- Author
- Not stated
- Published
- Undated
- Kind
- Long markdown post from a company repo, with anecdotes and a product pitch
- Original
- github.com/humanlayer/advanced-context-engineering-for-coding-agents/blob/main/ace-fca.md
- Subject
- Harnesses and agent loops
What it is
The first-person author works on tooling for coding agents. The post is based on a talk given at Y Combinator. It explains the workflow and the reasoning behind it.
What it says
- The post claims coding agents can work in large codebases with context engineering. It calls the method frequent intentional compaction.
- The method keeps context use in a 40%-60% range across research, plan and implement steps.
- The post says the context window is the only lever on output quality. It ranks incorrect information as the worst problem.
- Subagents are for context control, not for playing roles.
- Human review is most useful on research and plans. A bad plan line can cause hundreds of bad code lines.
- The author reports shipping 35k lines to BAML in 7 hours, with a colleague. One pull request was still open.
- The post reports a failed attempt on parquet-java. Its research steps missed deep dependencies.
What evidence it gives
The evidence is anecdote. The author describes a bug fix on a Rust project that a maintainer approved. The author also describes a large feature pair and one failure. No controlled comparison is given.
Interests and limits
The author's company sells a tool announced at the post's end. It has a stake. The results are self-reported. The 3-5 day estimate came from a colleague. The post's images and videos were not viewed. The post is undated and names no author.