Prompt Engineering

Prompt engineering covers the craft of getting useful, reliable output from large language models. This section collects tested prompt patterns, structured guides for tools like ChatGPT, Claude, and Gemini, and analysis of why certain phrasings and structures outperform others. The aim is practical leverage you can apply the same day, written for people who use these models as part of real work.

How to Build Multi-Agent Systems with Claude Opus 4.7 & Gemini Flash 3.5 (2026).

How to Build Multi-Agent Systems with Claude Opus 4.7 & Gemini Flash 3.5 (2026)

You are building a research pipeline that needs to search the web, process a dozen PDFs, extract structured data from tables, and produce a cited written report. You set it up as a single Claude Opus 4.7 agent. The quality…

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Claude vs ChatGPT 5: Which AI Wins for Agent Building? (2026).

Claude vs ChatGPT 5: Which AI Wins for Agent Building? (2026)

Your team has built on ChatGPT for two years. The new project is a customer facing agent with complex workflows, several tool integrations, and strict output constraints. Someone suggests evaluating Claude before you commit. Just before the architecture meeting, somebody…

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Claude Code for AI Engineering: Building and Testing ML Pipelines (2026 Guide).

Claude Code for AI Engineering: Building and Testing ML Pipelines (2026 Guide)

Building machine learning pipelines is one of those engineering domains that looks deceptively simple from the outside and is ruthlessly unforgiving in practice. Data arrives malformed. Feature engineering transforms compound invisibly. Training loops fail silently on edge cases. And the…

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