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LOCAL-FIRST ENGINEERING MEMORY

Above the repo.Beyond the session.

Lattice is a local-first engineering memory and workflow layer for AI-assisted development. Specs, tasks, decisions and experience are captured once in ~/.lattice and reused across projects, sessions and agents.

npm i -g @qcqx/lattice-cli
  • MIT
  • Local-first
  • No telemetry
  • Agent-agnostic
LOCAL · ~/.lattice

THE GAP

AI starts from zero.
Every time.

A new repo. A new session. A new teammate. A new agent. The context is rebuilt from scratch, then thrown away.

01

New repo

Conventions live in code, docs and someone’s head.

02

New session

Decisions disappear into chat scrollback.

03

New teammate

The same questions, boundaries and mistakes.

04

New agent

Every tool has its own context, disconnected from the rest.

WORKFLOW / END TO END

One task. A full loop.

Install the CLI once. Then run the whole workflow from your agent — start, load context, record decisions, archive, and distill a spec. The next session starts with the memory already in place.

01 / INSTALL ONCE

npm i -g @qcqx/lattice-cli

Node.js 18+ · no account · local files

02 / CALL IT FROM YOUR AGENT

lattice:task:startAsk your agent…

Type / or @ at the start of your agent input to invoke it; the CLI reads and writes ~/.lattice underneath.

agent · acme-portallocal · simulated

lattice:task:startContinue auth-guard. Keep the public API contract unchanged.

ltc task start auth-guard
task/auth-guard · in_progress
Lattice agent

Loaded the task and its memory. I’ll read the relevant specs before touching code.

Autoplay is only a demo; the real CLI reads and writes your local state.Read the quick start

THREE LAYERS

Memory, workflow, access.

Not another chat window. A way to make the work itself reusable.

01Memory

Memory layer

Specs, tasks, decisions and experience become typed, searchable artifacts.

  • Layered specs
  • Tasks & checkpoints
  • Project relations
  • RAG search
  • Cross-session experience
02Workflow

Workflow layer

Read before work, record while working, distill when archiving.

  • Read at start
  • Record in flight
  • Distill at archive
  • Reuse across projects
03Access

Access layer

Local files are the source of truth. CLI, Web, VS Code and any command-capable agent can read them.

  • CLI
  • Web workbench
  • VS Code
  • Dual-track sync
  • Agent agnostic

THE WORKBENCH

The workbench is the proof.

The real web workbench, running on mocked data. No login, no backend, no network requests.

Open the live demo
lattice
Global graph
Global graph
lattice
Project view
Project view
lattice
Task detail
Task detail
lattice
Spec reader
Spec reader

LOCAL-FIRST

Your memory stays yours.

Everything lives as plain files in ~/.lattice. No telemetry, no forced cloud, optional Git sync.

FAQ

FAQ

Is my data uploaded?

No. Lattice writes to ~/.lattice by default. Data leaves your machine only when you explicitly enable Git sync.

Which AI clients are supported?

Any agent that can run a CLI command. Lattice does not lock memory into one model or client.

How is this different from a wiki or issue tracker?

Lattice models the engineering process — specs, tasks, decisions and checkpoints — in one structure that agents can read directly.

Is it free? What runtime does it need?

MIT open source and free to use. The CLI needs Node.js; the web workbench is a browser UI over the same local data.

GET STARTED

Start with the repo you are in.

Install the CLI, initialize local memory, then continue in the next session.