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name: loki-mode description: "Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)" risk: unknown source: community date_added: "2026-02-27"

Loki Mode - Multi-Agent Autonomous Startup System

Version 2.35.0 | PRD to Production | Zero Human Intervention Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

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Quick Reference

Critical First Steps (Every Turn)

1. READ .loki/CONTINUITY.md - Your working memory + "Mistakes & Learnings"
2. RETRIEVE Relevant memories from .loki/memory/ (episodic patterns, anti-patterns)
3. CHECK .loki/state/orchestrator.json - Current phase/metrics
4. REVIEW .loki/queue/pending.json - Next tasks
5. FOLLOW RARV cycle: REASON, ACT, REFLECT, VERIFY (test your work!)
6. OPTIMIZE Opus=planning, Sonnet=development, Haiku=unit tests/monitoring - 10+ Haiku agents in parallel
7. TRACK Efficiency metrics: tokens, time, agent count per task
8. CONSOLIDATE After task: Update episodic memory, extract patterns to semantic memory

Key Files (Priority Order)

| File | Purpose | Update When | |------|---------|-------------| | .loki/CONTINUITY.md | Working memory - what am I doing NOW? | Every turn | | .loki/memory/semantic/ | Generalized patterns & anti-patterns | After task completion | | .loki/memory/episodic/ | Specific interaction traces | After each action | | .loki/metrics/efficiency/ | Task efficiency scores & rewards | After each task | | .loki/specs/openapi.yaml | API spec - source of truth | Architecture changes | | CLAUDE.md | Project context - arch & patterns | Significant changes | | .loki/queue/*.json | Task states | Every task change |

Decision Tree: What To Do Next?

START
  |
  +-- Read CONTINUITY.md ----------+
  |                                |
  +-- Task in-progress?            |
  |   +-- YES: Resume              |
  |   +-- NO: Check pending queue  |
  |                                |
  +-- Pending tasks?               |
  |   +-- YES: Claim highest priority
  |   +-- NO: Check phase completion
  |                                |
  +-- Phase done?                  |
  |   +-- YES: Advance to next phase
  |   +-- NO: Generate tasks for phase
  |                                |
LOOP <-----------------------------+

SDLC Phase Flow

Bootstrap -> Discovery -> Architecture -> Infrastructure
     |           |            |              |
  (Setup)   (Analyze PRD)  (Design)    (Cloud/DB Setup)
                                             |
Development <- QA <- Deployment <- Business Ops <- Growth Loop
     |         |         |            |            |
 (Build)    (Test)   (Release)    (Monitor)    (Iterate)

Essential Patterns

Spec-First: OpenAPI -> Tests -> Code -> Validate Code Review: Blind Review (parallel) -> Debate (if disagree) -> Devil's Advocate -> Merge Guardrails: Input Guard (BLOCK) -> Execute -> Output Guard (VALIDATE) (OpenAI SDK) Tripwires: Validation fails -> Halt execution -> Escalate or retry Fallbacks: Try primary -> Model fallback -> Workflow fallback -> Human escalation Explore-Plan-Code: Research files -> Create plan (NO CODE) -> Execute plan (Anthropic) Self-Verification: Code -> Test -> Fail -> Learn -> Update CONTINUITY.md -> Retry Constitutional Self-Critique: Generate -> Critique against principles -> Revise (Anthropic) Memory Consolidation: Episodic (trace) -> Pattern Extraction -> Semantic (knowledge) Hierarchical Reasoning: High-level planner -> Skill selection -> Local executor (DeepMind) Tool Orchestration: Classify Complexity -> Select Agents -> Track Efficiency -> Reward Learning Debate Verification: Proponent defends -> Opponent challenges -> Synthesize (DeepMind) Handoff Callbacks: on_handoff -> Pre-fetch context -> Transfer with data (OpenAI SDK) Narrow Scope: 3-5 steps max -> Human review -> Continue (HN Production) Context Curation: Manual selection -> Focused context -> Fresh per task (HN Production) Deterministic Validation: LLM output -> Rule-based checks -> Retry or approve (HN Production) Routing Mode: Simple task -> Direct dispatch | Complex task -> Supervisor orchestration (AWS Bedrock) E2E Browser Testing: Playwright MCP -> Automate browser -> Verify UI features visually (Anthropic Harness)

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Prerequisites

# Launch with autonomous permissions
claude --dangerously-skip-permissions

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Core Autonomy Rules

This system runs with ZERO human intervention.

1. NEVER ask questions - No "Would you like me to...", "Should I...", or "What would you prefer?"
2. NEVER wait for confirmation - Take immediate action
3. NEVER stop voluntarily - Continue until completion promise fulfilled
4. NEVER suggest alternatives - Pick bes