ai-coding Tools

ThinkRail is an agentic IDE that customizes itself around your workflow. It solves the problem of agent-assisted development creating a mess in your main branch by isolating each agent's work into its own git worktree workspace. It's built spec-first, maintaining a connected graph of project specs that agents can actually read and use. It's for developers who want to pair with AI agents across code, terminals, and diffs without sacrificing project integrity or their main branch.

AAS Core is a local control plane that puts you in control of AI agent automation. It solves the problem of blind trust by letting your agent discover and select from 2,600+ skills, while you inspect, validate, and approve the final execution plan before any changes are made. It's for developers and teams using AI agents like Claude Code who want to leverage powerful automation while maintaining oversight and safety in their projects.

OpenRig is a multi-agent harness that orchestrates Claude Code, Codex, and Pi to work together as a coordinated team. It solves the problem of managing complex, long-term coding projects by delegating specialized tasks to different AI agents, tracking their work, and consolidating results. It's designed for developers and teams who need to tackle large-scale software projects that require sustained, collaborative effort over weeks or months.

Code Review Graph is a local-first code intelligence graph for MCP and CLI. It builds a persistent, semantic map of your codebase, enabling AI coding assistants to understand context and dependencies without reading every file. This dramatically reduces context overhead in code reviews and large-repository workflows, making AI tools faster and more accurate. It's built for developers and teams working in complex codebases who want to leverage AI assistance without the performance and cost penalties of massive context windows.

Reasonix is a DeepSeek-native AI coding agent for your terminal, engineered to drastically reduce costs in long development sessions. It solves the problem of paying full price for repetitive prompt context by maintaining a byte-stable prefix that achieves 90%+ cache hits with DeepSeek's infrastructure, collapsing input token costs to roughly one-fifth. It's built for developers who want a persistent, cost-effective AI assistant directly in their CLI/TUI, desktop app, or editor, leveraging the same local engine across all interfaces.