Products

Independent products, built to help someone decide better.

I pick a meaningful workflow, define the right product surface, build a useful system, and then measure whether it helps someone make a better decision or produce a better outcome.

The Monetization Stack

Live

A visual diagnostic for sports publisher revenue

The problem: Sports publishers earn from many lines at once, and when revenue softens it's hard to tell which layer broke.
What it is: Every place a sports publisher makes money, what has to be true underneath for each line to earn, and the questions nobody has answered yet.
Why it matters: It maps 22 recurring failures to the layer where the fix belongs, so the conversation starts with the mechanism instead of the symptom.
What it shows: How I diagnose a revenue system before proposing a product.

Open the Monetization Stack →

Leak Agent

v1 · Live runs pending

A revenue-leak diagnostic for sports publishers

The problem: Sports publishers lose revenue in the same eight places, and it's hard to see from the inside.
The workflow: Reads a publisher's own site the way a buyer would and scores eight leaks, with the evidence attached to every finding.
Why it matters: It turns "revenue feels soft" into a ranked list of what to fix first.
What makes it reliable: Evidence on every claim, failures reported instead of guessed, and a human review before any report goes out.
What it shows: Build the benchmark as well as the scan. A record of how publishers actually monetize is the asset that compounds.
Status: Eight checks defined, six automated, 27 fixture tests passing. First live runs against real publishers are pending.

See the Leak Agent →

Grounded sports-data assistant

Prototype

Source-aware answers for fans and newsrooms

The problem: In sports media, a wrong score or injury status costs trust faster than a slow answer.
The workflow: Answers questions only from live data, shows every source, and declines betting picks and anything the data can't support.
Why it matters: Answer surfaces can keep fans on the page. Ungrounded ones create liability.
What makes it reliable: A four-part evaluation of accuracy, grounding, honesty and refusal, run against a 30-question golden set.
What it shows: Define quality before building, and check the measurement as hard as the model.
Status: Prototype. The public demo is retired; the design and the evaluation are documented.

Read the product note →

The kit behind them

The method and build logPublished thresholds and data sources, with every correction kept on the record.

The working libraryPrompts, playbooks and connectors reused across the work.

Selected workWhere the same judgment shipped inside PFF, Disney, Fox Sports and USA Today.

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Channing & Co

Product and revenue systems for sports, entertainment, and live experiences.