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Beads: Distributed Task Management for AI Agents

AI-Coding Development-Tools Task-Management Agents Project-Planning

Beads brings a refreshing take on agent-friendly task management, using a dependency-aware, distributed DAG model backed by git. While it’s still rapidly evolving, my experience adapting Beads has been positive—no major growing pains so far, likely because I’m integrating it as an agent memory and not as my exclusive planning tool.

Beads distributed task management DAG visualization


What Stands Out

  • DAG + Priority Model: Beads natively organizes tasks with dependencies and priorities, making long-horizon agent planning much easier than vanilla markdown TODOs.
  • Distributed Git-Backed Design: Issues sync via regular git operations, so collaborating across machines and agents is seamless.
  • Agent-Centric Workflow: Designed for coding agents to file, update, and track tasks for you. Human users mostly manage initialization and hygiene, leaving agents to handle the rest.
  • CLI & API Integrations: Easy to experiment with in your local setup, and plays well with other agent frameworks and planning tools.

Caveats & Considerations

  • Alpha-Quality: Beads is under heavy development. Bugs and version churn are expected, but the developer (and contributor community) fix issues quickly.
  • Not a One-Size-Fits-All Tracker: I haven’t relied solely on Beads—I recommend it for agent-task management, not for entire teams, org-wide roadmaps, or finished/archived work. Keep established tools (GitHub Issues, Jira, etc.) on hand.
  • Migration and Setup: Upgrading between versions (e.g., hash-based IDs) requires a bit of care, but the documentation covers most migration scenarios.
  • Session Hygiene: Some manual cleanup and cross-tool coordination (“landing the plane”) is still useful, but not a blocker.

Best Practices & Recommendations

  • Use Beads for active agent workflows, dependency planning, and ready-to-work detection.
  • Pair it with broader planning frameworks for high-level goals, future roadmaps, and archiving.
  • Experiment in side projects before bringing into larger scale, production environments.
  • Don’t expect Beads to be invisible—agents, and occasionally humans, need to reference issue IDs and help sync state.

Technical Details

Git-Native Architecture

Beads uses Git as its distributed database—no servers, just version control:

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Amp Coding Agent: Features That Make It Stand Out

AI-Coding Development-Tools Amp Coding-Agents

I’m constantly evaluating new coding agents, but one that’s consistently impressed me over the past few months is Amp . Hamel Husain recently wrote an excellent deep dive into Amp’s features that highlighted several capabilities I think make it particularly noteworthy for developers.

Amp Coding Agent Features

Standout Features

While Amp has all the expected features—MCP support, project context management, permissions systems—it’s the distinctive capabilities that really set it apart.

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