Welcome to AITaskManager (AITM). This guide walks you through everything you need to know to get real work done with it, from your first task to reading the results.

Overview & Getting Started

What is AITM?

AITM is a desktop app that turns a single English prompt into working, tested, reviewed code. You describe what you want in a Task, AITM runs it through a 9-step pipeline — branch, architect, code, review, fix, test, e2e, docs, merge — and hands you back a finished change on its own git branch, ready to merge.

AITM vs. using Claude Code or Cursor directly

Tools like Claude Code or Cursor are excellent for one AI session at a time, driven interactively by you. AITM sits a level above them: it orchestrates those same AI coding assistants for you, automatically.

Every task runs in its own isolated git worktree, so parallel tasks never step on each other's files. Each task moves through the full pipeline without you babysitting the AI — the same AI session that writes the code also gets reviewed, fixed, and tested before anything reaches your main branch. A watchdog detects stuck or "zombie" AI processes and automatically retries them, and finished work is auto-merged into your dev branch once it passes review and tests.

In short: Claude Code and Cursor give you an AI pair programmer. AITM gives you an AI pair programmer that queues its own work, checks its own work, and only interrupts you when something needs a human decision.

Core concepts

Concept	In one sentence
Project	A codebase AITM manages — imported once, then always available in the dashboard.
Task	A single unit of work you assign — "add a button", "fix a bug", "implement an endpoint".
Pipeline	The automatic multi-step process a task goes through: plan → code → review → fix → test → merge.
Agent	The AI "worker" running one pipeline step (e.g. the agent that writes code, the agent that reviews it).
Contract	A saved fact sheet describing how part of your project behaves, so the AI doesn't have to rediscover it every time.

Who AITM is for

AITM fits you especially well if you:

• Manage multiple projects at once, possibly in different languages/frameworks
• Want to use AI systematically and repeatably, not just as an occasional smart autocomplete
• Need visibility into what the AI is doing, with the ability to step in when needed
• Want the AI to remember your project's conventions instead of re-explaining them in every conversation

Importing a project

Before AITM can manage a project, it needs to "get to know" it. Adding a project triggers an automatic, non-destructive, and free (no AI cost) static pre-scan: stack & language detection, a code map of file dependencies, UI element extraction for frontends, variable discovery, and documentation linking. You can safely re-run this pre-scan any time.

First run

When you open AITM for the first time, add a project (point it at a local git repository), then click New Task to describe your first change. AITM creates a branch, spins up an isolated worktree, and starts the pipeline. You can watch progress live on the dashboard, and you'll find the finished result waiting for you once the pipeline completes.