AI Product OS
Ship products faster with specialized AI agents that simulate a full product team. A 12-step pipeline with quality gates takes you from raw idea to deployed, instrumented product.
12-Step Pipeline with Quality Gates
Every stage has a clear owner. Quality gates prevent skipping ahead. No shortcuts, no regressions.
/create-issueResearch AgentConvert idea into structured opportunity
/exploreResearch AgentValidate problem and market feasibility
/create-planProduct + Design + ArchitectureGenerate specs, UX, architecture, schema
/execute-planFrontend + Backend EngineersImplement frontend and backend
/deslopDeslop AgentClean and polish AI-generated code
/reviewCode Review AgentBaseline implementation review
/peer-reviewPeer Review AgentAdversarial architecture review
/qa-testQA AgentReliability and integration testing
/metric-planAnalytics AgentDefine tracking and success criteria
/deploy-checkDeploy AgentProduction readiness verification
/postmortemLearning AgentAnalyze bottlenecks and failures
/learningLearning AgentExtract insights into durable knowledge
12 Specialized AI Agents
Each agent has one responsibility. No scope creep, no overlap. They read from a shared knowledge base that grows with every project cycle.
Research Agent
Validates ideas, explores problems, assesses market feasibility
Product Agent
Writes product specs with acceptance criteria and success metrics
Design Agent
Defines UX flows, wireframes, and interaction patterns
Backend Architect Agent
Designs system architecture, API contracts, and database schemas
Frontend Engineer Agent
Implements UI components, pages, and client-side logic
Backend Engineer Agent
Implements API routes, database queries, and integrations
Code Review Agent
Checks for violations against coding standards and anti-patterns
Peer Review Agent
Adversarial architecture review focused on security and scalability
QA Agent
Tests reliability: happy paths, edge cases, network failures, races
Analytics Agent
Defines PostHog events, funnels, and success metrics
Deploy Agent
Verifies production readiness: env vars, schemas, build, domains
Learning Agent
Extracts postmortem insights into durable knowledge base rules
5 Products Built Through This Pipeline
Each product went through the full 12-step cycle. Every postmortem generated rules that made the next product better.
Clarity
ShippedAI-powered PM task engine. Type a messy thought, get it categorized into a structured Kanban board in under 3 seconds.
Finance Advisor
ShippedWhatsApp-based proactive nudge system for young earners. Daily spending reminders and weekly report cards to combat lifestyle inflation.
SMB Bundler
ShippedFeature bundle and value-based pricing engine for B2B SaaS. Select features, get AI-generated INR pricing and email pitch in 5 seconds.
Ozi Reorder
ShippedExperiment instrumentation for baby essentials dark-store. Tests whether consumption-cycle-aware reorder reminders lift repeat purchases.
Ozi Insights
ExploredCustomer insight workspace analyzing synthetic support tickets grounded in real Play Store reviews to surface pain points.
How It Works
Three phases. One feedback loop. The system gets smarter with every project cycle.
Define
Start with a raw idea. The Research Agent validates the problem, explores market feasibility, and converts it into a structured opportunity with clear hypotheses.
/create-issue + /exploreBuild with Gates
Sequential commands activate specialized agents. Quality gates between stages prevent skipping ahead. Code review, peer review, and QA must all pass before deployment.
/create-plan through /deploy-checkLearn Systematically
Every cycle ends with a postmortem that extracts engineering and product lessons into a knowledge base. Every future agent reads these rules before executing.
/postmortem + /learningThe knowledge base is the differentiator. Past mistakes become future prevention rules. Every agent re-reads accumulated lessons before executing, so the same error never appears twice.