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Design Patterns Are Not Prompt Decorations

TL;DR for operators A software team can tell an LLM to “use Singleton,” and the model may indeed wrap the code in something that looks satisfyingly architectural. Congratulations: the code has learned to wear a blazer. The useful question is whether that blazer still has pockets. In the paper examined here, Kjellberg, Fotrousi, and Staron test 13 LLMs on 164 Java HumanEval-X coding tasks, asking them to generate code that follows the Singleton design pattern while still passing task tests.1 They compare four strategies: direct instruction, binary automated feedback, predicate-specific automated feedback, and predicate-specific feedback with few-shot Singleton examples. ...

June 25, 2026 · 17 min · Zelina
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From Prompt Chains to Algebra: Why Agentics 2.0 Treats AI Workflows Like Math

Workflow diagrams lie. They make AI systems look orderly: one box extracts information, another box reasons, a third box writes a conclusion, and a final box sends the result somewhere official-looking. In production, of course, the boxes often exchange blobs of fragile text, half-structured JSON, hidden assumptions, and one optimistic prompt that begins with “You are an expert…” ...

March 5, 2026 · 15 min · Zelina
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Lost in the Repo: Why Bigger Context Windows Still Miss the Point

Context is comforting. A large context window gives managers, developers, and product demos the same pleasant illusion: if the model can see enough of the repository, it should stop missing important files. Put the whole codebase into the window. Add retrieval if necessary. Let the agent read, reason, edit, and move on. ...

February 24, 2026 · 15 min · Zelina