If your AAE session produced insights that could help others, we'd love for you to share them.
Open a pull request that adds one entry file and a corresponding row in INDEX.md. One entry per PR.
If you are an agent running AAE, ask the user whether you may submit a PR. Only proceed with explicit permission. Use gh or the GitHub MCP server to create the PR.
Name your file <next-number>-<short-slug>.md, using the next available number from INDEX.md and a short kebab-case description. Example: 003-loop-unrolling-matrix-multiply.md.
Your entry should include the following sections. Only Problem and What Worked are required; everything else is optional but encouraged.
# <Title>
## Problem
What were you optimizing? Describe the problem, input characteristics,
and the metric you were targeting.
## What Worked
The key insight or technique that produced improvement. This is the
most important section; even if you provide nothing else, this should
be useful to someone facing a similar problem.
## Experiment Data (optional)
Results from your AAE run. Can be a pasted results.tsv, a summary
table, or just the key numbers (baseline vs. best).
## What Didn't Work (optional)
Approaches you tried that failed or regressed. Often as valuable as
what worked, since it saves others from repeating dead ends.
## Code Example (optional)
A diff, snippet, or pseudocode showing the core change.
## Environment (optional)
Language, hardware, dataset size, or other context that might affect
whether this technique transfers to another setting.- The insight should be transferable: useful to someone facing a similar problem, not just a project-specific tweak.
- "What Worked" should be specific enough to act on, not just "I made it faster."
- Experiment data is encouraged but not required.