in days.

We wanted to try a different approach: learning through dialogue and repetition.

With Socratize, users enter realistic scenarios and have to respond to an AI “counterparty”.

For example:

A sales rep practices handling: “Your product is too expensive” A support agent practices de-escalating an angry customer An employee practices explaining a compliance rule in their own words

The AI responds like a realistic counterpart, challenges weak arguments, and continues the conversation until the user improves or fails the scenario.

The goal is simple: replace passive training with active practice.

We’re using Claude to generate responses and evaluate the quality of the user’s arguments based on context and reasoning. Each session is stored so teams can see where people struggle and what scenarios are hardest.

Tech stack:

Next.js (frontend) Node.js backend PostgreSQL Claude API

We launched the MVP last week.

We’re still early and would really appreciate feedback from people here:

Does this approach actually make sense for training? What use cases are we missing? What would make this fail in real companies? Is this fundamentally useful or just “interesting but not needed”?

Try it here: https://socratize.io

Free tier, no credit card required.

Happy to answer any questions.18:T4e4,I made this game while working on a different project about teaching English spelling. I was reading about homophones and got struck by how much a homophone can transform the shape of a word, so I started experimenting with little games built on that.

I added a few more transforms, anagrams, verb/tense changes, but the answers kept coming out too obvious. I couldn't distort the word enough to make it interesting. The breakthrough was compound pairs. Jumping from one word to another through their compound (sea → horse, via seahorse) really obscures the path and that's when it suddenly got fun and unpredictable.

I've been sharing it with friends. I'm in

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