Cognitive offloading!

This balance is what I’m finding interesting. AI can get you to something working remarkably quickly, but getting from ‘it works’ to ‘I’m comfortable putting this online’ still brings back testing, privacy, maintainability and judgement.

Nice! MessyData is simpler at this stage.

The core stack is: Next.js on Vercel, server-side OpenAI call, no database or agent architecture for the core flow.

Workflow is: pasted text → structured JSON → table → CSV export

So for now it’s more structured parser than autonomous agent.

This is immediately showing me the right build-in-public rhythm:

share the tool → hear the practical questions → clarify the product → improve the experience.

Grateful for the interest and question!

4/ So one next improvement is obvious:

Make the input guidance clearer.

MessyData should explain that it currently works best with pasted semi-structured text like copied tables, lists, CSV-ish text, markdown notes, emails, AI outputs, and messy notes.

3/ But this is a good product lesson:

For practical AI tools, explaining the limits can matter almost as much as showing the capability.

Users will want to know:
- what it accepts
- where it struggles
- what needs review
- what it is not trying to be