Cooking with Codex — Charlie Guo & Gabriel Chua, OpenAI
This workshop provides a comprehensive overview of Codex, an advanced AI agent, demonstrating its capability to automate complex, multi-stage development and operational workflows. The core methodology involves giving Codex detailed context (via plugins, appshots, and memory), allowing it to execute tasks through various interfaces (Computer Use, Chrome Extension), and managing long-running processes using advanced primitives like Goals, Subagents, and Thread Handoff. The ultimate goal is to move beyond single-turn prompts toward building fully automated 'software factories' that can manage entire development lifecycles.
Key takeaways
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Context is the most critical ingredient for Codex.
18:00
Codex requires rich context, which can be supplied through external sources (Plugins for Slack, Gmail, etc.), visual inputs (Appshots), and persistent memory (Chronicle/Personalization).
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Advanced workflow management uses Goals, Subagents, and Thread Handoff.
36:40
For complex, long-running tasks, use the `Goal` skill to define verifiable completion criteria. Subagents allow for specialized, parallel workstreams, while Thread Handoff enables visible communication between different parts of the agent's work.
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The App Server enables embedding Codex into custom products.
56:40
The App Server protocol is the core mechanism for integrating Codex's power (including context compaction and agent harness features) into proprietary or third-party applications, allowing users to leverage their existing ChatGPT token budget.
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Automations create repeatable, scheduled processes.
1:03:20
Automations (Heartbeat and Scheduled) allow agents to monitor systems (e.g., checking for deployment readiness, summarizing feedback) and trigger subsequent tasks or worktrees without constant human supervision.