An honest guide to choose between a closed model and an open-source one based on your use case, budget and data restrictions.
An honest guide to choose between a closed model and an open-source one based on your use case, budget and data restrictions.
The question is not “which model is best.” It’s “which model is best for this use case, with this data and this budget.”
When data cannot leave your infrastructure, when volume is massive, when you need to fine-tune with your domain.
When you need the immediate frontier, when you have no MLOps team, when the case is low-volume.
Lessons from the conversational agent we built on LangChain + Weaviate: chunking, verifiable citations, evaluations and the boring part nobody talks about.
Why writing specs before asking an agent for code totally changes the result — and how we're integrating it with MCP.
MCP sounds abstract until you plug it into your Jira, your repo and your documentation. Here are the three servers that save me the most time.