,"toc":4305},[4284,4288,4291,4295,4298,4302],[17,4285,4287],{"id":4286},"ground-context-dynamically-before-generating","Ground Context Dynamically Before Generating",[22,4289,4290],{},"Never generate blindly—always ground your agent in user-specific data via progressive disclosure RAG. Claude Design forces users to build a detailed design system upfront (brand context, colors, fonts, HTML for buttons\u002Fcards), then the agent selectively pulls relevant chunks into its window per task, avoiding context bloat. Extend this: for sales agents, RAG over CRM data before outreach; for legal, load templated contracts before drafting. First output isn't the deliverable—it's a structured memory artifact (markdown, HTML\u002FCSS, or JSON) that persists across sessions and downstream agents. This memory boosts speed\u002Fquality on repeats since models now parse these formats natively. Trade-off: initial setup time, but it crushes static system prompts, which most enterprise agents still misuse.",[17,4292,4294],{"id":4293},"iterate-with-multimodal-ux-and-self-critique","Iterate with Multimodal UX and Self-Critique",[22,4296,4297],{},"Ditch chatbot-only interfaces; let the agent generate task-specific controls (sliders for email aggressiveness, layout tweaks) from its own tokens, rendered dynamically. Claude Design handles 5+ inputs—chat, voice, DOM hovers, sketches, screenshots—for natural refinement loops. After output, run a self-QA: render (e.g., screenshot), feed back to vision model (needs strong one like Opus 4.7), critique\u002Fiterate until it matches intent. Burns tokens but yields production quality before user sees it—apply to emails, contracts, PDFs, UIs. This fixes where most agents fail: rigid UX and unpolished drafts.",[17,4299,4301],{"id":4300},"generate-variations-proactively-and-handoff-seamlessly","Generate Variations Proactively and Handoff Seamlessly",[22,4303,4304],{},"Surface decisions hierarchically with multi-variation: output 2-3 options upfront (e.g., layouts > typography > colors), letting users pick axes like sales tone (warm vs. direct). Beats clarifying questions by showing trade-offs concretely, reducing back-and-forth. Finalize with handoff: export to portable formats (HTML\u002FCSS, PDF, PowerPoint) for tools like Figma, Canva, Claude Code, or other agents. Avoid proprietary traps—markdown\u002FJSON works everywhere. In multi-agent futures, this enables ecosystems; today, it matches user workflows. Stack all patterns (especially grounding + memory) for qualitative leaps—most deployments lack this dynamic harness.",{"title":165,"searchDepth":166,"depth":166,"links":4306},[4307,4308,4309],{"id":4286,"depth":166,"text":4287},{"id":4293,"depth":166,"text":4294},{"id":4300,"depth":166,"text":4301},[174],{"content_references":4312,"triage":4319},[4313,4316],{"type":196,"title":4314,"url":4315,"context":4253},"Claude Design Launch Blog","https:\u002F\u002Fwww.anthropic.com\u002Fnews\u002Fclaude-design-anthropic-labs",{"type":181,"title":4317,"url":4318,"context":183},"llm-tutorials","https:\u002F\u002Fgithub.com\u002Fsamwit\u002Fllm-tutorials",{"relevance":201,"novelty":202,"quality":202,"actionability":201,"composite":4320,"reasoning":4321},4.55,"Category: AI Automation. The article provides a detailed framework for building AI agents using specific patterns that can be directly applied to various vertical applications, addressing the audience's need for practical, actionable content. It outlines concrete steps like grounding agents in user data and iterating with multimodal UX, which are immediately actionable for product builders.","\u002Fsummaries\u002Fd954c8a65c048e0d-6-agentic-patterns-from-claude-design-for-vertical-summary","2026-05-01 16:35:00","2026-05-03 16:51:24",{"title":4276,"description":165},{"loc":4322},"5cddd7260212b0ec","Sam Witteveen","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=V-djAkt0t-M","summaries\u002Fd954c8a65c048e0d-6-agentic-patterns-from-claude-design-for-vertical-summary",[217,218,220],"Claude Design's edge comes from stacking 6 patterns—context grounding, structured memory, iterative multimodal refinement, self-QA, multi-variation generation, handoff—around a strong LLM like Opus 4.7. Build your legal, sales, or medical agents the same way: ground in user data first, then iterate with quality checks.",[220],"n3uXvaNagGSyL1X9ut5T7S8MZAsHzxmuChlPhnf-d4c"]