Skip to content Building Research Agents for Tech Insights
[ad_1] ChatGPT something like: “Please scout all of tech for me and summarize trends and patterns based on what you ...
Read more Extracting Structured Data with LangExtract: A Deep Dive into LLM-Orchestrated Workflows
[ad_1] Having developed raw LLM workflows for structured extraction tasks, I have observed several pitfalls in them over time. In ...
Read more Tool Masking: The Layer MCP Forgot
[ad_1] By Frank Wittkampf & Lucas Vieira MCP and similar services were a breakthrough in AI connectivity¹: a big leap ...
Read more Why Your Prompts Don’t Belong in Git
[ad_1] post after a while, and I want to start with something that bit me early on. When I was ...
Read more How Your Prompts Lead AI Astray
[ad_1] been working on improving my prompting skills, and this is one of the most important lessons I’ve learnt so ...
Read more Declarative and Imperative Prompt Engineering for Generative AI
[ad_1] refers to the careful design and optimization of inputs (e.g., queries or instructions) for guiding the behavior and responses ...
Read more How To Significantly Enhance LLMs by Leveraging Context Engineering
[ad_1] is the science of providing LLMs with the correct context to maximize performance. When you work with LLMs, you ...
Read more Mastering Prompt Engineering with Functional Testing: A Systematic Guide to Reliable LLM Outputs
[ad_1] Creating efficient prompts for large language models often starts as a simple task… but it doesn’t always stay that ...
Read more Tutorial: Semantic Clustering of User Messages with LLM Prompts
[ad_1] As a Developer Advocate, it’s challenging to keep up with user forum messages and understand the big picture of ...
Read more 
