AI stuff
Prompt engineering lifecycle
Prompt engineering is the art and science of crafting effective instructions for large language models like Claude to produce desired outputs. At its core, prompt engineering involves designing, refining, and optimizing the text inputs (prompts) given to models to elicit accurate, relevant, and useful responses. It's about "communicating" with Clau
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Throughout this post, I’ve shared patterns I’ve observed across dozens of AI implementations. The most successful teams aren’t the ones with the most sophisticated tools or the most advanced models – they’re the ones that master the fundamentals of measurement, iteration, and learning.
The core principles are surprisingly simple:
The core principles are surprisingly simple:
- Look at your data.
Hamel Husain • A Field Guide to Rapidly Improving AI Products – Hamel’s Blog
Scaling Without Losing Trust
As your AI system grows, you’ll inevitably face pressure to reduce the human effort involved in evaluation. This is where many teams go wrong – they automate too much, too quickly, and lose the human connection that keeps their evaluations grounded.
The most successful teams take a more measured approach:
As your AI system grows, you’ll inevitably face pressure to reduce the human effort involved in evaluation. This is where many teams go wrong – they automate too much, too quickly, and lose the human connection that keeps their evaluations grounded.
The most successful teams take a more measured approach:
- Start with high
Hamel Husain • A Field Guide to Rapidly Improving AI Products – Hamel’s Blog
Monitor, protect, and control your AI agents.
Lakera: The World’s Most Advanced AI Security Platform
Credal | The Secure AI Agent Platform
credal.ai
Datasette
datasette.io
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h1xbpbfsf0w.typeform.comguarantees valid .json outpts - dottxt product
Structured data extraction from unstructured content using LLM schemas
Simon Willisonsimonwillison.net