Autonomous Agents with Reliable Outcomes
Codex Goals: A 6-Component Framework for Autonomous Agent Tasks
Claire Vo (ChatPRD) walks through Codex /goal in depth with real examples: a 5h45m autonomous run eliminating hundreds of Sentry errors, and a 4-hour job that cleaned 3,900 emails down to 68. The six-…
View details →OpenAI's Data Agent: Reliability from 6 Layers of Context
OpenAI built its internal data agent on a 'vanilla' architecture — the secret was stacking 6 layers of context across 90,000 tables to give the agent sufficient grounding. Used Codex to migrate 10,000…
View details →Salesforce: 90% of Enterprise Agent Work Happens After Go-Live
Based on 20,000 enterprise agent deployments, Salesforce found that 90% of the work in AI agents is post-launch: monitoring, correction, iteration. Key practices: start small and narrow scope, define …
View details →Loop Engineering: 5 Building Blocks and the Comprehension Debt Risk
Addy Osmani describes 5 building blocks of agent loop engineering: automations, worktrees, skills, plugins/connectors, and sub-agents. Key warning: 'comprehension debt' — when engineers use agent loop…
View details →"Fake Done" vs "Undefined Done": The /goal Primitive for Agent Finish Lines
The AI Maker piece frames the core failure modes of AI agents: "fake done" (agent claims completion without verifying) and "undefined done" (agent stops because it ran out of instructions, not because…
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