01The problem
Every coding agent today has the same bug: it learns your codebase in the morning and forgets it by lunch. You spend the afternoon re-explaining the same architectural constraint, the same naming convention, the same "no, we don't use that pattern here." The agent gets faster at typing and you get tired of teaching.
02What memory unlocks
- Codebase memory persists architectural decisions, conventions, owner-approval requirements, and "we tried that, it didn't work" facts across sessions.
- PR-grounded ingestion — every code review automatically becomes a memory the next session can use.
- Contradiction handling for when the conventions change, with author and timestamp surfaced.
- Per-repo namespaces with team-level access controls.
03In production
A platform engineering team used AgentPrizm with their internal coding agent. The agent stopped suggesting deprecated APIs after two days of being told. It started catching code-review feedback patterns automatically (e.g., "always log the trace ID at the boundary"). PR cycle times dropped because reviewers stopped writing the same comments.
04Measured impact
| Metric | Before | With AgentPrizm | Δ |
|---|---|---|---|
| Repeat code-review comments | 11/PR | 2/PR | −82% |
| PR cycle time, p50 | 18h | 11h | −39% |
| Agent suggestions accepted on first review | 41% | 67% | +63% |
| "Re-explained the same thing again" complaints | daily | quarterly | — |
Measured across 6+ design partners on Scale, Q1 2026. Your mileage will vary; we'll run an eval with you.
05Integrations
GitHub, GitLab, Bitbucket, and the major IDEs via MCP. Self-hosting recommended for proprietary codebases; air-gapped deployment supported.
See it on your data.We'll run a 2-week eval against your existing agent — same prompts, same model, only the memory layer changes. Start a pilot.