Hello OpenAI team,
I would like to request a Codex feature for local-first software development.
Feature idea:
Allow Codex to optionally prepare, adapt, quantize, and integrate a small task-specific local model into the applications it builds.
Example:
If I ask Codex to build a debt management desktop app, it should be able to optionally prepare a lightweight local model for that app’s specific use case and integrate it into the generated project so core AI features can work offline.
Why this would be valuable:
- offline and privacy-friendly app experiences
- less dependency on external APIs for end users
- more useful generated apps
- stronger local-first developer workflows
- better support for specialized software
Important note:
This could be controlled by plan limits or compute limits, so higher tiers could support larger local model workflows while standard paid tiers support smaller task-specific models.
What I’m asking for:
- optional local model preparation inside Codex
- optional task adaptation / lightweight fine-tuning flow
- optional quantization/export flow
- ability to integrate the resulting lightweight model into generated desktop or web apps
- clear controls for model size, runtime limits, and deployment target
This would make Codex much more powerful for developers building real local-first software.
Thanks.