Tracigo

The problem

Your team uses five tools to build one feature. Requirements live in Jira. Design decisions are in Confluence. Specs are in Google Docs. Code is in GitHub. The actual reasoning — why you chose MongoDB, why you dropped the offline feature, why the API contract changed — is scattered across Slack threads, meeting notes, and conversations that nobody can find six months later.

Every handoff between tools loses context. Every new team member asks the same questions. Every manager schedules another status meeting because nobody can see what's actually happening.

And now, with AI agents writing significant portions of your code, the problem compounds. Your agent spends an hour designing a retry system with you — requirements, architecture trade-offs, edge cases — then the session ends. Tomorrow, a new session starts from zero. The decisions are gone. The context is gone. You're re-explaining.

What Tracigo does

Tracigo is a development workspace where your entire team — PMs, engineers, QA, leads — works on features together, with AI agents, in one place.

Every feature gets its own workspace: an isolated branch with its own VS Code environment, its own AI agent sessions, and its own set of artifacts — structured documents that capture requirements, designs, specs, test plans, and the decisions behind them.

Artifacts are the key. They're not documentation written after the fact. They're created during the work, as part of the conversation between you and your AI agent. When your agent helps you think through requirements, those requirements become a living artifact that the whole team can see, review, and build on. When you make a design decision, the reasoning is captured — not lost in a chat transcript.

Your AI agents read artifacts automatically. Every new session starts with full context — what's been decided, what's in progress, what changed and why. No re-explaining. No starting over.

What you get

As an engineer: Your AI agent knows the full context every time. Requirements, design decisions, specs — all available without copy-pasting or re-explaining. When upstream decisions change, you know about it before writing code that will need to be rewritten.

As a PM or lead: You see what's happening across workspaces without status meetings. Requirements are traceable through design, spec, and code. When someone asks "why did we build it this way?", the answer is in the artifact, not in someone's memory.

As a team: Context stops getting lost in handoffs. Decisions survive beyond any individual. New team members read the artifact trail and understand the full history. The knowledge your team builds compounds instead of evaporating.

Core concepts

Projects

A project is your codebase — one or more git repositories grouped together. You point Tracigo at a folder, and it handles the rest.

Workspaces

A workspace is one unit of work — a feature, a bug fix, a refactor. It gets its own git branch, its own VS Code, its own agent sessions. Multiple workspaces run in parallel. You see them all in the sidebar.

Artifacts

Structured documents that live with your code in the .tracigo folder. Requirements, designs, specs, test plans — each artifact captures not just what was decided, but why. Your AI agents read and write them automatically. Your team reviews and collaborates on the shared version.

Learn more about artifacts →

Agent integration

Tracigo automatically configures 13+ AI coding agents (Claude Code, Codex, Copilot, Cursor, and more) to understand your artifacts. No MCP servers, no plugins, no setup. Open a workspace, and your agent knows everything.

Learn more about agent integration →

Next steps