Skill: miknasbh-stack/miknas-compoundos (version 1.0.0)

--- name: compoundos description: Design, implement, and operate a self-improving AI Operating System for business with 9 components: Strategic Layer, Prioritization Engine, Knowledge Management, Central Ops, Department Agents (ACRA), Projects, Auto-Capture, Communication Layer, and Metrics & Monitoring. Use when building AI-powered business operations systems, implementing agentic workflows, creating department-specific AI teams, establishing business intelligence systems, or setting up compounding intelligence architectures with learning loops. --- # CompoundOS - AI Operating System Implementation ## Core Concept CompoundOS is a self-improving AI Operating System that eliminates "context reset" - where scattered AI tools create disconnected data and lost context. The system compounds intelligence daily through a learning loop. **Key benefits:** - Self-improving: Every task makes the system smarter - Anything Tool: AI builds tools/workflows instead of buying SaaS - Frictionless: Eliminates bottlenecks, enables systematic high-leverage work ## Quick Start: 3-Step Implementation ### Step 1: Define Strategic Layer (Component 1) Create master document with these elements: **Required fields:** - **Big Obsessional Goal (BOG):** Your single, driving ambition - **Current Bottleneck:** The #1 thing blocking progress - **Target Audience:** Who you serve and their pains - **Positioning:** How you're uniquely positioned to win See [assets/strategy-template.md](assets/strategy-template.md) for template. ### Step 2: Create Agent with Strategy Feed strategic document into AI agent's permanent instructions. This ensures: - Every decision is filtered through the strategy - Agent can push back on misaligned requests - Context is maintained across sessions ### Step 3: Enforce Filter Always prompt AI as "Chief of Staff": 1. Review strategic document before executing 2. Score tasks against business objectives 3. Surface ONE needle-moving action daily ## Implementation Workflow ### Phase 1: Foundation (Components 1-3) 1. **Strategic Layer** - Define core (see above) 2. **Prioritization Engine** - Set up daily review cadence - Review backlog against strategy - Score tasks on strategic alignment - Output: ONE action to execute today 3. **Knowledge Management** - Set up memory system - Capture insights, decisions, outcomes - Auto-categorize by department/project - Enable retrieval before new tasks See [references/knowledge-setup.md](references/knowledge-setup.md) for detailed implementation. ### Phase 2: Execution Layer (Components 4-6) 4. **Central Ops** - Build workflow automation - Document SOPs for repeatable processes - Create automated task pipelines - Establish reproducible processes 5. **Department Agents** - Deploy ACRA agents - See [references/department-agents.md](references/department-agents.md) for agent templates - Each agent holds only department-relevant context - Specialized capabilities per department 6. **Projects** - Set up cross-functional orchestration - Shared context when goals span departments - Example: Product launch = Attract + Deliver collaboration ### Phase 3: Learning Layer (Components 7-9) 7. **Auto-Capture** - Enable self-improvement - Log all decisions, actions, outcomes - Feed data into knowledge system - See [references/learning-loop.md](references/learning-loop.md) 8. **Communication Layer** - Set up data gateways - Human-to-Machine: Voice, text, structured input - Machine-to-Machine: APIs, CRMs, webhooks 9. **Metrics & Monitoring** - Establish operating rhythm - See [references/metrics-cadence.md](references/metrics-cadence.md) - 5 cadences: Daily, Weekly, Monthly, Quarterly, Annually - Performance signals feed back to Strategic Layer ## ACRA Framework Quick Reference Department agents follow ACRA structure: | Department | Acronym | Focus | Example Capabilities | |------------|---------|-------|---------------------| | **A**ttract | A | Traffic & Content | YouTube pipeline, ad creation, SEO | | **C**onvert | C | Sales & Copywriting | Funnel optimization, outreach | | **R**etain | R | Customer Success | Onboarding, LTV, support | | **A**scend | A | Product Delivery | Feature delivery, upsells | **Support functions:** Finance, HR, Legal (as needed) See [references/department-prompts.md](references/department-prompts.md) for agent prompt templates. ## The Compounding Cycle ``` Strategic Layer → Prioritization → Execution (Ops/Departments/Projects) ↓ Auto-Capture ↓ ┌────────────────────┴────────────────────┐ ↓ ↓ Knowledge Management Metrics System ↓ ↓ └───────────────→ Learning Loop ←────────┘ ↓ Updates & Refines Strategy ``` **Result:** Your AI wakes up smarter each day. ## Component Interdependencies - **Strategic Layer** → Guides Prioritization Engine (Component 2) - **Auto-Capture** → Feeds Knowledge Management (Component 3) - **Department Agents** → Use Central Ops for workflows (Components 4-5) - **Metrics System** → Sends signals to Strategic Layer (Components 1-9) - **Communication Layer** → Connects all components (Component 8) ## Common Patterns ### Daily Operations Pattern 1. **Morning:** Prioritization Engine surfaces ONE needle-moving action 2. **Mid-day:** Department agents execute specialized work 3. **Evening:** Auto-Capture logs outcomes, Metrics reviews performance 4. **Night:** Learning Loop updates knowledge, refines strategy ### New Task Pattern 1. **Input:** Request enters via Communication Layer 2. **Filter:** Prioritization Engine scores against strategy 3. **Route:** Task assigned to appropriate department agent 4. **Execute:** Agent completes work with Central Ops support 5. **Capture:** Auto-Capture logs entire process and outcome 6. **Learn:** Knowledge Management extracts insights ### Project Launch Pattern 1. **Define:** Project scope shared across relevant departments 2. **Coordinate:** Cross-functional agents establish shared context 3. **Execute:** Each department contributes specialized work 4. **Monitor:** Metrics System tracks project KPIs 5. **Review:** Post-mortem captured, lessons learned ## Troubleshooting ### Context Disconnect **Symptom:** AI forgets previous decisions or context **Solution:** - Ensure Auto-Capture is logging everything - Check Knowledge Management retrieval is working - Verify Strategic Layer is being applied as filter ### Analysis Paralysis **Symptom:** Too many priorities, can't decide what to do **Solution:** - Strengthen Prioritization Engine scoring - Limit to ONE needle-moving action per day - Revisit Strategic Layer for clarity ### Department Silos **Symptom:** Teams not sharing context, duplicated work **Solution:** - Use Projects for cross-functional goals - Ensure shared context is orchestrated - Check Communication Layer integrations ### No Learning Occurring **Symptom:** System not getting smarter over time **Solution:** - Verify Auto-Capture is active - Check Knowledge Management is extracting insights - Ensure Metrics feedback loop is reaching Strategic Layer ## Best Practices 1. **Start small:** Implement Components 1-3 first, then expand 2. **Define before build:** Strategic Layer must be solid first 3. **Capture everything:** Auto-Capture is non-negotiable 4. **One action per day:** Prioritization Engine enforces focus 5. **Review regularly:** Metrics cadence must be maintained 6. **Iterate strategy:** Learning Loop must update Strategic Layer ## Reference Materials | Topic | Reference | |-------|-----------| | Knowledge Management Setup | [references/knowledge-setup.md](references/knowledge-setup.md) | | Department Agent Templates | [references/department-agents.md](references/department-agents.md) | | Metrics & Operating Cadence | [references/metrics-cadence.md](references/metrics-cadence.md) | | Learning Loop & Auto-Capture | [references/learning-loop.md](references/learning-loop.md) | | Strategic Layer Template | [assets/strategy-template.md](assets/strategy-template.md) | | Department Prompt Templates | [assets/department-prompts.md](assets/department-prompts.md) | ## When to Use This Skill Use CompoundOS when: - Building AI-powered business operations systems - Implementing agentic workflows with departmental specialization - Creating self-improving business intelligence systems - Eliminating context reset across multiple AI tools - Establishing compounding intelligence architectures - Setting up automated task prioritization and execution - Designing cross-functional AI agent teams --- *CompoundOS: Your business intelligence compounds daily.*


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