[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-54ccf33e4fd6400c-build-event-sourced-ai-agents-with-stream-processo-summary":3,"summaries-facets-categories":589,"summary-related-54ccf33e4fd6400c-build-event-sourced-ai-agents-with-stream-processo-summary":4211},{"id":4,"title":5,"ai":6,"body":13,"categories":546,"created_at":547,"date_modified":547,"description":132,"extension":548,"faq":547,"featured":549,"kicker_label":547,"meta":550,"navigation":164,"path":570,"published_at":571,"question":547,"scraped_at":572,"seo":573,"sitemap":574,"source_id":575,"source_name":576,"source_type":577,"source_url":578,"stem":579,"tags":580,"thumbnail_url":584,"tldr":585,"tweet":586,"unknown_tags":587,"__hash__":588},"summaries\u002Fsummaries\u002F54ccf33e4fd6400c-build-event-sourced-ai-agents-with-stream-processo-summary.md","Build Event-Sourced AI Agents with Stream Processors",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","x-ai\u002Fgrok-4.1-fast",8703,2623,34569,0.00302945,{"type":14,"value":15,"toc":539},"minimark",[16,21,32,35,87,95,101,105,108,123,126,373,381,387,398,402,405,416,419,433,439,445,449,452,455,484,487,490,493,496,499,502,506,535],[17,18,20],"h2",{"id":19},"event-stream-as-the-sole-primitive-for-agents","Event Stream as the Sole Primitive for Agents",[22,23,24,25,31],"p",{},"The foundation is a simple event log at events.iterate.com, where every interaction—user inputs, LLM streaming chunks, tool calls, errors, circuit breakers—is an immutable event with type, optional payload, stream path, offset, and timestamp. Append events via POST \u002F:path with JSON or raw payloads; invalid inputs auto-generate error events like ",[26,27,28],"a",{"href":28,"rel":29},"https:\u002F\u002Fevents.iterate.com\u002Finvalid-event-appended",[30],"nofollow",".",[22,33,34],{},"Key operations enable agent-like behavior without custom servers:",[36,37,38,46,52,67,77],"ul",{},[39,40,41,45],"li",{},[42,43,44],"strong",{},"Streaming reads",": GET \u002F:path?live=true for Server-Sent Events (SSE) tailing new events indefinitely.",[39,47,48,51],{},[42,49,50],{},"Idempotency",": Include X-Idempotency-Key header to dedupe retries.",[39,53,54,57,58,62,63,31],{},[42,55,56],{},"Pausing\u002Fresuming",": Append ",[26,59,60],{"href":60,"rel":61},"https:\u002F\u002Fevents.iterate.com\u002Fstream-paused?reason=DEMO",[30]," to halt appends (prevents infinite loops); resume with ",[26,64,65],{"href":65,"rel":66},"https:\u002F\u002Fevents.iterate.com\u002Fstream-resumed",[30],[39,68,69,57,72,76],{},[42,70,71],{},"Scheduling",[26,73,74],{"href":74,"rel":75},"https:\u002F\u002Fevents.iterate.com\u002Fschedule?delayMs=5000&eventType=heartbeat",[30]," for future events (e.g., heartbeats every 5s or timed tasks); cancel with matching idempotency.",[39,78,79,57,82,86],{},[42,80,81],{},"Subscriptions",[26,83,84],{"href":84,"rel":85},"https:\u002F\u002Fevents.iterate.com\u002Fsubscribe-push?targetUrl=https:\u002F\u002Fyour-server.com",[30]," for outbound webhooks on new events.",[22,88,89,90,94],{},"Circuit breakers auto-pause after 100 events\u002Fsec, ensuring stability. This setup mimics agent logs (e.g., Claude\u002FPi traces) but makes ",[91,92,93],"em",{},"everything"," replayable: on restart after 100 events, derive full state without re-calling LLMs.",[22,96,97,100],{},[42,98,99],{},"Common pitfall",": Forgetting paths start with \u002F (URL-encode if nested). Use project slugs via X-Project-Slug header for isolated namespaces during experiments.",[17,102,104],{"id":103},"stream-processor-reducer-side-effects-hook","Stream Processor: Reducer + Side-Effects Hook",[22,106,107],{},"A processor is pure JS\u002FTS code with two parts:",[109,110,111,117],"ol",{},[39,112,113,116],{},[42,114,115],{},"Synchronous reducer",": Function deriving state from events. Input: array of events; output: new state (JSON-serializable). Runs on every append, replaying from offset 0 for consistency.",[39,118,119,122],{},[42,120,121],{},"Async after-append hook",": Triggered post-reduce, for side effects like LLM calls or tools. Input: current state + latest event; no state mutation.",[22,124,125],{},"Example processor (from workshop repo):",[127,128,133],"pre",{"className":129,"code":130,"language":131,"meta":132,"style":132},"language-typescript shiki shiki-themes github-light github-dark","import { EventsClient } from '@iterate-labs\u002Fai-engineer-workshop';\n\nconst processor = {\n  reduce(events: any[]) {\n    return {\n      messages: events.filter(e => e.type === 'user_message').map(e => e.payload),\n      assistant: events.filter(e => e.type === 'assistant_message'),\n    };\n  },\n  async afterAppend(state, event) {\n    if (event.type === 'user_message') {\n      const messages = [...state.messages, event.payload];\n      \u002F\u002F Call LLM here, append chunks as events\n    }\n  }\n};\n","typescript","",[134,135,136,159,166,182,205,213,254,278,284,290,313,328,348,355,361,367],"code",{"__ignoreMap":132},[137,138,141,145,149,152,156],"span",{"class":139,"line":140},"line",1,[137,142,144],{"class":143},"szBVR","import",[137,146,148],{"class":147},"sVt8B"," { EventsClient } ",[137,150,151],{"class":143},"from",[137,153,155],{"class":154},"sZZnC"," '@iterate-labs\u002Fai-engineer-workshop'",[137,157,158],{"class":147},";\n",[137,160,162],{"class":139,"line":161},2,[137,163,165],{"emptyLinePlaceholder":164},true,"\n",[137,167,169,172,176,179],{"class":139,"line":168},3,[137,170,171],{"class":143},"const",[137,173,175],{"class":174},"sj4cs"," processor",[137,177,178],{"class":143}," =",[137,180,181],{"class":147}," {\n",[137,183,185,189,192,196,199,202],{"class":139,"line":184},4,[137,186,188],{"class":187},"sScJk","  reduce",[137,190,191],{"class":147},"(",[137,193,195],{"class":194},"s4XuR","events",[137,197,198],{"class":143},":",[137,200,201],{"class":174}," any",[137,203,204],{"class":147},"[]) {\n",[137,206,208,211],{"class":139,"line":207},5,[137,209,210],{"class":143},"    return",[137,212,181],{"class":147},[137,214,216,219,222,224,227,230,233,236,239,242,245,247,249,251],{"class":139,"line":215},6,[137,217,218],{"class":147},"      messages: events.",[137,220,221],{"class":187},"filter",[137,223,191],{"class":147},[137,225,226],{"class":194},"e",[137,228,229],{"class":143}," =>",[137,231,232],{"class":147}," e.type ",[137,234,235],{"class":143},"===",[137,237,238],{"class":154}," 'user_message'",[137,240,241],{"class":147},").",[137,243,244],{"class":187},"map",[137,246,191],{"class":147},[137,248,226],{"class":194},[137,250,229],{"class":143},[137,252,253],{"class":147}," e.payload),\n",[137,255,257,260,262,264,266,268,270,272,275],{"class":139,"line":256},7,[137,258,259],{"class":147},"      assistant: events.",[137,261,221],{"class":187},[137,263,191],{"class":147},[137,265,226],{"class":194},[137,267,229],{"class":143},[137,269,232],{"class":147},[137,271,235],{"class":143},[137,273,274],{"class":154}," 'assistant_message'",[137,276,277],{"class":147},"),\n",[137,279,281],{"class":139,"line":280},8,[137,282,283],{"class":147},"    };\n",[137,285,287],{"class":139,"line":286},9,[137,288,289],{"class":147},"  },\n",[137,291,293,296,299,301,304,307,310],{"class":139,"line":292},10,[137,294,295],{"class":143},"  async",[137,297,298],{"class":187}," afterAppend",[137,300,191],{"class":147},[137,302,303],{"class":194},"state",[137,305,306],{"class":147},", ",[137,308,309],{"class":194},"event",[137,311,312],{"class":147},") {\n",[137,314,316,319,322,324,326],{"class":139,"line":315},11,[137,317,318],{"class":143},"    if",[137,320,321],{"class":147}," (event.type ",[137,323,235],{"class":143},[137,325,238],{"class":154},[137,327,312],{"class":147},[137,329,331,334,337,339,342,345],{"class":139,"line":330},12,[137,332,333],{"class":143},"      const",[137,335,336],{"class":174}," messages",[137,338,178],{"class":143},[137,340,341],{"class":147}," [",[137,343,344],{"class":143},"...",[137,346,347],{"class":147},"state.messages, event.payload];\n",[137,349,351],{"class":139,"line":350},13,[137,352,354],{"class":353},"sJ8bj","      \u002F\u002F Call LLM here, append chunks as events\n",[137,356,358],{"class":139,"line":357},14,[137,359,360],{"class":147},"    }\n",[137,362,364],{"class":139,"line":363},15,[137,365,366],{"class":147},"  }\n",[137,368,370],{"class":139,"line":369},16,[137,371,372],{"class":147},"};\n",[22,374,375,376,380],{},"Deploy by appending a ",[26,377,378],{"href":378,"rel":379},"https:\u002F\u002Fevents.iterate.com\u002Fdynamic-worker-configured",[30]," event with processor source as payload string. The service isolates and runs it in a sandboxed worker per stream—polyglot in principle (docs at events.iterate.com\u002Fapidocs for other langs).",[22,382,383,386],{},[42,384,385],{},"Quality criteria",": Reducer must be pure\u002Fdeterministic (no side effects, I\u002FO). State should capture only essentials for decision-making (e.g., message history, not raw chunks). Test by replaying event logs: curl full history, pipe to jq, verify state.",[22,388,389,392,393,397],{},[42,390,391],{},"Pitfall avoidance",": Avoid LLM calls in reducer (blocks replay). Use hooks for async work. Handle streaming: append partial tokens as ",[26,394,395],{"href":395,"rel":396},"https:\u002F\u002Fevents.iterate.com\u002Fllm-chunk",[30]," events.",[17,399,401],{"id":400},"composing-processors-for-extensible-agents","Composing Processors for Extensible Agents",[22,403,404],{},"Multiple processors attach to one stream via separate dynamic-worker-configured events. They run in parallel:",[36,406,407,410,413],{},[39,408,409],{},"Author's processor: Core agent logic (e.g., OpenAI chat).",[39,411,412],{},"Safety checker: Injects context pre-LLM (e.g., append guardrail event in 200ms window).",[39,414,415],{},"External: Rust\u002FTS plugins from different servers compose seamlessly.",[22,417,418],{},"Example flow:",[109,420,421,424,427,430],{},[39,422,423],{},"User appends message.",[39,425,426],{},"All processors reduce to their state.",[39,428,429],{},"Hooks fire: Safety checks, then LLM call, append response chunks.",[39,431,432],{},"Replay skips LLM re-runs via reducer.",[22,434,435,438],{},[42,436,437],{},"Trade-offs",": Gains composability (mix\u002Fmatch extensions), distribution (edge-deployed, HTTP-only). Risks: Races\u002Floops (mitigate with pausing, idempotency). No auth (rotate secrets post-demo).",[22,440,441,444],{},[42,442,443],{},"Before\u002Fafter",": Naive agent: Opaque traces, non-replayable side effects. This: Full event log as single source of truth, URL per agent (\u002Fjonas\u002Fagent1), webhooks\u002Fforms as inputs.",[17,446,448],{"id":447},"hands-on-from-curl-to-full-agent","Hands-On: From Curl to Full Agent",[22,450,451],{},"Prerequisites: Node\u002FTS basics, agent familiarity (e.g., function calling). Fits early in workflow: Prototype before frameworks like LangChain.",[22,453,454],{},"Steps to build:",[109,456,457,460,466,472,478,481],{},[39,458,459],{},"Clone github.com\u002Fiterate\u002Fai-engineer-workshop, npm i.",[39,461,462,463],{},"Create client: ",[134,464,465],{},"const client = createEventsClient({ baseUrl: 'https:\u002F\u002Fevents.iterate.com', pathPrefix: '\u002Fyourname\u002Fagent' });",[39,467,468,469],{},"Append init event: ",[134,470,471],{},"await client.append({ type: 'user_message', payload: 'Hello' });",[39,473,474,475],{},"Tail live: ",[134,476,477],{},"client.tail({ live: true }, console.log);",[39,479,480],{},"Define\u002Fdeploy processor: Serialize as string, append dynamic-worker-configured.",[39,482,483],{},"Extend: Append JSON transformer for event rewriting; schedule tools.",[22,485,486],{},"Exercise: Build coding agent—append code events, reduce to context window, hook to LLM for edits. Combine with external webhook for GitHub PRs.",[22,488,489],{},"\"The split matters: when your program restarts after 100 events, you want to catch up state without replaying LLM requests.\"",[22,491,492],{},"\"Dynamic worker configured... Append it to any stream and that stream becomes an AI agent without server or dependencies.\"",[22,494,495],{},"\"Processors from different authors on different servers can compose against the same stream.\"",[22,497,498],{},"\"Everything that happens (streaming chunks, tool calls, errors, circuit breaker triggers) is an event in the log.\"",[22,500,501],{},"\"I would like to build agent harnesses... purely event sourced. Aka debugable.\"",[17,503,505],{"id":504},"key-takeaways","Key Takeaways",[36,507,508,511,514,517,520,523,526,529,532],{},[39,509,510],{},"Start every agent with an event stream: Append user inputs\u002Ftools as typed events; tail via SSE for real-time.",[39,512,513],{},"Implement processors as {reduce(events), afterAppend(state, event)}—pure sync state, async effects only.",[39,515,516],{},"Deploy dynamically: POST processor JS as event payload; runs isolated per stream.",[39,518,519],{},"Prevent loops: Use pausing, idempotency, rate limits out-of-box.",[39,521,522],{},"Compose boldly: Multiple workers per stream enable plugins\u002Fsafety without forking codebases.",[39,524,525],{},"Debug via replay: Curl full log, reduce manually to verify state sans LLMs.",[39,527,528],{},"Edge-first: Agents get public URLs instantly; HTTP webhooks\u002Fforms as inputs\u002Foutputs.",[39,530,531],{},"Polyglot\u002Fextensible: TS SDK for workshop, but curl\u002FOpenAPI for any lang.",[39,533,534],{},"Test rigorously: Simulate 100+ events, pause\u002Fresume, check reducer purity.",[536,537,538],"style",{},"html pre.shiki code .szBVR, html code.shiki .szBVR{--shiki-default:#D73A49;--shiki-dark:#F97583}html pre.shiki code .sVt8B, html code.shiki .sVt8B{--shiki-default:#24292E;--shiki-dark:#E1E4E8}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}html pre.shiki code .sScJk, html code.shiki .sScJk{--shiki-default:#6F42C1;--shiki-dark:#B392F0}html pre.shiki code .s4XuR, html code.shiki .s4XuR{--shiki-default:#E36209;--shiki-dark:#FFAB70}html pre.shiki code .sJ8bj, html code.shiki .sJ8bj{--shiki-default:#6A737D;--shiki-dark:#6A737D}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":132,"searchDepth":161,"depth":161,"links":540},[541,542,543,544,545],{"id":19,"depth":161,"text":20},{"id":103,"depth":161,"text":104},{"id":400,"depth":161,"text":401},{"id":447,"depth":161,"text":448},{"id":504,"depth":161,"text":505},[],null,"md",false,{"content_references":551,"triage":567},[552,557,561,564],{"type":553,"title":554,"url":555,"context":556},"tool","events.iterate.com","https:\u002F\u002Fevents.iterate.com","mentioned",{"type":553,"title":558,"url":559,"context":560},"@iterate-labs\u002Fai-engineer-workshop","https:\u002F\u002Fgithub.com\u002Fiterate\u002Fai-engineer-workshop","recommended",{"type":562,"title":563,"url":559,"context":556},"other","iterate\u002Fai-engineer-workshop repo",{"type":562,"title":565,"url":566,"context":556},"jonastemplestein GitHub","https:\u002F\u002Fgithub.com\u002Fjonastemplestein",{"relevance":207,"novelty":184,"quality":184,"actionability":207,"composite":568,"reasoning":569},4.55,"Category: AI & LLMs. The article provides a detailed framework for building event-sourced AI agents, addressing practical applications for developers looking to integrate AI features into their products. It includes specific operations and examples that can be directly implemented, making it highly actionable.","\u002Fsummaries\u002F54ccf33e4fd6400c-build-event-sourced-ai-agents-with-stream-processo-summary","2026-05-14 14:00:06","2026-05-14 19:00:15",{"title":5,"description":132},{"loc":570},"54ccf33e4fd6400c","AI Engineer","video","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=vi-2nasppAg","summaries\u002F54ccf33e4fd6400c-build-event-sourced-ai-agents-with-stream-processo-summary",[581,131,582,583],"agents","automation","ai-tools","https:\u002F\u002Fi.ytimg.com\u002Fvi\u002Fvi-2nasppAg\u002Fhqdefault.jpg","Create debuggable, composable agent harnesses using event logs, synchronous reducers for state, and dynamic JS processors appended as events—no servers or deployments required.","Live workshop where Jonas Templestein demos building an event-sourced agent harness on [events.iterate.com](https:\u002F\u002Fevents.iterate.com) (not linked), using curl to append events like \"dynamic 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Pi Coding Agents via CLI Tools in Products",{"provider":7,"model":8,"input_tokens":4216,"output_tokens":4217,"processing_time_ms":4218,"cost_usd":4219},7151,1918,24178,0.00236655,{"type":14,"value":4221,"toc":4252},[4222,4226,4229,4232,4236,4239,4242,4246,4249],[17,4223,4225],{"id":4224},"pis-core-mechanics-for-custom-product-agents","Pi's Core Mechanics for Custom Product Agents",[22,4227,4228],{},"Pi is a minimal TypeScript SDK for building coding agents: an LLM runs tools in a loop with goals and context, using agent core for prompting, events, and hooks. Instantiate an Agent class, inject context or prompts, and subscribe to events like tool calls succeeding (checkmarks in streams). Hooks before tool calls enable checks like role-based access without updating contacts prematurely. For coding, add a runtime shell (Bash) where agents discover tools like ffmpeg for untaught tasks (e.g., voice messages), creating the illusion of learning. Extensions add session events and UI interactions: select CRM leads via dropdowns in terminal or web UIs Pi generates. OpenClaw extends Pi for multi-channel sessions, threads, and plugins (routing, sub-agents), reusing Pi's session support, coding agent, agent core, LM abstraction, and terminal UI.",[22,4230,4231],{},"Build simple agents first: a 3-file TypeScript CRM lead qualifier with commands like \"show all leads and score them\" uses tools for listing\u002Fscoring, steered by system prompts describing tools. Sessions persist context across interactions, ideal for ongoing tasks.",[17,4233,4235],{"id":4234},"architectural-principle-design-for-agent-strengths","Architectural Principle: Design for Agent Strengths",[22,4237,4238],{},"Make systems agent-friendly: agents excel at stitching simple tools, so expose data access via CLIs rather than complex APIs. CLIs match agent skills (Bash shell), avoiding compensation for messy interfaces. Example: Cowork bundles Excel skills using small CLIs (pandas, openpyxl, LibreOffice) instead of direct Excel interaction, yielding strong reception in finance tools.",[22,4240,4241],{},"No established patterns exist—experiment in the \"fuck around and find out\" phase. Tinker with Pi: ask it to build features via system prompts; rip apart\u002Freassemble its open-source minimalism. Emerging pattern: one-thing-well programs (Ken Thompson\u002FUnix) compose into agent power. Secure with sandboxes; explore Nvidia's OpenClaw policy\u002Fopen shell for agent isolation.",[17,4243,4245],{"id":4244},"real-world-embedding-b2b-sales-pipeline","Real-World Embedding: B2B Sales Pipeline",[22,4247,4248],{},"Route incoming RFP emails to per-customer agent sessions: monitor inbox, gateway routes to sessions (reuse for context), using agent.md (role\u002Fsystem instructions) and customer.md (quirks, discounts, access). Tools as CLIs query CRM\u002FERP securely in sandboxes, pulling leads\u002Forders. Agent loops tools to analyze RFPs, generating draft responses in the inbox—humans edit without leaving email.",[22,4250,4251],{},"Dashboard shows cases (sessions), tool calls (e.g., German apologies handled), and threads. Output: RFP email triggers draft; ignored emails skipped. Scales to multiple agents\u002Fthreads. Key: humans see only polished drafts; agents handle complexity underground. Pi perfect for this—minimal, extensible; bet on coding agents as core building blocks.",{"title":132,"searchDepth":161,"depth":161,"links":4253},[4254,4255,4256],{"id":4224,"depth":161,"text":4225},{"id":4234,"depth":161,"text":4235},{"id":4244,"depth":161,"text":4245},[601],{"content_references":4259,"triage":4269},[4260,4263,4265,4267],{"type":553,"title":4261,"author":4262,"context":560},"Pi","Mario",{"type":553,"title":4264,"context":556},"OpenClaw",{"type":553,"title":4266,"context":556},"Cowork",{"type":562,"title":4268,"context":556},"Nvidia OpenClaw Policy\u002FOpen Shell",{"relevance":207,"novelty":184,"quality":184,"actionability":184,"composite":4270,"reasoning":4271},4.35,"Category: AI & LLMs. The article provides a detailed overview of using Pi's TypeScript SDK to build coding agents, addressing practical applications for integrating AI tools into products, which aligns with the audience's needs. It includes specific examples of how to implement agents in a B2B sales context, making it actionable for developers and founders.","\u002Fsummaries\u002F490adef2a9996480-embed-pi-coding-agents-via-cli-tools-in-products-summary","2026-05-11 17:00:06","2026-05-12 15:00:15",{"title":4214,"description":132},{"loc":4272},"490adef2a9996480","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=vAIDdLKB6-w","summaries\u002F490adef2a9996480-embed-pi-coding-agents-via-cli-tools-in-products-summary",[581,131,583,582],"https:\u002F\u002Fi.ytimg.com\u002Fvi\u002FvAIDdLKB6-w\u002Fhqdefault.jpg","Pi's minimal TypeScript SDK powers LLM agents that loop tools; expose CRM\u002FERP data as secure CLIs for natural agent use, as in a B2B sales pipeline routing RFP emails to per-customer sessions that output inbox drafts.","Conference talk by [Matthias Luebken](https:\u002F\u002Fx.com\u002Fluebken) demoing how to embed the Pi coding agent SDK (which powers OpenClaw) into a B2B sales product: RFP emails route to per-customer agent sessions that pull CRM\u002FERP data via CLIs and output draft responses. Core advice: simplify data access and tools to match agent capabilities rather than adding complexity.",[],"s9big88RR4wfZ2gFV9rIsKpBAdm0oGzfFUhcLbzMSTo",{"id":4287,"title":4288,"ai":4289,"body":4294,"categories":4322,"created_at":547,"date_modified":547,"description":132,"extension":548,"faq":547,"featured":549,"kicker_label":547,"meta":4323,"navigation":164,"path":4344,"published_at":4345,"question":547,"scraped_at":4346,"seo":4347,"sitemap":4348,"source_id":4349,"source_name":4350,"source_type":4351,"source_url":4352,"stem":4353,"tags":4354,"thumbnail_url":547,"tldr":4355,"tweet":547,"unknown_tags":4356,"__hash__":4357},"summaries\u002Fsummaries\u002Fc76472bc1a134239-notion-s-platform-turns-workspaces-into-ai-agent-h-summary.md","Notion's Platform Turns Workspaces into AI Agent Hubs",{"provider":7,"model":8,"input_tokens":4290,"output_tokens":4291,"processing_time_ms":4292,"cost_usd":4293},5663,2258,29705,0.0022391,{"type":14,"value":4295,"toc":4317},[4296,4300,4303,4307,4310,4314],[17,4297,4299],{"id":4298},"run-custom-code-and-logic-without-external-infra","Run Custom Code and Logic Without External Infra",[22,4301,4302],{},"Notion Workers provide a cloud-based sandbox for deploying custom code securely, enabling data syncs into Notion databases, custom tool building, and webhook triggers for actions across apps. Skip third-party platforms or self-hosted scripts—use your preferred AI coding agent to generate the code. Workers share the same credit system as Custom Agents (over 1 million built since February launch) and stay free through August for experimentation. This overcomes prior limits where agents couldn't handle custom logic or external data.",[17,4304,4306],{"id":4305},"sync-live-data-from-any-api-into-workflows","Sync Live Data from Any API into Workflows",[22,4308,4309],{},"Pull real-time data from databases like Salesforce, Zendesk, or Postgres directly into Notion via Workers-powered syncs. Notion databases become a unified canvas powering agents and multi-step automations, coordinating across tools without manual workarounds.",[17,4311,4313],{"id":4312},"integrate-and-control-external-agents-seamlessly","Integrate and Control External Agents Seamlessly",[22,4315,4316],{},"Chat with, assign tasks to, and track progress from partner agents like Claude Code, Cursor, Codex, and Decagon as if they were native. Use the External Agent API to connect internal company agents. Build agent tools with custom logic when Model Context Protocol (MCP) falls short. Access via Notion CLI on Business\u002FEnterprise plans, shifting Notion from note-taker to programmable orchestration layer for agentic AI.",{"title":132,"searchDepth":161,"depth":161,"links":4318},[4319,4320,4321],{"id":4298,"depth":161,"text":4299},{"id":4305,"depth":161,"text":4306},{"id":4312,"depth":161,"text":4313},[619],{"content_references":4324,"triage":4342},[4325,4328,4331,4334,4336,4338,4340],{"type":562,"title":4326,"url":4327,"context":556},"Introducing Custom Agents","https:\u002F\u002Fwww.notion.com\u002Fblog\u002Fintroducing-custom-agents",{"type":309,"title":4329,"url":4330,"context":556},"Notion Product Announcement Livestream","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=rpE2rzKO6L0",{"type":553,"title":4332,"url":4333,"context":556},"Notion CLI","https:\u002F\u002Fdevelopers.notion.com\u002Fcli\u002Fget-started\u002Foverview",{"type":553,"title":4335,"context":556},"Claude Code",{"type":553,"title":4337,"context":556},"Cursor",{"type":553,"title":4339,"context":556},"Codex",{"type":553,"title":4341,"context":556},"Decagon",{"relevance":207,"novelty":184,"quality":184,"actionability":184,"composite":4270,"reasoning":4343},"Category: AI Automation. The article discusses Notion's new features that allow users to create AI workflows and integrate external agents, addressing the audience's need for practical AI tooling. It provides specific details about how to implement these features, making it actionable for product builders.","\u002Fsummaries\u002Fc76472bc1a134239-notion-s-platform-turns-workspaces-into-ai-agent-h-summary","2026-05-13 21:45:09","2026-05-13 23:00:26",{"title":4288,"description":132},{"loc":4344},"c76472bc1a134239","TechCrunch — AI","article","https:\u002F\u002Ftechcrunch.com\u002F2026\u002F05\u002F13\u002Fnotion-just-turned-its-workspace-into-a-hub-for-ai-agents\u002F","summaries\u002Fc76472bc1a134239-notion-s-platform-turns-workspaces-into-ai-agent-h-summary",[581,583,582],"Notion's Developer Platform adds Workers for custom code, API data syncs, and external agent integration to orchestrate multi-step AI workflows without external infrastructure.",[],"-QnrJ8-k9vXJ0VLkPcVK-LovIFelyDTaXxUVRh5ZkEw",{"id":4359,"title":4360,"ai":4361,"body":4366,"categories":4402,"created_at":547,"date_modified":547,"description":132,"extension":548,"faq":547,"featured":549,"kicker_label":547,"meta":4403,"navigation":164,"path":4413,"published_at":4414,"question":547,"scraped_at":4415,"seo":4416,"sitemap":4417,"source_id":4418,"source_name":4419,"source_type":4351,"source_url":4420,"stem":4421,"tags":4422,"thumbnail_url":547,"tldr":4423,"tweet":547,"unknown_tags":4424,"__hash__":4425},"summaries\u002Fsummaries\u002Fcfba085e5ebce4be-codex-chrome-extension-gives-ai-agents-signed-in-b-summary.md","Codex Chrome Extension Gives AI Agents Signed-In Browser Access",{"provider":7,"model":8,"input_tokens":4362,"output_tokens":4363,"processing_time_ms":4364,"cost_usd":4365},7445,1582,27656,0.0022575,{"type":14,"value":4367,"toc":4397},[4368,4372,4375,4379,4390,4394],[17,4369,4371],{"id":4370},"multi-tier-browser-strategy-for-agent-tasks","Multi-Tier Browser Strategy for Agent Tasks",[22,4373,4374],{},"Codex handles browser tasks across three tiers based on needs: dedicated plugins for services like GitHub, Slack, Figma, and Notion; the new Chrome extension for signed-in sites requiring real browser state (e.g., LinkedIn, Salesforce, Gmail, internal tools); and the in-app sandboxed browser for localhost, local dev servers, file previews, or public pages. The agent automatically picks the right tier, preventing interference with your main browsing—Chrome actions occur in isolated tab groups, allowing parallel use of DevTools or tab context collection. This setup streamlines workflows previously blocked by API gaps, enabling web app testing and context gathering from open tabs without disrupting your session.",[17,4376,4378],{"id":4377},"prompt-driven-chrome-invocation","Prompt-Driven Chrome Invocation",[22,4380,4381,4382,4385,4386,4389],{},"Invoke the Chrome extension directly in prompts with ",[134,4383,4384],{},"@Chrome",", such as ",[134,4387,4388],{},"@Chrome open Salesforce and update the account from these call notes",". If Chrome is closed, Codex opens it. Combine with existing tools for hybrid tasks, like pulling data from signed-in CRM then processing locally. Available on macOS and Windows (not EU\u002FUK), installation involves five steps to link Codex to your browser profile, detailed in docs.",[17,4391,4393],{"id":4392},"permissions-and-security-trade-offs","Permissions and Security Trade-offs",[22,4395,4396],{},"The extension demands broad permissions (history, bookmarks, page data) for agent control, balanced by per-site confirmations, allow\u002Fblock lists, and manual session approvals for sensitive features. Risks include prompt injection from malicious sites; mitigate by disabling Memories to isolate sessions and prevent cross-contamination. OpenAI stores browser data only when explicitly added to chat context via screenshots or summaries, prioritizing privacy. Developers gain production-ready access to authenticated web flows but must weigh isolation needs against convenience.",{"title":132,"searchDepth":161,"depth":161,"links":4398},[4399,4400,4401],{"id":4370,"depth":161,"text":4371},{"id":4377,"depth":161,"text":4378},{"id":4392,"depth":161,"text":4393},[601],{"content_references":4404,"triage":4411},[4405,4408],{"type":553,"title":4406,"url":4407,"context":560},"Codex Chrome Extension","https:\u002F\u002Fchromewebstore.google.com\u002Fdetail\u002Fcodex\u002Fhehggadaopoacecdllhhajmbjkdcmajg",{"type":562,"title":4409,"url":4410,"context":560},"Full Docs","https:\u002F\u002Fdevelopers.openai.com\u002Fcodex\u002Fapp\u002Fchrome-extension",{"relevance":207,"novelty":184,"quality":184,"actionability":184,"composite":4270,"reasoning":4412},"Category: AI Automation. The article discusses a practical application of AI agents using a Chrome extension to enhance productivity by automating tasks across various platforms, addressing the audience's need for actionable AI tools. It provides specific details on how to invoke the extension and its implications for workflow optimization, making it relevant and actionable.","\u002Fsummaries\u002Fcfba085e5ebce4be-codex-chrome-extension-gives-ai-agents-signed-in-b-summary","2026-05-08 22:22:41","2026-05-09 15:37:21",{"title":4360,"description":132},{"loc":4413},"cfba085e5ebce4be","MarkTechPost","https:\u002F\u002Fwww.marktechpost.com\u002F2026\u002F05\u002F08\u002Fopenai-adds-chrome-extension-to-codex-letting-its-ai-agent-access-linkedin-salesforce-gmail-and-internal-tools-via-signed-in-sessions\u002F","summaries\u002Fcfba085e5ebce4be-codex-chrome-extension-gives-ai-agents-signed-in-b-summary",[581,583,582],"OpenAI's Codex Chrome extension lets its AI agent use your signed-in Chrome sessions for tasks on LinkedIn, Salesforce, Gmail, and internal tools, auto-selecting from plugins, Chrome, or in-app browser tiers.",[],"b7vWCFyxTpPqPIKmgqGrusNZz3iLtfcELDKk-vQ1qUY",{"id":4427,"title":4428,"ai":4429,"body":4434,"categories":4466,"created_at":547,"date_modified":547,"description":132,"extension":548,"faq":547,"featured":549,"kicker_label":547,"meta":4467,"navigation":164,"path":4475,"published_at":4476,"question":547,"scraped_at":4477,"seo":4478,"sitemap":4479,"source_id":4480,"source_name":4481,"source_type":4351,"source_url":4482,"stem":4483,"tags":4484,"thumbnail_url":547,"tldr":4485,"tweet":4486,"unknown_tags":4487,"__hash__":4488},"summaries\u002Fsummaries\u002F08c91534732e25d0-codex-chrome-extension-automates-browsers-via-natu-summary.md","Codex Chrome Extension Automates Browsers via Natural Language",{"provider":7,"model":8,"input_tokens":4430,"output_tokens":4431,"processing_time_ms":4432,"cost_usd":4433},4605,1353,17124,0.00157485,{"type":14,"value":4435,"toc":4461},[4436,4440,4443,4447,4450,4454],[17,4437,4439],{"id":4438},"setup-connect-extension-directly-in-codex","Setup: Connect Extension Directly in Codex",[22,4441,4442],{},"Install the Codex Chrome extension on any Chromium-based browser (Chrome, Brave, Edge) without manual Chrome Web Store steps. In the Codex app, navigate to favorite apps, select the Chrome extension option—which links to OpenAI's setup page—and add it. This grants Codex browser control permissions. A dedicated browser skill enhances efficiency for tasks like navigation and interaction. Once connected, Codex handles automation hands-free, clicking elements and filling forms based on natural language prompts.",[17,4444,4446],{"id":4445},"capabilities-automate-web-workflows-and-ui-testing","Capabilities: Automate Web Workflows and UI Testing",[22,4448,4449],{},"Codex turns browsers into agent-controlled environments for complex tasks. Use prompts like \"use your Chrome extension, go to this website, and post a question to the council: is a hot dog a sandwich?\" to trigger actions: open tabs, click buttons (e.g., start new discussion), type queries, and submit. It operates independently—user hands-off—while providing status updates for confirmation (e.g., \"yes\" to proceed). This excels for UI testing, debugging live apps, or repetitive web ops, outperforming manual scripting by handling dynamic sites via vision and reasoning.",[17,4451,4453],{"id":4452},"real-world-test-interacting-with-llm-council-plus","Real-World Test: Interacting with LLM Council Plus",[22,4455,4456,4457,31],{},"In a demo, Codex queried a custom LLM Council Plus deployment—a fork of Andrej Karpathy's project supporting up to 8 models. The council featured DeepSeek V4 Flash, Granite 4.1 on Llama, and Gemini 3.1 as chairman. Codex navigated the site, initiated a debate on \"hot dog as sandwich,\" routed the query, awaited peer-ranked responses (models anonymously score each other to reduce bias), and retrieved the verdict: \"technically and legally no, though culinarily debated.\" This validates Codex for end-to-end agent-browser loops, settling AI debates autonomously. Repo: ",[26,4458,4459],{"href":4459,"rel":4460},"https:\u002F\u002Fgithub.com\u002Fjacob-bd\u002Fllm-council-plus",[30],{"title":132,"searchDepth":161,"depth":161,"links":4462},[4463,4464,4465],{"id":4438,"depth":161,"text":4439},{"id":4445,"depth":161,"text":4446},{"id":4452,"depth":161,"text":4453},[601],{"content_references":4468,"triage":4473},[4469,4470],{"type":553,"title":4406,"url":4410,"context":556},{"type":562,"title":4471,"author":4472,"url":4459,"context":556},"LLM Council Plus GitHub Repo","jacob-bd",{"relevance":207,"novelty":184,"quality":184,"actionability":184,"composite":4270,"reasoning":4474},"Category: AI Automation. The article provides a detailed overview of how to use OpenAI's Codex extension for automating browser tasks, which directly addresses the audience's need for practical applications of AI tools. It includes specific examples of commands and workflows that users can implement, enhancing its actionability.","\u002Fsummaries\u002F08c91534732e25d0-codex-chrome-extension-automates-browsers-via-natu-summary","2026-05-07 22:26:16","2026-05-08 11:19:36",{"title":4428,"description":132},{"loc":4475},"afd53b896c7cfd18","Gen AI Spotlight","https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=xTIrCNO7RkY","summaries\u002F08c91534732e25d0-codex-chrome-extension-automates-browsers-via-natu-summary",[583,581,582],"Install OpenAI's Codex extension on Chromium browsers like Brave to control web tasks—navigate sites, post queries—with plain English commands, as demoed debugging an LLM Council app.","Quick demo of installing OpenAI's Codex Chrome extension on Brave, then using it to navigate the creator's LLM Council site (a Karpathy fork) and post the \"hot dog sandwich\" question for a model debate.",[],"28TAyJ5i_QgUnOk6HRI8LF3iZeKp4R_FWJXWsvehYII"]