I'm sometime using Claude Code for the work, and I really like to parallelize multiple agents. So I'm wondering how you manage two workers who are editing a same file?
oups, I just realized you already explain you're using a git worktree. Sorry about that!
I think the demo statement idea is really clever! Without something like that, agents always build layers of plumbing that never connect to anything visible...
I've seen the same problem by using CC on my own projects.
Anthropic just shipped Agent Teams for Claude Code (https://news.ycombinator.com/item?id=46902368). I've been building the same thing independently for months, but with a different architecture that solves the two biggest problems people flagged in that thread: file conflicts and quality.
Their approach uses file locking. Tasks have to be file-disjoint or agents overwrite each other. CAS uses git worktrees instead. Each agent gets its own full copy of the repo on its own branch. Three agents can edit the same file simultaneously and the supervisor merges everything back. No locks, no file-disjoint constraint.
The other problem: agents that say "done" when they're not. CAS has verification gates. Workers self-verify before closing (no TODOs, code is wired up, tests pass). Tasks enter pending_verification and workers can't claim new work until it clears. This was born out of pain. Without it, agents mark tasks done while leaving half-connected code everywhere.
`cas` launches a TUI with a supervisor. You give it an epic and it takes over: analyzes the tasks, figures out the right implementation phases based on dependencies, determines how many workers can run in parallel without file conflicts, and spawns them. Each task gets a demo statement describing the observable outcome ("User types query, results filter live"). This was the single biggest quality lever I found. Without it, agents default to building layers of plumbing that never connect to a working feature.
For inter-agent messaging, we reverse-engineered Claude Code's Team feature to build a push-based SQLite message queue. The previous version injected prompts by writing raw bytes into the terminal multiplexer. It worked, but barely. Now the supervisor sends a message and the worker's next MCP call picks it up. Clean and reliable.
Workers claim tasks via a lease system (renewed by heartbeat) to prevent double-claiming. The supervisor reviews completed work, merges the branch, syncs remaining workers, and assigns next tasks.
The TUI has side-by-side/tabbed views, session recording/playback, desktop notifications, and detach/reattach. Terminal emulation uses a custom VT parser based on Ghostty's.
Persistent context
CAS also runs as an MCP server (55+ tools) so agents remember things between sessions. 4-tier memory inspired by MemGPT. Rules that earn trust (Draft > Proven > Stale) and auto-sync to .claude/rules/. Full-text search via Tantivy BM25. Everything local in SQLite.
What's hard
Agent coordination is a distributed systems problem wearing a trenchcoat. Stale leases, zombie worktrees, agents that lie about completion. We've added heartbeats, verification gates, and lease expiry, but supervisor quality still varies with epic complexity. The honest answer is this is an ongoing arms race.
I'm sometime using Claude Code for the work, and I really like to parallelize multiple agents. So I'm wondering how you manage two workers who are editing a same file?
oups, I just realized you already explain you're using a git worktree. Sorry about that!
I think the demo statement idea is really clever! Without something like that, agents always build layers of plumbing that never connect to anything visible...
I've seen the same problem by using CC on my own projects.
Anthropic just shipped Agent Teams for Claude Code (https://news.ycombinator.com/item?id=46902368). I've been building the same thing independently for months, but with a different architecture that solves the two biggest problems people flagged in that thread: file conflicts and quality.
Their approach uses file locking. Tasks have to be file-disjoint or agents overwrite each other. CAS uses git worktrees instead. Each agent gets its own full copy of the repo on its own branch. Three agents can edit the same file simultaneously and the supervisor merges everything back. No locks, no file-disjoint constraint.
The other problem: agents that say "done" when they're not. CAS has verification gates. Workers self-verify before closing (no TODOs, code is wired up, tests pass). Tasks enter pending_verification and workers can't claim new work until it clears. This was born out of pain. Without it, agents mark tasks done while leaving half-connected code everywhere.
GitHub: https://github.com/codingagentsystem/cas Website: https://cas.dev
How it works
`cas` launches a TUI with a supervisor. You give it an epic and it takes over: analyzes the tasks, figures out the right implementation phases based on dependencies, determines how many workers can run in parallel without file conflicts, and spawns them. Each task gets a demo statement describing the observable outcome ("User types query, results filter live"). This was the single biggest quality lever I found. Without it, agents default to building layers of plumbing that never connect to a working feature.
For inter-agent messaging, we reverse-engineered Claude Code's Team feature to build a push-based SQLite message queue. The previous version injected prompts by writing raw bytes into the terminal multiplexer. It worked, but barely. Now the supervisor sends a message and the worker's next MCP call picks it up. Clean and reliable.
Workers claim tasks via a lease system (renewed by heartbeat) to prevent double-claiming. The supervisor reviews completed work, merges the branch, syncs remaining workers, and assigns next tasks.
The TUI has side-by-side/tabbed views, session recording/playback, desktop notifications, and detach/reattach. Terminal emulation uses a custom VT parser based on Ghostty's.
Persistent context
CAS also runs as an MCP server (55+ tools) so agents remember things between sessions. 4-tier memory inspired by MemGPT. Rules that earn trust (Draft > Proven > Stale) and auto-sync to .claude/rules/. Full-text search via Tantivy BM25. Everything local in SQLite.
What's hard
Agent coordination is a distributed systems problem wearing a trenchcoat. Stale leases, zombie worktrees, agents that lie about completion. We've added heartbeats, verification gates, and lease expiry, but supervisor quality still varies with epic complexity. The honest answer is this is an ongoing arms race.
Getting started
curl -fsSL https://cas.dev/install.sh | sh cas init --yes && cas
~235K lines of Rust, 17 crates, MIT licensed. Happy to answer questions.