neilbb

1. Windows users would need WSL. Currently focusing on macOS and Linux.

2. The manager never blocks. She helps me dump tasks into taskwarrior and route them. Since the manager plane is a mesh with p2p communication, no single agent becomes a bottleneck. Each designer connects to 1 or more workers in a star topology, and when workers get blocked, they alert the designer directly rather than waiting.

3. Pane looks interesting. How are you embedding the terminal into the desktop app? Is it a PTY wrapper or something like xterm.js?

using a single plan-reviewer would be slow when there are multiple aspects to review. That's why a local star topology with a plan-review-leader is needed: it spawns multiple reviewers in parallel, each focused on a different aspect.

The problem isn't "skill atrophy" — it's which skills matter more in a changing world. If LLMs genuinely do something better, let them do it and focus on what they do badly.

What I'm exploring now:

1. How to convert tokens to value more efficiently

2. How to orchestrate a large LLM team instead of babysitting one session

3. How to parallelize work and make sure nothing blocks others

4. How to accelerate both productivity and quality control

5. How to make the system evolve itself

To achieve these, it requires much more skill and knowledge, not less.

If you impl this as a backend and connect to Telegram bots, agents can just do `$ ask "Should I do this?"` for agent→human and `$ alert "this thing blocked me"` for coder→planner. That's what I'm actually doing — I have 1 manager + 3 designers + 1 researcher + 2 debugger + 1 communicator + any number of temporal coders/reviewers in my setup, all connected to taskwarrior for task-driven-dev