Why I built it
AILunchroom.com started from a simple frustration: a lot of AI training sounds polished in a presentation and then falls apart when someone tries to use it at work. I wanted an early product that treats AI practice like a real work session, not a lecture.
Product thesis
People learn faster when the examples feel close to their actual job. AILunchroom uses realistic prompts, guided labs, role-aware paths, and exercises that leave the user with a concrete takeaway.
Current proof
- Public early launch with a clear training-product direction.
- Role-aware learning paths and workplace-first prompt framing.
- Labs designed to leave users with usable prompts and final outputs.
- Product, curriculum, copy, UX, and deployment handled as one connected build.
My role
- Product concept and positioning.
- Training structure, lab flow, and prompt design.
- Frontend implementation and deployment.
- Ongoing copy, curriculum, UX, and operating decisions.
Design choices
The product is for people who are curious about AI but not trying to become AI specialists. That shapes the interface: clear steps, visible outputs, less jargon, and prompts that sound like workplace requests rather than platform instructions.
Operating boundaries
The product has to be careful with privacy, user expectations, and overpromising. AI practice can be powerful, but the product should still make room for review, judgment, and the limits of model output.
Next proof to add
The next strong public proof point is a product walkthrough: first landing, first lab, prompt revision, and the final output a learner takes away.
Related
See Practical AI Implementation for the broader adoption frame behind this product note.