Roadmap

What we are building, in order. This is a living document — priorities shift based on user feedback.

Have a feature request? Open an issue on GitHub

Shipped

v0.1.0
Loop detection via VS Code diagnostics API
Fires when the same error hash appears 2–5× in a session depending on sensitivity setting.
Edit-pattern loop detection
Detects when you are editing the same region of code repeatedly with no forward progress.
TypeScript context engine (~80% token reduction)
Free tier. Extracts imports and a focused window around the current error.
Rust context engine (89–99% token reduction)
Pro tier. Full AST parse, Shannon entropy scoring, Myers delta, memory cache.
MCP server support
Setup path for Claude Code, Cursor, Windsurf, Codex CLI, Zed, and VS Code / Copilot.
Shell hooks — CLI output compression
bash, zsh, fish on Windows (WSL), macOS, Linux. 60–90% reduction on npm, git, docker output.
Multi-IDE auth — VS Code, Cursor, Windsurf
URI callback scheme auto-detected from vscode.env.uriScheme.
Windows · macOS · Linux platform support
x64 and ARM64. Binary distributed inside platform-specific VSIX.
Session sync to web dashboard
Metrics sync every 5 minutes and on session end. The web dashboard refreshes periodically for signed-in users.

In Progress

v0.2.0
Web dashboard — tighter sync cadence
Reduce the gap between local session changes and what appears in the signed-in web dashboard.
Metrics durability
Add stronger retry and offline queue behavior so metrics are not dropped when the API is temporarily unreachable.
Marketplace hardening
Keep tightening metadata, packaging, and onboarding details for smoother Marketplace review and install success.
Billing and entitlement wiring
Turn the existing paid-tier story into explicit product behavior instead of copy-only gating.

Next Up

v0.3.0
Smart suggestions — AI-powered break-out hints
When a loop is detected, LoopGuard asks Claude to suggest three fundamentally different approaches — not just renamed versions of the same fix.
Prompt history tracking
LoopGuard stores a hash of every AI prompt you send. Detects when you re-send the same prompt and warns you before you waste another turn.
Per-file loop heatmap
Shows which files in your project are causing the most loops across all sessions. Identifies structural bugs, not just session-level issues.
Slack / Discord alerts for teams
Teams can route loop alerts to a shared channel. Useful for pair debugging and onboarding tracking.

Planned

v1.0.0
JetBrains IDE support (IntelliJ, PyCharm, WebStorm)
Separate plugin using the IntelliJ Platform SDK. Same loop detection and context engine, different activation model.
Team plan — shared dashboards
Org-level view of loop rates, token spend, and time wasted across all developers. Identify which parts of the codebase create the most AI friction.
Token budget enforcement
Set a daily token budget per developer. LoopGuard warns when 80% is consumed and blocks context copies when the limit is hit.
Multi-model routing
Route cheap queries (boilerplate, formatting) to smaller models and only send complex loop-breaking queries to GPT-4 / Claude Opus.
Context quality scoring
After each AI response, score how relevant it was. Feed this back into the entropy model to improve future context selection.

Research

Future
Offline LLM routing
Route context-heavy requests to a local model (Ollama, LM Studio) to eliminate API costs entirely for routine tasks.
Cross-session loop database
Aggregate loop patterns across all users (opt-in, anonymized) to identify the top 100 error patterns that cost developers the most time industry-wide.
CI/CD integration
Run LoopGuard in CI to detect loops in automated test runs — useful for flaky test debugging and build pipeline optimization.