KakaoPay FE Harness: Model Improvements Reduce Agents from 21 to 11
·2026.11.03 09:00
Key point
Harness size was halved due to improved model performance, but verification mechanisms must be maintained.
Details
- Harness composition was reduced from 21 Agents and 29 Skills to 11 Agents and 17 Skills due to improved model performance
- Mechanisms to compensate for model limitations, such as step splitting, strong instructions, and keyword routing, were removed as they became unnecessary or increased token costs
- Team-specific convention documents, execution-result-based verification, and release gates remain necessary due to the model's tendency to evaluate its own results favorably
- Verification through observing actual behavior is essential even for enforcement mechanisms; without quantitative metrics, the harness accumulates indefinitely
Harness Composition and Enforcement Methods
- Path-specific rule files are generated and Hard/Soft rules are applied through domain knowledge presets and initialization Skills
- Seven Hook scripts are used to enforce delegation, prevent step skipping, block mid-execution termination, and record verification results
- Three types of Reviewer Agents (Maintenance, Convention, Accuracy) review in parallel, with final confirmation based on actual failure conditions
Issues Encountered During Development
- Blocking failed due to a PreToolUse Hook output format error, which was resolved by reimplementing the correct format
- An issue occurred where lint failures were recorded as passes due to exit code errors when executing pipe commands; this was fixed to record pipe commands as failures
- Work interference between sessions caused by using git stash was addressed by adding a rule prohibiting the use of that command in Skill documentation
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