Products
Great products deliver great outcomes.
Engineer paths that ensure others fall into a pit of success?
The Pipeline
Friction to deployed capability in five steps. Each step's output feeds the next.
| Step | Phase | Output |
|---|---|---|
| 1. Discover | Validate Demand | Scored demand signals |
| 2. Spec | Create PRD Stories | Feature/Function/Outcome table |
| 3. Rank | Prioritize PRDs | Sorted build order |
| 4. Prove | Commission PRDs | L0-L4 maturity evidence |
| 5. Build | Flow Engineering | Maps → types → tests → code |
Dig Deeper
🗃️ AI Products
4 items
🗃️ Product Design
10 items
🗃️ CLI Tools
2 items
📄️ MCP Tools
Decision checklist and adoption radar for MCP tool selection across agent teams
🗃️ Engineering
9 items
Virtuous Feedback Loop
The core Feedback Loop of interaction design is about outcomes meeting expectations.
- Take meaningful action with minimal friction
- Did outcomes match expectations?
- What next stay in the flow of progress?
Context
- Jobs To Be Done — The framework: discover demand before building
- Flow Engineering — Stories become maps become code
- Commissioning Dashboard — What's specified, built, proven
- Business Factory — The capability catalogue
Links
- Product Engineers on X
- Outcome Driven Development
- Product-Market fit
- Thoughtbot Playbook
- Felt Presence
Questions
At which step in the pipeline does signal from the original pain get lost — and how do you know?
- When a story (Feature/Function/Outcome) can't be commissioned, is the story wrong or the commissioning check?
- What's the cost of skipping demand validation and jumping straight to spec?
- Does the pipeline produce better products, or just more structured documentation?