Git for AI Coding
The default infrastructure for AI-native software development.
curl -sSL https://bitloops.com/install.sh | bashYour data are not sent to our servers. Apache 2.0 licensed. Runs locally. Written in Rust.
AI Chats Linked to Commits
Track every assistant run against branch, commit, and diff history for confident review.
Local-First by Default
Keep source code, prompts, and context in your environment with no mandatory cloud dependency.
CLI-First Workflows
Drive your AI-native workflow from the Rust CLI and launch the dashboard locally with one command.
Constraint Enforcement
Combine deterministic checks and LLM-aware guardrails before generated code reaches production.
AI Coding Is Powerful. But It's Chaotic.
Modern teams are adopting AI coding assistants fast, but the workflow controls are still missing.
Modern teams are using
But today
- No unified conversation history
- No audit trail between prompts and commits
- No structured context management
- No enforcement of architectural constraints
- Sensitive code flows through opaque systems
You do not control the workflow.
You do not control the guarantees.
You do not control the long-term impact.
Bitloops Is the Infrastructure Layer for AI Coding
Bitloops runs locally as a Rust CLI and gives teams a reliable workflow foundation.
Tracks AI assistant conversations
Links them to git commits
Injects targeted, structured context
Enforces constraints on generated code (Coming Soon)
All without sending your code to our servers.
Core Pillars
The platform architecture is built around privacy, attribution, context intelligence, and enforceable engineering constraints.
Your Code Never Leaves Your Environment
Local-first foundation
- Runs locally
- Works offline
- Stores data in your repository
- Soon: configurable self-hosted DB
- No code or commit history sent to Bitloops
- Optional high-level telemetry (opt-in only)
Enterprise-ready posture
- No compliance headaches
- No vendor data exposure
- No training on your code
Bitloops is infrastructure, not a cloud proxy.
Every AI Conversation Connected to Real Commits
Tracks conversations across
- Claude Code
- Gemini
- Cursor
- OpenCode
- Agent frameworks
Associates sessions with
- Branch
- Commit
- Diff
- Author
Dashboard visibility
- AI session timeline
- Prompt -> response -> commit mapping
- Per-agent contribution breakdown
- AI contribution vs human edits
- Repository-level activity insights
Outcome
- Auditable
- Measurable
- Reviewable
Version control for AI interactions.
Stop Manually Managing Context
Developers today
- Attach files manually
- Maintain context docs
- Re-explain architecture to every agent
- Copy-paste between tools
Bitloops does this instead
- Extracts relevant project context
- Injects only targeted information
- Maintains shared organizational knowledge
- Reduces prompt overhead
Context as infrastructure, not tribal knowledge.
AI Output That Respects Your Architecture
Future capabilities
- Enforce architectural rules
- Prevent anti-patterns
- Enforce domain boundaries
- Validate design invariants
- Ensure codebase-wide consistency
Hybrid enforcement approach
- Deterministic rules
- Static analysis
- LLM-based reasoning
- Policy enforcement
This is not AI linting. It is organizational constraint enforcement for AI-generated code.
Local Dashboard. Zero Cloud Dependency.
`bitloops dashboard` launches a local web server for direct observability.
bitloops dashboard
- AI session history
- Agent comparison
- Commit mapping
- Context usage
- Contribution metrics
- Constraint violations (Coming Soon)
Full observability. No SaaS required.
How It Works
What Bitloops does locally while you keep using your existing AI tools.
Install
Choose your preferred install method.
curl
curl -sSL https://bitloops.com/install.sh | bashbrew
brew install bitloops/tap/bitloopscargo
cargo install bitloopsEnable and connect agents
bitloops enable auto-detects supported assistants.
Work as usual
Keep using your AI tools and existing developer workflow.
Bitloops tracks and structures workflow metadata
Git hooks, local metadata, structured storage, and an agent-agnostic abstraction layer run in the background.
- Git hooks
- Local metadata
- Structured storage
- Agent-agnostic abstraction layer
Apache 2.0. No Lock-In.
Open codebase you can inspect, extend, and run yourself.
Open foundation
- Fully open
- Extensible
- Pluggable
- Vendor-neutral
Built for
- Platform teams
- DevEx teams
- OSS-oriented engineers
Quick Comparison
A practical view of where Bitloops fits compared to standalone assistants and cloud platforms.
| Feature | AI Agents | Cloud AI Platforms | Bitloops |
|---|---|---|---|
| Local-first | ❌ | ❌ | ✅ |
| Git-linked sessions | ❌ | ❌ | ✅ |
| Cross-agent tracking | ❌ | ❌ | ✅ |
| Deterministic constraint enforcement | ❌ | ❌ | ✅ |
| Vendor lock-in | High | High | None |
Who Bitloops Is For
Best fit for teams already relying on AI coding tools in real projects.
For
- Engineering teams using AI heavily
- CTOs concerned about governance
- Platform engineering teams
- Security-conscious organizations
- Teams scaling AI usage
Roadmap
Upcoming work based on user feedback and the current engineering roadmap.
Bring Structure to AI Coding.
curl -sSL https://bitloops.com/install.sh | bash