Patterns of an AI lineup card
summary
Argues that an AI portfolio needs a measurable playbook: use lineup cards to rank and sequence ranked opportunities, keep hot spares for pivots, and use scoring cards that record per-project metrics across “innings” (MVP, pilot, public/private beta, GA) so you can compare resource spend (salaries, cloud costs, tooling) to outcomes like win percentage or revenue lift. Recommends cross‑functional squads, continuous discovery, and avoiding one‑trick tooling or cowboy experiments.
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chapters (25)
- 0:00Intro
- 0:41About me
- 1:11The real reality
- 1:40Game value
- 1:58Quantitative tools
- 2:12Qualitative tools
- 2:41Transformation
- 3:12Strategy
- 7:01Analogy
- 8:17Multiobjective
- 9:08Baseline
- 10:56Incremental
- 11:39Vision
- 13:58Product Mentality
- 15:50Scale
- 16:32Sports analogy
- 17:40Takeaways
- 20:12Portfolio
- 20:28Sequencing
- 21:09Project Prioritization
- 22:03Analogies
- 23:46Quantitative
- 24:27Scorecards
- 25:34Closing thoughts
- 26:36Continuous measurement
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