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Hagicode
Hagicode is an AI coding assistant built around real development workflows. It helps teams understand code, organize changes, execute tasks, and keep the reasoning behind the work.

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Early Access Software

Get involved with this software as it develops.

Note: This Early Access software is not complete and may or may not change further. If you are not excited to use this software in its current state, then you should wait to see if it progresses further in development. Learn more

What the developers have to say:

Why Early Access?

“Hagicode already provides a usable core experience, and
Early Access allows us to improve it with feedback from real
users in real development workflows. The current version
already supports onboarding, project setup, AI-assisted
sessions, proposal-driven work, and multi-agent workflows,
but we are still refining stability, usability, and the
overall product experience. Releasing in Early Access helps
us validate priorities with the community while continuing
to improve the software in the open.”

Approximately how long will this software be in Early Access?

“ We currently expect Hagicode to remain in Early Access for
approximately 12 months. That may change depending on
development progress and community feedback.”

How is the full version planned to differ from the Early Access version?

“ We plan for the full version to offer a more complete and
polished experience across onboarding, workflow clarity,
stability, and feature depth. We also plan to continue
improving multi-agent collaboration, project management
workflows, customization, platform support, and the
software’s game-inspired systems. Our goal is to make the
full version more robust for everyday use while keeping the
experience easier to understand and more consistent overall.”

What is the current state of the Early Access version?

“ The Early Access version is already functional and usable.
Players can install the desktop application, complete
onboarding, create or import a project, choose a supported
Agent CLI, start read-only or edit sessions, use proposal-
driven workflows, and access features such as AI-assisted
commit generation and multi-agent project organization.
However, the product is still under active development. Some
workflows, integrations, and game-inspired systems are still
being refined, and certain supported tools may require
separate local installation, authentication, or external AI
service access.”

Will this software be priced differently during and after Early Access?

“ We plan to keep pricing stable during Early Access. If the
scope and feature set expand significantly over time, we may
review pricing closer to full release, but we do not
currently plan a major pricing change.”

How are you planning on involving the Community in your development process?

“ Community feedback will play an important role in shaping
Hagicode during Early Access. We plan to gather feedback
through Steam discussions, community channels, livestreams,
GitHub, and direct user reports. We are especially
interested in feedback on onboarding, workflow design,
multi-agent collaboration, usability, and overall product
direction. We want development priorities to be informed by
how people actually use the software.”
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Planned Release Date: 2026

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About This Software

In one sentence, Hagicode is an AI coding assistant built around real development workflows. It helps teams understand code, organize changes, execute tasks, and keep the reasoning behind the work.

This page does not try to list every module. It stays with three themes: Smart, Efficient, and Fun.

What is Hagicode?

Hagicode is not just a tool for generating a few lines of code. It is a workspace for the broader development loop:

  • Understand codebases before changing them

  • Turn ideas into structured changes with proposals, tasks, and validation

  • Keep work traceable so decisions can be reviewed and reused later

  • Connect to current supported Agent CLIs: Claude Code, Codex, GitHub Copilot, OpenCode, Hermes, QoderCLI, Kiro, Kimi, Gemini, DeepAgents, and Codebuddy

Hermes, Gemini, and DeepAgents are supported through manual local installation or authentication flows. The remaining CLIs expose one-click installation entry points or guided install flows. For setup details, use the AI Agent CLI Installation page. IFlowCli remains legacy compatibility only and is not part of the current active support range.

Smart: understand first, then act

The “Smart” part of Hagicode is less about flashy demos and more about making AI useful in real projects.

Align on goals, scope, and validation before implementation starts.

1. Proposal-driven instead of blindly editing

For larger changes, Hagicode can turn an idea into a proposal before implementation starts. That gives you a shared view of:

  • the goal

  • the scope

  • the task breakdown

  • the validation criteria

This makes AI feel more like a planning partner than an auto-editor.

2. Read-only / edit dual mode

Sometimes you want analysis, not changes. Hagicode separates those two cases clearly:

  • Read-only mode for exploring unfamiliar code, tracing bugs, and understanding architecture

  • Edit mode for implementing features, fixing defects, and refactoring with intent

That boundary makes it easier to trust the workflow.

3. Project context matters

Hagicode focuses on project-level understanding instead of isolated code snippets:

  • it looks at repository structure and existing patterns

  • it supports multi-turn conversation, task tracking, and tool usage

  • it works better as a long-running engineering partner

4. Team knowledge stays visible

Proposal and archive flows help preserve the reason behind a change, not just the final diff. That matters when teams grow, hand work off, or revisit earlier decisions.

Efficient: turn common actions into one smooth flow

The “Efficient” part of Hagicode is about reducing context switching and helping work move in a natural sequence.

Understand first, then choose whether the AI should move into editing work.

The current product already combines session progress, project status, and repository context into one board.

1. One workflow from understanding to delivery

A common workflow looks like this:

  • import or create a project

  • inspect the code in a read-only session

  • break the change down in a proposal session

  • switch to edit mode to implement

  • generate a better commit message with AI

That is simpler than spreading the same work across disconnected tools.

2. Monospec for multi-repository work

If your work spans more than one repository, Monospec gives you a unified view:

  • coordinate multiple repositories in one place

  • keep conventions aligned across repos

  • give AI a wider context for cross-repo analysis

It works well for microservices, multi-module products, and long-lived platform work.

3. AI Compose Commit for cleaner history

Good code changes still need clear commit history. Hagicode helps generate commit messages that are easier to read and easier to maintain:

  • closer to Conventional Commits style

  • clearer for reviewers and teammates

  • more useful for release notes, rollback, and audits

4. Clear setup paths

Whether you prefer Desktop, Docker Compose, or a specific Agent CLI stack, the docs aim to keep the setup path explicit so you can start faster with less guesswork.

Who is Hagicode for?

RoleWhat you getNew engineersFaster onboarding into unfamiliar codebasesDevelopersLess switching between analysis, implementation, and commit cleanupTechnical leadsBetter control over complex changes and decision traceabilityMulti-repo teamsA more unified way to coordinate work across repositories

System Requirements

Windows
macOS
SteamOS + Linux
    Minimum:
    • Requires a 64-bit processor and operating system
    • OS: Windows 10
    • Memory: 4 GB RAM
    • Network: Broadband Internet connection
    • Storage: 10 GB available space
    Recommended:
    • Requires a 64-bit processor and operating system
    • OS: Windows 11
    • Memory: 32 GB RAM
    • Network: Broadband Internet connection
    • Storage: 1024 GB available space
    Minimum:
    • Memory: 4 GB RAM
    • Storage: 10 GB available space
    Recommended:
    • Memory: 32 MB RAM
    • Storage: 1024 GB available space
* Starting February 15, 2024, the Steam Client will no longer support 32-bit games or macOS 10.14 or lower.
    Minimum:
    • Memory: 4 GB RAM
    • Storage: 10 GB available space
    Recommended:
    • Memory: 32 GB RAM
    • Storage: 1024 GB available space
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