Your agents should learn from your best work

Skillsync turns agent sessions into a durable record of how your team solves problems, so people and agents can build on what worked.

Trace decisions. Read the session they came from, and what got rejected
Turn what worked into skills your engineers and their agents run
Agents improve with every session: each run learns from the last

Decision traceorg-private

Why is the relay a single server?

01The relay stays one server; scale is per-customer allocation

No shared state between instances; Redis adds latency. A box per customer also isolates their traffic.

↳ view in session · relay-architecture #m-142

02Rejected: horizontal scaling behind a shared store

03End-to-end encrypted so the relay host can't read sessions

Use cases

The substrate for self-improving systems

Skillsync is the foundation companies build self-improving systems on. Your team's sessions become the durable layer of skills, decisions, and context that every agent, loop, and tool draws from, and improves against, over time. Everything below is built on it.

Build on Skillsync

Self-improving systems

Agents get better every time you ship

Generic loops drift and reinvent patterns with no one watching. Skillsync feeds systems like Hermes the skills mined from how your team actually builds, so agents run longer unsupervised and stay on your rails.

Decision traces

Never lose the why behind a decision

Every architectural decision, what was tried, what was rejected, and why, captured as a queryable trace from the sessions where the work happened. Build audit views, design-review tooling, or ADRs on top of it.

Skills

Solve it once, reuse it everywhere

Every recurring pattern in your team's sessions becomes a named, versioned skill any teammate or agent can pull. Your conventions stop living in a few heads and become something you can install.

Search & recall

Real answers, not stale wikis

A searchable index across every session, human or agent. Ask “how do we handle X here” or “why did we build Y this way” and get the reasoning from where the work actually happened, not a stale wiki.

Onboarding

New hires ramp in days, not months

New hires learn from the actual sessions and skills that define your codebase, not out-of-date docs. Their first PR looks like it came from someone who's been there a year.

AI-native collaboration

Multiplayer, not just multiagent

Agentic tools today scale one engineer with a fleet of agents. Software is a team sport: Skillsync gives every teammate and their agents one shared substrate to draw from and add to.