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loki-mode

v5.9.0

Published

Multi-agent autonomous startup system for Claude Code, Codex CLI, and Gemini CLI

Readme

Loki Mode

The First Truly Autonomous Multi-Agent Startup System

Claude Code Agent Types Loki Mode HumanEval SWE-bench License

Documentation Website | Architecture | Research | Comparisons

PRD → Deployed Product in Zero Human Intervention

Loki Mode transforms a Product Requirements Document into a fully built, tested, deployed, and revenue-generating product while you sleep. No manual steps. No intervention. Just results.


Demo

asciicast

Click to watch Loki Mode build a complete Todo App from PRD - zero human intervention


Presentation

Loki Mode Presentation

9 slides: Problem, Solution, 37 Agents, RARV Cycle, Benchmarks, Multi-Provider, Full Lifecycle

Download PPTX for offline viewing


Usage

Option 1: Claude Code Skill (Recommended)

# Install
git clone https://github.com/asklokesh/loki-mode.git ~/.claude/skills/loki-mode

# Run
claude --dangerously-skip-permissions

# Then say:
Loki Mode with PRD at ./my-prd.md

Option 2: Shell Script

# Clone repo
git clone https://github.com/asklokesh/loki-mode.git
cd loki-mode

# Run directly
./autonomy/run.sh ./my-prd.md

Option 3: npm

npm install -g loki-mode
loki start ./my-prd.md

Option 4: Homebrew (macOS/Linux)

brew install asklokesh/tap/loki-mode
loki start ./my-prd.md

Option 5: Docker

docker run -v $(pwd):/workspace asklokesh/loki-mode:5.1.1 ./my-prd.md

Option 6: VS Code Extension

Install directly from the VS Code Marketplace for a visual interface:

# From VS Code
1. Open Extensions (Cmd+Shift+X / Ctrl+Shift+X)
2. Search "loki-mode"
3. Click Install

# Or via command line
code --install-extension asklokesh.loki-mode

Important: Start the Loki Mode server before using the extension:

loki start              # If using CLI
# or
./autonomy/run.sh       # If running from source

Extension Features:

  • Start/Stop/Pause/Resume sessions from the activity bar
  • Real-time task progress in the sidebar
  • Provider selection (Claude, Codex, Gemini)
  • Status bar showing current phase and progress
  • Quick actions menu (Cmd+Shift+L / Ctrl+Shift+L)

View on Marketplace

See Installation Guide for more details.

Multi-Provider Support (v5.0.0)

Loki Mode supports three AI providers:

# Claude Code (default - full features)
loki start --provider claude ./my-prd.md

# OpenAI Codex CLI (degraded mode)
loki start --provider codex ./my-prd.md

# Google Gemini CLI (degraded mode)
loki start --provider gemini ./my-prd.md

# Or via environment variable
LOKI_PROVIDER=codex loki start ./my-prd.md

Provider Comparison: | Provider | Features | Parallel Agents | Task Tool | |----------|----------|-----------------|-----------| | Claude | Full | Yes (10+) | Yes | | Codex | Degraded | No | No | | Gemini | Degraded | No | No |

See skills/providers.md for full provider documentation.


Benchmark Results

Three-Way Comparison (HumanEval)

| System | Pass@1 | Details | |--------|--------|---------| | Loki Mode (Multi-Agent) | 98.78% | 162/164 problems, RARV cycle recovered 2 | | Direct Claude | 98.17% | 161/164 problems (baseline) | | MetaGPT | 85.9-87.7% | Published benchmark |

Loki Mode beats MetaGPT by +11-13% thanks to the RARV (Reason-Act-Reflect-Verify) cycle.

Full Results

| Benchmark | Score | Details | |-----------|-------|---------| | Loki Mode HumanEval | 98.78% Pass@1 | 162/164 (multi-agent with RARV) | | Direct Claude HumanEval | 98.17% Pass@1 | 161/164 (single agent baseline) | | Direct Claude SWE-bench | 99.67% patch gen | 299/300 problems | | Loki Mode SWE-bench | 99.67% patch gen | 299/300 problems | | Model | Claude Opus 4.5 | |

Key Finding: Multi-agent RARV matches single-agent performance on both benchmarks after timeout optimization. The 4-agent pipeline (Architect->Engineer->QA->Reviewer) achieves the same 99.67% patch generation as direct Claude.

See benchmarks/results/ for full methodology and solutions.


What is Loki Mode?

Loki Mode is a multi-provider AI skill that orchestrates 37 specialized AI agent types across 6 swarms to autonomously build, test, deploy, and scale complete startups. Works with Claude Code, OpenAI Codex CLI, and Google Gemini CLI. It dynamically spawns only the agents you need—5-10 for simple projects, 100+ for complex startups—working in parallel with continuous self-verification.

PRD → Research → Architecture → Development → Testing → Deployment → Marketing → Revenue

Just say "Loki Mode" and point to a PRD. Walk away. Come back to a deployed product.


Why Loki Mode?

Better Than Anything Out There

| What Others Do | What Loki Mode Does | |----------------|---------------------| | Single agent writes code linearly | 100+ agents work in parallel across engineering, ops, business, data, product, and growth | | Manual deployment required | Autonomous deployment to AWS, GCP, Azure, Vercel, Railway with blue-green and canary strategies | | No testing or basic unit tests | 14 automated quality gates: security scans, load tests, accessibility audits, code reviews | | Code only - you handle the rest | Full business operations: marketing, sales, legal, HR, finance, investor relations | | Stops on errors | Self-healing: circuit breakers, dead letter queues, exponential backoff, automatic recovery | | No visibility into progress | Real-time dashboard with agent monitoring, task queues, and live status updates | | "Done" when code is written | Never "done": continuous optimization, A/B testing, customer feedback loops, perpetual improvement |

Core Advantages

  1. Truly Autonomous: RARV (Reason-Act-Reflect-Verify) cycle with self-verification achieves 2-3x quality improvement
  2. Massively Parallel: 100+ agents working simultaneously, not sequential single-agent bottlenecks
  3. Production-Ready: Not just code—handles deployment, monitoring, incident response, and business operations
  4. Self-Improving: Learns from mistakes, updates continuity logs, prevents repeated errors
  5. Zero Babysitting: Auto-resumes on rate limits, recovers from failures, runs until completion
  6. Efficiency Optimized: ToolOrchestra-inspired metrics track cost per task, reward signals drive continuous improvement

Features & Documentation

| Feature | Description | Documentation | |---------|-------------|---------------| | VS Code Extension | Visual interface with sidebar, status bar | Marketplace | | Multi-Provider (v5.0.0) | Claude, Codex, Gemini support | Provider Guide | | CLI (v4.1.0) | loki command for start/stop/pause/status | CLI Commands | | Config Files | YAML configuration support | autonomy/config.example.yaml | | Dashboard | Realtime Kanban board, agent monitoring | Dashboard Guide | | 37 Agent Types | Engineering, Ops, Business, Data, Product, Growth | Agent Definitions | | RARV Cycle | Reason-Act-Reflect-Verify workflow | Core Workflow | | Quality Gates | 7-gate review system with anti-sycophancy | Quality Control | | Memory System | Episodic, semantic, procedural memory | Memory Architecture | | Parallel Workflows | Git worktree-based parallelism | Parallel Workflows | | GitHub Integration | Issue import, PR creation, status sync | GitHub Integration | | Distribution | npm, Homebrew, Docker installation | Installation Guide | | Research Foundation | OpenAI, DeepMind, Anthropic patterns | Acknowledgements | | Benchmarks | HumanEval 98.78%, SWE-bench 99.67% | Benchmark Results | | Comparisons | vs Auto-Claude, Cursor | Auto-Claude, Cursor |


Dashboard & Real-Time Monitoring

Monitor your autonomous startup being built in real-time through the Loki Mode dashboard:

Agent Monitoring

Track all active agents in real-time:

  • Agent ID and Type (frontend, backend, QA, DevOps, etc.)
  • Model Badge (Sonnet, Haiku, Opus) with color coding
  • Current Work being performed
  • Runtime and Tasks Completed
  • Status (active, completed)

Task Queue Visualization

Four-column kanban view:

  • Pending: Queued tasks waiting for agents
  • In Progress: Currently being worked on
  • Completed: Successfully finished (shows last 10)
  • Failed: Tasks requiring attention

Live Status Monitor

# Watch status updates in terminal
watch -n 2 cat .loki/STATUS.txt
╔════════════════════════════════════════════════════════════════╗
║                    LOKI MODE STATUS                            ║
╚════════════════════════════════════════════════════════════════╝

Phase: DEVELOPMENT

Active Agents: 47
  ├─ Engineering: 18
  ├─ Operations: 12
  ├─ QA: 8
  └─ Business: 9

Tasks:
  ├─ Pending:     10
  ├─ In Progress: 47
  ├─ Completed:   203
  └─ Failed:      0

Last Updated: 2026-01-04 20:45:32

Access the dashboard:

# Automatically opens when running autonomously
./autonomy/run.sh ./docs/requirements.md

# Or open manually
open .loki/dashboard/index.html

Auto-refreshes every 3 seconds. Works with any modern browser.


Autonomous Capabilities

RARV Cycle: Reason-Act-Reflect-Verify

Loki Mode doesn't just write code—it thinks, acts, learns, and verifies:

1. REASON
   └─ Read .loki/CONTINUITY.md including "Mistakes & Learnings"
   └─ Check .loki/state/ and .loki/queue/
   └─ Identify next task or improvement

2. ACT
   └─ Execute task, write code
   └─ Commit changes atomically (git checkpoint)

3. REFLECT
   └─ Update .loki/CONTINUITY.md with progress
   └─ Update state files
   └─ Identify NEXT improvement

4. VERIFY
   └─ Run automated tests (unit, integration, E2E)
   └─ Check compilation/build
   └─ Verify against spec

   IF VERIFICATION FAILS:
   ├─ Capture error details (stack trace, logs)
   ├─ Analyze root cause
   ├─ UPDATE "Mistakes & Learnings" in CONTINUITY.md
   ├─ Rollback to last good git checkpoint if needed
   └─ Apply learning and RETRY from REASON

Result: 2-3x quality improvement through continuous self-verification.

Perpetual Improvement Mode

There is NEVER a "finished" state. After completing the PRD, Loki Mode:

  • Runs performance optimizations
  • Adds missing test coverage
  • Improves documentation
  • Refactors code smells
  • Updates dependencies
  • Enhances user experience
  • Implements A/B test learnings

It keeps going until you stop it.

Auto-Resume & Self-Healing

Rate limits? Exponential backoff and automatic resume. Errors? Circuit breakers, dead letter queues, retry logic. Interruptions? State checkpoints every 5 seconds—just restart.

# Start autonomous mode
./autonomy/run.sh ./docs/requirements.md

# Hit rate limit? Script automatically:
# ├─ Saves state checkpoint
# ├─ Waits with exponential backoff (60s → 120s → 240s...)
# ├─ Resumes from exact point
# └─ Continues until completion or max retries (default: 50)

Quick Start

1. Install

# Option A: npm (recommended)
npm install -g loki-mode

# Option B: Homebrew (macOS/Linux)
brew tap asklokesh/tap && brew install loki-mode
loki-mode-install-skill  # Set up Claude Code integration

# Option C: Docker
docker pull asklokesh/loki-mode:5.0.0

# Option D: Git clone
git clone https://github.com/asklokesh/loki-mode.git ~/.claude/skills/loki-mode

See Installation Guide for detailed instructions.

2. Create a PRD

# Product: AI-Powered Todo App

## Overview
Build a todo app with AI-powered task suggestions and deadline predictions.

## Features
- User authentication (email/password)
- Create, read, update, delete todos
- AI suggests next tasks based on patterns
- Smart deadline predictions
- Mobile-responsive design

## Tech Stack
- Next.js 14 with TypeScript
- PostgreSQL database
- OpenAI API for suggestions
- Deploy to Vercel

Save as my-prd.md.

3. Run Loki Mode

# Using the CLI (v4.1.0)
loki start ./my-prd.md

# Or using run.sh directly
./autonomy/run.sh ./my-prd.md

# Or manual mode in Claude Code
claude --dangerously-skip-permissions
> Loki Mode with PRD at ./my-prd.md

4. Monitor Progress

# Check status
loki status

# Open dashboard in browser
loki dashboard

# Or watch terminal output
watch -n 2 cat .loki/STATUS.txt

5. Walk Away

Seriously. Go get coffee. It'll be deployed when you get back.

That's it. No configuration. No manual steps. No intervention.


CLI Commands (v4.1.0)

The loki CLI provides easy access to all Loki Mode features:

| Command | Description | |---------|-------------| | loki start [PRD] | Start Loki Mode with optional PRD file | | loki stop | Stop execution immediately | | loki pause | Pause after current session | | loki resume | Resume paused execution | | loki status | Show current status | | loki dashboard | Open dashboard in browser | | loki import | Import GitHub issues as tasks | | loki config show | Show configuration | | loki config init | Create config file from template | | loki version | Show version |

Configuration File

Create a YAML config file for persistent settings:

# Initialize config
loki config init

# Or copy template manually
cp ~/.claude/skills/loki-mode/autonomy/config.example.yaml .loki/config.yaml

Config search order: .loki/config.yaml (project) -> ~/.config/loki-mode/config.yaml (global)


Agent Swarms (37 Types)

Loki Mode has 37 predefined agent types organized into 6 specialized swarms. The orchestrator spawns only what you need—simple projects use 5-10 agents, complex startups spawn 100+.

Engineering (8 types)

eng-frontend eng-backend eng-database eng-mobile eng-api eng-qa eng-perf eng-infra

Operations (8 types)

ops-devops ops-sre ops-security ops-monitor ops-incident ops-release ops-cost ops-compliance

Business (8 types)

biz-marketing biz-sales biz-finance biz-legal biz-support biz-hr biz-investor biz-partnerships

Data (3 types)

data-ml data-eng data-analytics

Product (3 types)

prod-pm prod-design prod-techwriter

Growth (4 types)

growth-hacker growth-community growth-success growth-lifecycle

Review (3 types)

review-code review-business review-security

See references/agents.md for complete agent type definitions.


How It Works

Skill Architecture (v3.0+)

Loki Mode uses a progressive disclosure architecture to minimize context usage:

SKILL.md (~190 lines)         # Always loaded: core RARV cycle, autonomy rules
skills/
  00-index.md                  # Module routing table
  agents.md                    # Agent dispatch, A2A patterns
  production.md                # HN patterns, batch processing, CI/CD
  quality-gates.md             # Review system, severity handling
  testing.md                   # Playwright, E2E, property-based
  model-selection.md           # Task tool, parallelization
  artifacts.md                 # Code generation patterns
  patterns-advanced.md         # Constitutional AI, debate
  troubleshooting.md           # Error recovery, fallbacks
references/                    # Deep documentation (23KB+ files)

Why this matters:

  • Original 1,517-line SKILL.md consumed ~15% of context before any work began
  • Now only ~1% of context for core skill + on-demand modules
  • More room for actual code and reasoning

Phase Execution

| Phase | Description | |-------|-------------| | 0. Bootstrap | Create .loki/ directory structure, initialize state | | 1. Discovery | Parse PRD, competitive research via web search | | 2. Architecture | Tech stack selection with self-reflection | | 3. Infrastructure | Provision cloud, CI/CD, monitoring | | 4. Development | Implement with TDD, parallel code review | | 5. QA | 14 quality gates, security audit, load testing | | 6. Deployment | Blue-green deploy, auto-rollback on errors | | 7. Business | Marketing, sales, legal, support setup | | 8. Growth | Continuous optimization, A/B testing, feedback loops |

Parallel Code Review

Every code change goes through 3 specialized reviewers simultaneously:

IMPLEMENT → REVIEW (parallel) → AGGREGATE → FIX → RE-REVIEW → COMPLETE
                │
                ├─ code-reviewer (Sonnet) - Code quality, patterns, best practices
                ├─ business-logic-reviewer (Sonnet) - Requirements, edge cases, UX
                └─ security-reviewer (Sonnet) - Vulnerabilities, OWASP Top 10

Severity-based issue handling:

  • Critical/High/Medium: Block. Fix immediately. Re-review.
  • Low: Add // TODO(review): ... comment, continue.
  • Cosmetic: Add // FIXME(nitpick): ... comment, continue.

Directory Structure

.loki/
├── state/          # Orchestrator and agent states
├── queue/          # Task queue (pending, in-progress, completed, dead-letter)
├── memory/         # Episodic, semantic, and procedural memory
├── metrics/        # Efficiency tracking and reward signals
├── messages/       # Inter-agent communication
├── logs/           # Audit logs
├── config/         # Configuration files
├── prompts/        # Agent role prompts
├── artifacts/      # Releases, reports, backups
├── dashboard/      # Real-time monitoring dashboard
└── scripts/        # Helper scripts

Example PRDs

Test Loki Mode with these pre-built PRDs in the examples/ directory:

| PRD | Complexity | Est. Time | Description | |-----|------------|-----------|-------------| | simple-todo-app.md | Low | ~10 min | Basic todo app - tests core functionality | | api-only.md | Low | ~10 min | REST API only - tests backend agents | | static-landing-page.md | Low | ~5 min | HTML/CSS only - tests frontend/marketing | | full-stack-demo.md | Medium | ~30-60 min | Complete bookmark manager - full test |

# Example: Run with simple todo app
./autonomy/run.sh examples/simple-todo-app.md

Configuration

Autonomy Settings

Customize the autonomous runner with environment variables:

LOKI_MAX_RETRIES=100 \
LOKI_BASE_WAIT=120 \
LOKI_MAX_WAIT=7200 \
./autonomy/run.sh ./docs/requirements.md

| Variable | Default | Description | |----------|---------|-------------| | LOKI_PROVIDER | claude | AI provider: claude, codex, gemini | | LOKI_MAX_RETRIES | 50 | Maximum retry attempts before giving up | | LOKI_BASE_WAIT | 60 | Base wait time in seconds | | LOKI_MAX_WAIT | 3600 | Maximum wait time (1 hour) | | LOKI_SKIP_PREREQS | false | Skip prerequisite checks |

Circuit Breakers

# .loki/config/circuit-breakers.yaml
defaults:
  failureThreshold: 5
  cooldownSeconds: 300

External Alerting

# .loki/config/alerting.yaml
channels:
  slack:
    webhook_url: "${SLACK_WEBHOOK_URL}"
    severity: [critical, high]
  pagerduty:
    integration_key: "${PAGERDUTY_KEY}"
    severity: [critical]

Requirements

  • Claude Code with --dangerously-skip-permissions flag
  • Internet access for competitive research and deployment
  • Cloud provider credentials (for deployment phase)
  • Python 3 (for test suite)

Optional but recommended:

  • Git (for version control and checkpoints)
  • Node.js/npm (for dashboard and web projects)
  • Docker (for containerized deployments)

Integrations

Vibe Kanban (Visual Dashboard)

Integrate with Vibe Kanban for a visual kanban board:

# 1. Start Vibe Kanban (terminal 1)
npx vibe-kanban

# 2. Run Loki Mode (terminal 2)
./autonomy/run.sh ./prd.md

# 3. Export tasks to see them in Vibe Kanban (terminal 3)
./scripts/export-to-vibe-kanban.sh

# 4. Optional: Auto-sync for real-time updates
./scripts/vibe-sync-watcher.sh

Important: Vibe Kanban integration requires manual export. Tasks don't automatically appear - you must run the export script to sync.

Benefits:

  • Visual progress tracking of all active agents
  • Manual intervention/prioritization when needed
  • Code review with visual diffs
  • Multi-project dashboard

See integrations/vibe-kanban.md for complete step-by-step setup guide and troubleshooting.


Testing

Run the comprehensive test suite:

# Run all tests
./tests/run-all-tests.sh

# Or run individual test suites
./tests/test-bootstrap.sh        # Directory structure, state init
./tests/test-task-queue.sh       # Queue operations, priorities
./tests/test-circuit-breaker.sh  # Failure handling, recovery
./tests/test-agent-timeout.sh    # Timeout, stuck process handling
./tests/test-state-recovery.sh   # Checkpoints, recovery

Contributing

Contributions welcome! Please:

  1. Read SKILL.md to understand the core architecture
  2. Review skills/00-index.md for module organization (v3.0+)
  3. Check references/agents.md for agent definitions
  4. Open an issue for bugs or feature requests
  5. Submit PRs with clear descriptions and tests

License

MIT License - see LICENSE for details.


Acknowledgments

Loki Mode incorporates research and patterns from leading AI labs and practitioners:

Research Foundation

| Source | Key Contribution | |--------|------------------| | Anthropic: Building Effective Agents | Evaluator-optimizer pattern, parallelization | | Anthropic: Constitutional AI | Self-critique against principles | | DeepMind: Scalable Oversight via Debate | Debate-based verification | | DeepMind: SIMA 2 | Self-improvement loop | | OpenAI: Agents SDK | Guardrails, tripwires, tracing | | NVIDIA ToolOrchestra | Efficiency metrics, reward signals | | CONSENSAGENT (ACL 2025) | Anti-sycophancy, blind review | | GoalAct | Hierarchical planning |

Practitioner Insights

  • Boris Cherny (Claude Code creator) - Self-verification loop, extended thinking
  • Simon Willison - Sub-agents for context isolation, skills system
  • Hacker News Community - Production patterns from real deployments

Inspirations

Full Acknowledgements - Complete list of 50+ research papers, articles, and resources

Built for the Claude Code ecosystem, powered by Anthropic's Claude models (Sonnet, Haiku, Opus).


Ready to build a startup while you sleep?

git clone https://github.com/asklokesh/loki-mode.git ~/.claude/skills/loki-mode
./autonomy/run.sh your-prd.md

Keywords: claude-code, claude-skills, ai-agents, autonomous-development, multi-agent-system, sdlc-automation, startup-automation, devops, mlops, deployment-automation, self-healing, perpetual-improvement