How I think about Codex (https://www.linkedin.com/pulse/how-i-think-codex-gabriel-chua-ukhic)

Gabriel Chua (Developer Experience Engineer for APAC at OpenAI) provides his take on the confusing terminology behind the term “Codex”, which can refer to a bunch of of different things within the OpenAI ecosystem:

In plain terms, Codex is OpenAI’s software engineering agent, available through multiple interfaces, and an agent is a model plus instructions and tools, wrapped in a runtime that can execute tasks on your behalf. […]

At a high level, I see Codex as three parts working together:

Codex = Model + Harness + Surfaces […]

• Model + Harness = the Agent

• Surfaces = how you interact with the Agent

He defines the harness as “the collection of instructions and tools”, which is notably open source and lives in the openai/codex (https://github.com/openai/codex) repository.

Gabriel also provides the first acknowledgment I’ve seen from an OpenAI insider that the Codex model family are directly trained for the Codex harness:

Codex models are trained in the presence of the harness. Tool use, execution loops, compaction, and iterative verification aren’t bolted on behaviors — they’re part of how the model learns to operate. The harness, in turn, is shaped around how the model plans, invokes tools, and recovers from failure.

Tags: definitions (https://simonwillison.net/tags/definitions), openai (https://simonwillison.net/tags/openai), generative-ai (https://simonwillison.net/tags/generative-ai), llms (https://simonwillison.net/tags/llms), ai-assisted-programming (https://simonwillison.net/tags/ai-assisted-programming), codex-cli (https://simonwillison.net/tags/codex-cli)