From conversation to reviewed work.

Clarify the work. Distribute it deliberately. Inspect the output. Fold the learning into the next run.

Hands-on product design, design engineering, and operating systems that turn conversations into reviewable work.

Meeting: Start with the evidence, not a cleaned-up story.

Recordings, notes, and observations enter together. Contradictions stay visible instead of being edited away too early.

I decide which sources are authoritative and which conflicts require human review.

Brief: Turn the conversation into questions we can answer.

The messy material becomes a brief with clear questions, boundaries, and a definition of done.

I define what can be automated, what needs verification, and what only a person should decide.

Skills: Give each phase a reliable playbook.

Reusable instructions carry the standards for research, design, quality checks, and review.

I select the smallest useful set of skills and keep their responsibilities from overlapping.

Orchestration: Keep one lead workstream. Give specialists clear lanes.

The main task keeps the whole problem in view while specialist workstreams investigate and verify bounded pieces.

I set agent boundaries, sequence the work, and decide when parallelism creates value instead of noise.

Review: Make disagreement easy to see and resolve.

A review page puts the evidence beside each finding so a person can agree, reject, or reclassify it.

I design the review threshold and keep human judgment visible at the point of uncertainty.

Learning: Teach the correction back to the system.

Every correction improves the rules for the next run, so the team does not solve the same problem from scratch.

I decide which feedback is a one-off fix and which should change the shared workflow.

Measure: Turn validated findings into work the team can use.

Reviewed opportunities are deduplicated, broken into useful pieces, and compared with work already planned.

I choose the useful level of decomposition and connect effort to expected product and business value.

What the loop changed

My own sprint throughput went from a median of ~45 to ~105 median points per sprint after moving to an AI-assisted workflow.