✗It guesses
It invents fixes that don't apply to your stack or your version — confidently, every time.
WeVibe is the verified-knowledge layer for AI coding — the fixes that actually worked, with provenance, surfaced the instant they apply. Not memory that stores your slop, but proven knowledge that makes any agent stop repeating bugs your stack already solved — and punch well above its size.
The fix you need almost always exists — it's just trapped in someone's private chat log, never indexed, never verified. So your agent guesses instead.
It invents fixes that don't apply to your stack or your version — confidently, every time.
The whole stack already worked this out. Your agent has no idea, so it makes the mistake again.
Even frontier models hallucinate. Without the right context at the right moment, every agent — and smaller, local ones most of all — leaves real accuracy behind.
First-gen memory tools just store everything and match keywords. WeVibe matches the situation — the symptoms, stack, and versions of what you're doing this second — and only ever from fixes proven to work.
Every memory stores a situation card — the symptoms, triggers, stack, and environment that make it relevant. Not a bag of keywords.
Your live context and the memory are embedded the same way by the same local model, so the right lesson rises to the top instead of the loudest keyword.
Retrieved fixes are decrypted locally, scanned, and shown for your OK. Nothing is silently injected into your context.
What the verified-knowledge layer actually buys you — measured in our testing against a perfect-knowledge ceiling.
First-gen memory just stores everything your agent does — slop and dead ends included. WeVibe is the layer above it: a curated social graph of fixes proven to work, with the tooling to keep them private, current, and yours. It's the real answer to "why not just ask the model?" — verified provenance, not a confident guess.
Every memory is a fix that actually worked — carrying provenance: who verified it and the exact version it applies to.
The network never sees plaintext. Embedding and decryption happen locally at a trusted step — not on someone else's server.
Human approval before anything is injected. Self-custodial by design — your keys, your knowledge, yours to keep.
As more verified fixes flow in, the curated graph stays sharp instead of bloating. In a separate longevity simulation, the signal cleanly separated from the noise — automatically.
A clean separation between what's worth keeping and what isn't — 5× wider than the prior approach, with good fixes wrongly retired only 5.5% of the time.
Bring your stack, point your agent at the pack, and watch the guessing stop.
Contribute verified fixes, keep your own keys, and own what you put in — a smarter commons, built on proof.