The Summer of Codex

9 months ago

LLMs are improving exponentially and their utility depends on user proficiency.
The author initially hesitated to use AI for their 80,000-line Go codebase but gradually integrated LLMs for architecture improvements, bug fixes, and unit tests.
The author found LLM output speed and confidence addictive but refrained from paid subscriptions to avoid over-reliance.
OpenAI's Codex was initially too expensive but became accessible via the Plus plan, offering background task implementation and pull request creation.
A detailed prompt example shows how Codex was used to modify a Customer resource to support businesses, saving significant time.
Codex successfully implemented the changes, allowing the author to review, merge, and push updates quickly while maintaining work-life balance.
Repetitive coding tasks, like CRUD APIs, can be efficiently handled by Codex with proper prompting and an AGENTS.md file for coding preferences.
The author seeks to improve prompting techniques by studying guides like Foundry's and the Lyra prompt.
Autocomplete suggestions in code editors still have room for improvement.

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