GM! Claw Code is starting to become something really interesting.
We’re moving to a system where multiple agents can coordinate work without the human sitting in a terminal micromanaging everything.
Built in Rust, memory-aware, multi-model, persistent sessions.
But the important part is the workflow itself:
human gives direction → agents plan, execute, review, retry.
Current focus:
• improving agent coordination
• better memory between sessions
• parallel task execution
• cleaner review / retry loops
• reducing context overload between agents
• making the CLI feel instant even on large projects
Next plans:
• local-first execution mode
• shared memory between multiple claws
• autonomous repo workflows (issues → PRs → review)
• better terminal UI and live activity tracking
• plugin / tool system for custom workflows
• lightweight background agents running continuously
We’re continue building $CC.
Our tokens CA : 0xed21b113b9E7AD8A569Eb838eFbfCc79660B87D8
https://t.co/T6IudcWhbf
$CC Product Principles :
1. State machine first — every worker has explicit lifecycle states.
2. Events over scraped prose — channel output should be derived from typed events.
3. Recovery before escalation — known failure modes should auto-heal once before asking for help.
4. Branch freshness before blame — detect stale branches before treating red tests as new regressions.
5. Partial success is first-class — e.g. MCP startup can succeed for some servers and fail for others, with structured degraded-mode reporting.
6. Terminal is transport, not truth — tmux/TUI may remain implementation details, but orchestration state must live above them.
7. Policy is executable — merge, retry, rebase, stale cleanup, and escalation rules should be machine-enforced.
https://t.co/T6IudcWhbf
$CC Current Pain Points :
1. Session boot is fragile
• trust prompts can block TUI startup
• prompts can land in the shell instead of the coding agent
• “session exists" does not mean "session is ready"
2. Truth is split across layers
• tmux state
• clawhip event stream
• git/worktree state
• test state
• gateway/plugin/MCP runtime state
3. Events are too log-shaped
• claws currently infer too much from noisy text
• important states are not normalized into machine-readable events
4. Recovery loops are too manual
• restart worker
• accept trust prompt
• re-inject prompt
• detect stale branch
• retry failed startup
• classify infra vs code failures manually
5. Branch freshness is not enforced enough
• side branches can miss already-landed main fixes
• broad test failures can be stale-branch noise instead of real regressions
6. Plugin/MCP failures are under-classified
• startup failures, handshake failures, config errors, partial startup, and degraded mode are not exposed cleanly enough
7. Human UX still leaks into claw workflows
• too much depends on terminal/TUI behavior instead of explicit agent state transitions and control APIs
https://t.co/T6IudcWhbf
Definition of "clawable"
A clawable harness is:
• deterministic to start
• machine-readable in state and failure modes
• recoverable without a human watching the terminal
• branch/test/worktree aware
• plugin/MCP lifecycle aware
• event-first, not log-first
• capable of autonomous next-step execution
$CC Contract Address has been updated on the site.
Clawable Coding Harness Roadmap : Turn claw-code into the most clawablecoding harness:
• no human-first terminal assumptions
• no fragile prompt injection timing
• no opaque session state
• no hidden plugin or MCP failures
• no manual babysitting for routine recovery
This roadmap assumes the primary users are claws wired through hooks, plugins, sessions, and channel events.
https://t.co/T6IudcWhbf
If you only look at the generated files in this repository, you are looking at the wrong layer.
The Python rewrite was a byproduct. The Rust rewrite was also a byproduct. The real thing worth studying is the system that produced them: a clawhip-based coordination loop where humans give direction and autonomous claws execute the work.
Claw Code is not just a codebase. It is a public demonstration of what happens when:
• a human provides clear direction,
• multiple coding agents coordinate in parallel,
• notification routing is pushed out of the agent context window,
• planning, execution, review, and retry loops are automated,
• and the human does not sit in a terminal micromanaging every step.
our token $CC is live on @flaunchgg.
CA : 0xed21b113b9E7AD8A569Eb838eFbfCc79660B87D8
web : https://t.co/T6IudcWhbf
Introducing Claw Code : The fastest CLI agent harness ever built. Rust-Powered, memory aware.
Built in Rust using oh-my-codex.
CAPABILITIES :
- Rust Core Engine
> A blazing-fast foundation built in Rust with zero-cost abstractions. Every operation is memory-safe, concurrency-friendly, and ruthlessly optimized.

- Agent Harness
> Orchestrate AI agents with deterministic, predictable behavior. The claw CLI wraps model APIs into a unified interface you can trust.

- Session Memory
> Persistent context that survives across sessions and reboots. Your agent remembers everything, from project state to conversation history.

- Multi-Model
> Native support for Anthropic, OpenAI, and emerging providers. Switch models mid-session without losing context or momentum.
CA : 0xed21b113b9E7AD8A569Eb838eFbfCc79660B87D8
https://t.co/T6IudcWhbf
Claw Code is Built for speed.
Designed to scale.
Every component is engineered with zero-cost abstractions. The Rust workspace compiles to a single binary that runs anywhere—from developer laptops to CI pipelines—delivering consistent, memory-safe performance without runtime overhead.
https://t.co/T6IudcWhbf