Human-centered systems. Powered by AI.
3MC Automation is a product systems and operations studio focused on governed AI workflows, practical automation, knowledge infrastructure, and implementation-ready decision systems.
We design public frameworks and anonymized case studies that show how ambiguous work can become structured, reviewable, and ready for accountable execution. AI accelerates the work. Human judgment, approval, and ownership remain the control layer.
- AI-assisted product and operating systems
- Product discovery, prioritization, and delivery workflows
- Human-in-the-loop governance and approval models
- Knowledge acquisition, provenance, and canonical data systems
- Requirements, acceptance criteria, and Engineering-ready artifacts
- Workflow automation for intake, triage, reporting, and decision support
- Executive-ready Product and operations communication
| Framework | Purpose |
|---|---|
| AAPOS: AI-Assisted Product Operating System | A practical Product Ownership framework for moving from ambiguous business problems to governed Product recommendations, Engineering plans, and executive decision requests. |
| KAOS: Knowledge Acquisition Operating System | An AI-assisted knowledge engineering framework for transforming fragmented information into governed, structured knowledge with provenance and human approval. |
| Case Study | Demonstrates |
|---|---|
| Evidence-Based Program Discovery Workflow | Guided intake, requirements, MVP boundaries, acceptance criteria, governance, and recommendation planning. |
| Governed AI Operations Assistant | Executive workflow triage, prioritization, memory boundaries, human review, and administrative workload support. |
| Survey Insights Pipeline | Survey intake, CSV validation, participant-count safeguards, human review, and stakeholder-ready reporting. |
- AI accelerates. Humans decide.
- Discovery comes before commitment.
- Product Intent locks before Engineering planning.
- Uncertainty, dependencies, risk, and tradeoffs remain visible.
- Every approval states what it permits and what it does not permit.
- Automation should strengthen accountability, not hide it.
- The best systems are usable, auditable, and trusted by the people who depend on them.
Public repositories contain original frameworks, fictional examples, and safely anonymized case studies. They do not disclose client identities, confidential source material, private data, unsupported outcomes, or implementation claims that cannot be verified publicly.
