HypothesisLab

The Learning Library

The Learning Library (Library in the nav) is the team's collective memory of every resolved hypothesis. It's where you go before writing a new bet — to find out whether your team has already tried something similar and what they learned.

Private hypotheses are never shown here. Drafts and active hypotheses don't appear either — only resolved ones.


Header and counter

The counter under the title tells you how many resolved hypotheses across the whole team. As your team works, this number grows; it's a small but real measure of organisational learning.

Library header


Search and filter

A single bar with everything you need to slice the library:

  • Search — full-text search over the title and learning notes (powered by Postgres FTS, so ranking is meaningful).
  • All outcomes — limit to Held, Broke, Wrong Magnitude, or Unresolvable bets.
  • All templates — limit to one template family (e.g. Pricing Change only).
  • All PMs — limit to one author. Useful when you remember "Alex tried this".
  • Date range — two date pickers for resolved-between filtering.
  • Sort — Newest first (default), Oldest, Confidence ↑/↓, or Broke first.

Search and filters

Tip: the highest-leverage search is Broke first with a tag filter. The team's failure log on a specific topic is usually more useful than its success log — failures encode where the world pushed back.


Entry cards

Each result is a single card showing:

  • The chain icon (⛓) if the hypothesis was created from a template.
  • Title.
  • Author · Template · Resolution date · Confidence (e.g. C1/5).
  • The learning note preview.
  • Tags.
  • The outcome pill on the right (HELD / BROKE / WRONG MAGNITUDE / UNRESOLVABLE).

Click a card to open the full hypothesis detail page — the original chain, pre-mortem, actual values, and any team comments.

Library entry card


Tag filter bar

The same tag pills you see on the dashboard work here too. Pick one to scope the library to a topic. Combining the tag filter with the outcome filter is the fastest way to surface relevant prior art.


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