#prompt-engineering

A same-day LLM eval harness needs 20-50 real tasks, automated grading, and a baseline model to diff against — not hundreds of labels. Qualify a new model fast.

Ten one-shot audit and upgrade jobs for Claude Fable 5, each drawn from Anthropic's own prompting guide, with the cheaper model that should execute the plan.

Anthropic's 400K-session study: non-coders succeed at nearly the rate of engineers. Domain expertise, not coding skill, drives the gap — here is the playbook.

Prompt-library metrics — catalog coverage, eval coverage, regression rate, model-fit divergence. The 10-KPI panel for production prompt ops.

Ten prompt engineering anti-patterns that quietly destroy production quality — few-shot pollution, instruction-stacking, format-via-example, more.

Fifty prompt patterns by task type — extraction, transformation, classification, reasoning, agent loops. With model-specific notes and reusable templates.

Make introduces AI Scenarios with built-in prompt engineering interfaces for marketing automation. Setup guide for creating intelligent workflow automations.

Master prompt engineering for marketing copy with 20 tested templates. Ad headlines, email sequences, landing pages, social posts, and brand voice calibration.

ETH Zurich study finds AGENTS.md and similar convention files increase AI agent inference costs by up to 159% with minimal accuracy gains. Alternatives.

Master advanced prompt engineering: chain-of-thought, few-shot learning, system prompts, and agentic patterns for GPT-5, Claude, and Gemini.