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Build a household dinner-suggestion app

A non-coder used Codex to build a local app that suggests dinners from pantry stock, garden produce, diets, appliances and weather.

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Use case overview

A non-coder used Codex to build a local app that suggests dinners from pantry stock, garden produce, diets, appliances and weather.

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Reported experience

  1. What they did

    Deirdre Straughan, a non-coder, wrote a feature list, had ChatGPT turn it into a Codex prompt, and let Codex build a local Python/FastAPI/SQLite web app in small milestones. Codex ran for minutes at a time, tested itself and explained what to try. She approved terminal and file permissions, tested with real data, and requested changes. Later she added an Edamam recipe source and metric conversion.

  2. How it went

    After about 20 hours and two full rebuilds, she had a usable, more robust MVP. Ad hoc feature requests had made the first versions buggy and sluggish.

  3. Worth knowing

    Agree the scope up front and ask for one change at a time. Ad hoc requests caused bugs, and Codex sometimes ignored all but the first changes. Edamam costs $9/month.

Example prompts

Try with Codex
Build me a simple local app that suggests dinners based on what's in my pantry ([list items]), my garden produce ([list items]), our diets ([diets]), the appliances we own ([appliances]), and today's weather. Make it easy for me to update the lists. Finish by running it and showing me three sample suggestions, and explain how to start it again.

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