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Generative AI Design Patterns: thirty-two names for things already being done

Valliappa Lakshmanan and Hannes Hapke · O'Reilly, 2025 (excerpt)
25 de febrero de 2026 por
Generative AI Design Patterns: thirty-two names for things already being done
Andrés Briñez

The preface states the problem that shows up in every project: the distance between the demo that impresses and the system that survives the following Monday. From there it distributes thirty-two patterns across chapters on output format control, bringing in your own knowledge, reasoning, reliability, agents, deployment and safety guardrails.

What I took from it

Having names for things. Once a practice is called model-as-judge, or reflection, or dependency injection adapted to this world, it stops being an improvisation and becomes a decision with known alternatives and an estimable cost. That can be discussed in a proposal; an improvisation cannot.

The separation between patterns that control the shape of an answer and patterns that bring in proprietary knowledge. They get confused constantly, and confusing them leads to solving a formatting problem with more documents, which is expensive and does not work.

And the cost framing: latency and spend have patterns of their own, such as the small language model or reusing repeated instructions. They are not a later adjustment. They are chosen at design time or they are not chosen at all, because changing them afterwards means rebuilding half of what is already there.

What I left out

The risk of the format. A numbered catalogue invites use as a checklist, and a pattern without the problem that justifies it is complexity for free, paid for by whoever maintains the thing afterwards. And an honest caveat covering this whole entry: about the chapters that were not in the excerpt I have no opinion, so I offer none.

# AI
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Jakub Langr and Vladimir Bok · Manning, 2019
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