Field guideJune 2026· 40 pages
Information Science for the AI Era
A self-study field guide to software architecture, data and AI systems — for a product leader building in technology and banking. Written for a 10-hour flight.
Pier Stein
Product · Growth · Investment Products · AI
A primer I wrote to go from comfortable with apps, APIs and databases to genuinely fluent in how modern systems, data and AI fit together — pitched at a curious product leader, with a banking lens throughout. Every idea comes with a plain-language analogy, a why-it-matters, and a PM move you can use on Monday. Four parts, fourteen chapters, a capstone and a glossary. Read it cover to cover on a long flight, or jump straight to any chapter.
Download the PDFChapters
- 01Thinking in systems: the journey of a single tap
- 02Backend engineering, demystified
- 03Software architecture: the shape of a system
- 04How systems talk — and stay correct
- 05Data foundations: where truth is stored
- 06Data in motion: pipelines, streaming & the single source of truth
- 07Machine learning, just enough
- 08Inside a large language model
- 09Building with LLMs
- 10Agents and teams of agents
- 11The delivery lifecycle: from idea to production
- 12Security, privacy, reliability & risk
- 13System design in practice
- 14The PM as technical leader