Short agent logs can be more useful than polished summaries
AI agents can produce final summaries that sound more complete than the real work behind them. A line like “I fixed the issue and cleaned up the ” may feel clear, but it can hide the details a reviewer needs. The useful information is usually more specific: which files changed, which parts were left alone, what failed during the run, what were made, and what still needs a human check.
For , a short structured log can be more helpful than a long confident explanation. The useful format is not a noisy raw log, but a brief list of what was tried, what changed, what failed, what remains uncertain, and what should be checked next.
Key points
- Final summaries can hide the exact details a reviewer needs.
- Useful agent output should show changed files, skipped areas, failures, , and human checks.
- A short structured log may be better than a long confident explanation.
- A good format covers what was tried, what changed, what failed, what is uncertain, and what to check next.