Keshro, plan and execute migrations with AI agents
Git worktree isolation with context inheritance between agents solves real coordination problems.
Distributed multi-agent research engine with dynamic strategy planning, durable stream-based coordination, and controlled synthesis
Isolated agent cohorts over durable streams beats prompt-based disagreement, but MCP and Anthropic already do multi-agent.
AI researchers, multi-agent system builders, prompt engineers
Anthropic multi-shot prompting · LangGraph · Smolagents
That means, coordination is just done over a log with natural language, which allows us to rewire topology of agents mid-run, fork, merge, spawn breakout rooms or build any research methodology on the fly depending on the question. If something goes wrong / crashes, agents can resume from where they left off. Further, if the log or stream is serverless, agents can connect over the log from any machine anywhere in the world and collaborate on tasks / research.
Git worktree isolation with context inheritance between agents solves real coordination problems.
Fresh context per phase stops AI agents from reviewing their own work.
BEAM kernel with deterministic replay solves agent state durability problems.
Single Go binary: Telegram → Claude agents in isolated Docker with swarms, memory, Nix.
Voice-controlled agent orchestration in a sea of similar multi-agent tools.
Container isolation and tmux sessions for async multi-agent workflows.