OpenAI's agent manual rotted into a graveyard of stale rules. Grab my Working Context Starter Kit, the four-file guide that keeps yours current.

Three engineers at OpenAI kept writing down what their agents needed to know, and the file kept getting worse.

New guidance piled on old guidance until, in OpenAI’s words, the monolithic manual turned into a graveyard of stale rules. The agents could not tell what was still true. The humans stopped maintaining it. The file became an attractive nuisance.

They were five months into an internal product at that point. Roughly 1,500 pull requests, about a million lines of code, and not one of those lines written by a person.

The obvious headline is that AI made a small engineering team much faster, and that part of the story is true. It also leaves out the part that matters to the rest of us: nobody knew what those million lines should be before the work began. The engineers could describe the product they wanted and give Codex a serious first assignment, but they could not predict every feature, dependency, design choice, bug, or wrong turn they would encounter over the next five months. The product did not exist yet, which meant the complete instructions could not exist either.

Some Codex runs went past six hours. The engineers kept learning the whole time. They saw features take shape and found assumptions that did not survive contact with the code. By the time a run ended, the person reviewing it was often smarter about the project than the person who had started it, while the agent was still following the older person’s instructions.

This is why most of us are still giving AI such small jobs. If you think the whole job has to fit inside the first prompt, you will choose work small enough to explain in one sitting: summarize this meeting, clean up this email, make these slides, compare these five products. Those are useful requests, but you already understand the job before the AI begins. You know what the output should look like, and if the answer is bad you can try again without changing much else.

The projects that could change your work are rarely that tidy. A useful new product, a deep research project, or a better way to run part of a business contains questions you cannot answer yet. You learn what you want by seeing the first attempt. A bad assumption becomes obvious when it breaks, and sometimes the work reveals that you were trying to build the wrong thing in the first place. If you do not know how to change an agent’s direction while all of that is happening, keeping the assignment small is the only safe move.

By 10x your ambition, I do not mean that you should type ten times as many prompts or fill your screen with ten agent windows. I mean you can take seriously a project you would have dismissed a year ago because you could not do all the work yourself, could not afford the team, or could not explain every step before starting. Agents give us a third choice: start with a result we care about, ask for the first real piece, and use what comes back to get smarter about what the project should become. That is a much bigger promise than saving an hour on email, because it means your ambition no longer has to stop at the edge of your résumé.

Here’s what’s inside:

• You know more than you can explain, and a blank page can’t get it out of you. Why a VP of sales couldn’t spec the system he needed, then named the real rule ten seconds after seeing a wrong first version.

• What you still decide, and what you can hand over. Anthropic looked at 400,000 Claude Code sessions and found people making about 70 percent of the planning calls and only 20 percent of the execution ones.

• The move that changes a whole project at once. How I stopped a benchmark run that had gone busy but useless, and what I rewrote to put 339 sources and 1,000 questions back to work.

• The four kinds of context, and why one file can’t hold them. Stable rules, current state, a map of your material, and history all change at different speeds, and mixing them buries the decision you made this morning.

• The Working Context Starter Kit. Four ordinary files that keep every agent caught up with your latest thinking, plus the opening prompt I use to start a project I can’t fully describe yet.

Let me show you how to begin before you can see the whole path, and how to keep every agent working from your newest decision.