Pydantic + OpenAI: The Cleanest Way to Get Structured Outputs from LLMs
Learn how to combine Pydantic models with OpenAI's API to reliably extract structured, validated data from LLM responses—eliminating parsi...
8 articles
Learn how to combine Pydantic models with OpenAI's API to reliably extract structured, validated data from LLM responses—eliminating parsi...
Lessons from developing Shippy, an AI agent for logistics, reveal that modular design, human-in-the-loop validation, and handling real-wor...
Dynamic subagents enhance AI agent systems by enabling real-time delegation of specialized tasks. This modular approach improves scalabili...
A team built a custom AI routing layer to reduce API costs, but it introduced latency, errors, and unpredictable behavior that degraded th...
Reliable AI agents often fail due to over-engineering the 'head' (reasoning). Tail control flips this: by constraining the agent's actions...
A hands-on guide to integrating large language models into products, covering architecture patterns, prompt engineering, cost optimization...
Learn to create a flexible agent harness that orchestrates AI models, tools, and memory. This guide covers architecture, implementation st...
A clear and practical article about artificial intelligence for a professional audience.