
Every AI-written lesson lands as a draft
Generating training content is the easy part. Deciding it is fit to put in front of two hundred colleagues is not, and that decision does not belong to a model.
Four ways in, one way out
A lesson can start from a topic, from your own PDF or Word document, from a real skill gap surfaced by a review, or from someone writing it themselves. Whichever route it takes, an AI-generated lesson lands as a draft.
A person reads it and publishes it. There is no configuration flag to skip that, because the failure it prevents is not a formatting error — it is teaching the whole company something that is confidently wrong.
What the model does not know
It does not know your reorganisation, your renamed teams, the policy you replaced in March, or the one client whose contract makes the general advice wrong. It writes plausible material, and plausible is exactly the failure mode that gets past a skim.
Documents are read, not kept
An uploaded document is split semantically into as many as eight lessons and is never stored. We take the structure and the content and let the file go — a source document is often the most sensitive thing in the exchange.
The quiz is not decoration
Every lesson ends with a multiple-choice quiz at a 70% pass mark, with unlimited retries and the best attempt counting. Unlimited retries are deliberate: the goal is that people end up knowing the material, not that we produce a clean distribution of first-attempt scores.

We publish the review formula before anyone is scored
Goal progress 30%, kudos 15%, your department's own yardsticks 55% — and the reward scheme is fixed during setup, before a single person is graded. Here is why the order matters more than the numbers.
Read article
One yardstick at a time, across the whole team
Judging a whole person in one pass invites the halo effect, where a strong impression on one measure bleeds into every other rating. So the scoring board is built the other way round.
Read article
In, out, or unresolved — the third answer that matters
Eligibility used to have two outcomes, and a blank cell quietly meant "out". Somebody could be dropped from their own performance review with no warning anywhere. Now a round refuses to launch instead.
Read articleSee it working, not just described.
Every decision in these posts is visible in the product. We will walk you through whichever one you care about.

