Approach
I take ambiguous product work through production.
Four stages keep decisions attached to the build.
Discover names the problem. Define cuts the scope. Deliver builds in the real repository. Deploy closes the loop with review, visual checks, and monitoring.
Machine
Maps the problem space fast: research, competitive scans, and structured audits with the numbers attached, still in time to sit with the real users.
Human
In the room with stakeholders and users. Names the actual problem before anyone starts designing a solution.
Algorithm
Make the requirements less dumb. Every requirement gets a name and gets questioned.
Machine
Turns the brief into specs, design-system contracts, and an executable plan, carrying forward what prior engagements already taught.
Human
Decides what not to build. Cuts the work that will not earn its place on the roadmap.
Algorithm
Delete the part or process. If nothing comes back, not enough was cut.
Machine
Builds, tests, and iterates through real repositories and review gates, around the clock, supervised.
Human
Holds the quality bar. Taste. The call that something is actually right, or not.
Algorithm
Simplify and optimize, then accelerate cycle time.
Machine
Ships behind CI, visual QA, and monitoring so releases stay regression-proof after merge.
Human
Owns the outcome. Reads the signal. Chooses the next move.
Algorithm
Automate, last.
By the numbers
Closed work compounds.
54 in Jan to 162 in Jun: 3.0× the starting month. Full months through July; Aug omitted as partial.
AI orchestration
Judgment picks the model. The system ships.
Primary workhorse
Mechanical lanes
Hard reasoning
Diffs land only when they clear review and CI. No vanity acceptance rate.
Model routing
Grok 4.5
Day-to-day build and rewrite
72%
Composer 2.5
Mechanical execution
11%
Opus / Fable
Hard judgment and plans
10%
Auto
Light passes
7%
Recent mix: Grok 4.5 carries day-to-day build. Composer executes the mechanical lane. Heavier models for plans and optical review.
Across the surface
669 closed outcomes across every surface that ships.
- Marketing & go-to-market326
- Design system257
- Product surfaces55
- AI tooling & ops28
- Enterprise3
One loop from brief to merge. GTM and design system carry the load; product and AI ops ship in parallel.
Shipping rhythm
Closed work lands through the day, not in a single sprint burst.
Commit rhythm from retained git. Peak hour shows when merges land. Peak 2p.
Commits by hour
Peak 2p
Decision sequence
Five gates keep speed from becoming wasted work.
Challenge the requirement. Cut what does not earn its place. Simplify the surviving path. Accelerate it. Automate only after the work is sound.
The order matters. Automating a bad requirement only makes the wrong work move faster.
Make the requirements less dumb.
Every requirement gets a name attached to it. Not a department, a person. Then it gets questioned, even when a smart person wrote it. Especially then.
Delete the part or process.
Take away more than feels comfortable. If you never have to add anything back, you did not cut enough.
Simplify and optimize.
Only now. The most common mistake is optimizing something that should not exist.
Accelerate.
Now go fast. Not before. If you are digging your grave, do not dig faster.
Automate. Last.
Automating a broken process just makes it fail faster.
The result is a smaller, clearer build with one owner from decision through release.
Bring me the product problem nobody owns.
I will identify the smallest valuable release and tell you what should ship first.