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Intuist

Write the answer key first

An AI's wrong answer looks exactly like a right one. Why your own experts should write the answer key first, and how we keep VedaOS safe while it improves.

Johri Dhanotra
CEO & Founder
ORIGINAL ON LINKEDIN

FOUNDER NOTEFirst published on LinkedIn, kept here so it has a permanent home. Join the conversation there.

Reading an AI's answer is the worst way to test it.

It will look right. That is what these models do: a clean paragraph, a tidy table, a date in the right format. A wrong answer looks exactly the same.

The fix is old and dull. Before the AI answers anything, your own experts take real cases from your business and write down the right answer to each. Engineers call this an eval. I call it an answer key.

We run our own company this way, because the models underneath VedaOS change every few months and each new one sounds smarter than the last. Here is what keeps it safe while it gets better.

A model never takes over on how it sounds. Before a new one replaces an old one, both take the same answer keys, built from our real work. It wins there or it does not ship.

Nothing reaches customers on one opinion. Every change runs a battery of automated tests, and the larger ones face a second, independent review whose only job is to break them.

No AI feature ships on a demo. It runs on real cases first.

When a model provider stumbles, the work does not stop. It moves to another model, including our own, on our own GPUs.

Security is checked every night, not once a year. A standing red team attacks the previous day's changes. SOC 2 Type II is the floor.

And every app is watched after it ships. Between late June and 12 October, Veda closed 3,661 production tickets with no human handoff.

If you are about to put AI on work that matters, write the answer key first.

The test you write yourself is the one an AI cannot charm.

The original post is on LinkedIn.

  • Evals
  • AI testing
  • VedaOS
  • AI apps
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WRITTEN BY

Johri Dhanotra

CEO & Founder

Founder of Intuist. Thirty years of building software, now building the AI that builds software.

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