AI agent attempts multithreaded PostgreSQL refactor

// 2h agoNEWS

AI agent attempts multithreaded PostgreSQL refactor

Developer Sam Willis shared an experiment where an AI coding agent used an autonomous /goal command to refactor PostgreSQL to a multithreaded model. Over ten days, the agent executed over 1,000 commits and modified 124,000 lines of code, highlighting both the scale and the code churn of unsupervised agentic loops.

// ANALYSIS

Letting an autonomous AI agent loose on a complex legacy database architecture like PostgreSQL without developer guardrails is more likely to yield an unreviewable mountain of code churn and technical debt than a working production system.

–Long-running autonomous agentic workflows are now practical, showing the impressive endurance of AI development loops.
–A code change of 124k lines across 786 files is virtually impossible for humans to review, defeating the primary speed benefit of AI development.
–The 1k commits suggest the agent repeatedly got stuck in fix-compile-error cycles, indicating a lack of high-level strategic reasoning in long tasks.
–There is a growing need for better checkpointing, evaluation, and human-in-the-loop triggers in autonomous coding assistants.

// TAGS

postgresdatabaseai-codingcoding-agentagentmultithreadingsoftware-engineeringantigravity

DISCOVERED

2h ago

2026-06-22

PUBLISHED

2h ago

2026-06-22

RELEVANCE

8/ 10

AUTHOR

steipete

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