Skip to content Building Research Agents for Tech Insights
ChatGPT something like: “Please scout all of tech for me and summarize trends and patterns based on what you think ...
Read more Extracting Structured Data with LangExtract: A Deep Dive into LLM-Orchestrated Workflows
Having developed raw LLM workflows for structured extraction tasks, I have observed several pitfalls in them over time. In one ...
Read more Tool Masking: The Layer MCP Forgot
By Frank Wittkampf & Lucas Vieira MCP and similar services were a breakthrough in AI connectivity¹: a big leap forward ...
Read more Why Your Prompts Don’t Belong in Git
post after a while, and I want to start with something that bit me early on. When I was building ...
Read more How Your Prompts Lead AI Astray
been working on improving my prompting skills, and this is one of the most important lessons I’ve learnt so far: ...
Read more Declarative and Imperative Prompt Engineering for Generative AI
refers to the careful design and optimization of inputs (e.g., queries or instructions) for guiding the behavior and responses of ...
Read more How To Significantly Enhance LLMs by Leveraging Context Engineering
is the science of providing LLMs with the correct context to maximize performance. When you work with LLMs, you typically ...
Read more Mastering Prompt Engineering with Functional Testing: A Systematic Guide to Reliable LLM Outputs
Creating efficient prompts for large language models often starts as a simple task… but it doesn’t always stay that way. ...
Read more Tutorial: Semantic Clustering of User Messages with LLM Prompts
As a Developer Advocate, it’s challenging to keep up with user forum messages and understand the big picture of what ...
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