"To achieve great things, two things are needed: a plan and not quite enough time." - Leonard Bernstein
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Bernstein is a deterministic orchestrator for CLI coding agents (Claude Code, Codex, Gemini CLI, and 40+ more). Scheduling is plain Python - no LLM in the coordination loop - so runs are reproducible end to end. Every task runs in its own git worktree behind lint/type/test gates. Results stay checkable after the fact: an always-on lineage spine and replay journal, plus an opt-in HMAC-chained audit log (--audit) with receipts you can verify offline. Air-gap install profile included. Apache-2.0.
Four things set it apart; everything after is detail.
- No LLM in the coordination loop. Scheduling is plain Python, so a run is reproducible end to end. Replay yesterday's plan and get yesterday's task graph.
- Checkable after the fact. The lineage spine and replay journal record every run; the opt-in audit chain adds receipts you verify offline. Non-determinism surfaces as a hash mismatch at the exact step, not a flaky re-run.
- Isolated by construction. Each task gets its own git worktree behind merge gates. No shared mutable state between agents.
- Broad and local. 40+ CLI agent adapters plus a generic
--promptwrapper, file-based state, no SaaS hop, no third-party data plane.
The full list is on the capabilities page; the feature matrix is the exhaustive index.
pipx install bernstein
bernstein init
bernstein -g "fix the failing test in tests/test_foo.py"pip, uv, brew, dnf, npm, Docker, and the air-gapped wheelhouse are covered in the install guide.
Determinism here is something you check, not something you take on faith. Run once with audit enabled, then verify what was recorded:
BERNSTEIN_AUDIT=1 bernstein -g "fix the failing test in tests/test_foo.py"
bernstein replay list # run ids recorded on disk
bernstein replay latest --verify # recompute the journal head, name the first divergent step
bernstein lineage verify <run_id> # recompute the always-on lineage spine
bernstein audit verify # HMAC chain + Merkle seal (written because audit was enabled)The journal and the lineage spine are written on every run. bernstein audit verify only has a chain to check when the run was started with --audit, BERNSTEIN_AUDIT=1, or a compliance preset.
Each goal moves through four stages:
- Decompose. The manager breaks your goal into tasks with roles, owned files, and completion signals. One LLM call, then plain Python from there.
- Spawn. Agents start in isolated git worktrees, one per task. Main branch stays clean.
- Verify. The janitor checks concrete signals: tests pass, files exist, lint clean, types correct.
- Merge. Verified work lands in main. Failed tasks get retried or routed to a different model.
Why the scheduler is plain Python, and what that trades away: why deterministic.
cd your-project
bernstein init # creates .sdd/ workspace + bernstein.yaml
bernstein -g "Add rate limiting" # agents spawn, work in parallel, verify, exit
bernstein live # watch progress in the TUI dashboard
bernstein run plan.yaml # multi-stage plan: skip LLM planning, execute directly
bernstein stop # graceful shutdown with drainThe full operator surface (PR automation, schedules, chat bridges, the autofix daemon) is in operator commands.
Claude Code, Codex CLI, Gemini CLI, GitHub Copilot CLI, Cursor, Aider, Goose, OpenAI Agents SDK, Amp, Cody, Continue, Devin Terminal, Junie, Kilo, Kiro, AWS Q Developer, Ollama, OpenCode, OpenHands, Open Interpreter, gptme, Plandex, AIChat, Letta Code, Qwen, and more. The adapter index carries the full table with install commands; anything else with a --prompt flag works through the generic wrapper.
Mix agents in the same run: cheap local models for boilerplate, heavier cloud models for architecture. bernstein integrations list --installed shows what is available on your machine.
Everything deep lives on the docs site:
| capabilities | the full capability list: MCP server mode, signed agent cards, sandbox backends, artifact sinks, regulatory mappings |
| who this is for | where the value lands, and where Bernstein is the wrong tool |
| workflows | declarative YAML DAGs of agent / command / loop nodes |
| web UI | browser dashboard on the same API the TUI uses |
| cloud execution | run agents on Cloudflare Workers with R2 workspace sync |
| security | scorecard, fuzzing, hardening |
| architecture | how it works under the hood |
Bernstein is named after Leonard Bernstein, the American conductor and composer. The project orchestrates a crew of CLI coding agents the way Bernstein conducted the New York Philharmonic: every player on cue, the score deterministic, the conductor accountable for the result. He is the original orchestrator the project takes its name from.
i wrote bernstein because i was paying $400/month in claude bills running three coding agents in parallel and getting nondeterministic merges. Apache 2.0, solo maintained. Live stats: bernstein.run.
Listed in vinta/awesome-python, covered in Augment Code's open-source agent orchestrators roundup, cited by awesome-agentic-patterns as the production implementation of deterministic zero-LLM orchestration, and featured in Python Weekly #742.
All coverage: 20+ awesome lists, directories, newsletters, and peer citations
The full tracked list, including every awesome-list entry, catalog listing, prior-art citation, and newsletter mention, lives in docs/mentions.md. Entries are added as they appear; corrections welcome by issue or PR.
PRs welcome; CONTRIBUTING.md has setup and code style. Security reports go through SECURITY.md. If Bernstein saves you time: GitHub Sponsors. Contact: forte@bernstein.run.
Citation metadata lives in CITATION.cff. License: Apache-2.0.
Alex Chernysh · GitHub · X · bernstein.run