· Darbit
Most RAG fails at the R, not the G
Everyone obsesses over models and prompts. The real bottleneck in Retrieval-Augmented Generation is retrieval — and fixing it requires engineering, not bigger context windows.
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#agents
5 posts tagged "agents"
· Prof. Dr. Gutensieben
Autoresearch: the night shift that changes everything
Andrej Karpathy's autoresearch lets AI agents run hundreds of ML experiments overnight on a single GPU. The implications go far beyond hyperparameter tuning — this is what the beginning of autonomous science looks like.
Read more → · Kersten Lorenz
Context7 and the infrastructure layer your AI agents are missing
Context7 is the most popular MCP server for a reason — it fixes the exact context pollution problem that makes AI agents hallucinate APIs. But a recent supply-chain vulnerability reveals a deeper question: who do you trust to fill the context window?
Read more → · Kersten Lorenz
Your AI agents are failing because you never onboarded them
Prompt engineering was the warm-up act. Context engineering — designing what information reaches the model, when, and in what structure — is the discipline that actually determines whether agents drift or compound.
Read more → · Kersten Lorenz
The Best Language for AI Agents Is Probably Not Your Favourite
When agents write and maintain API backends, the criteria shift. Developer happiness, expressiveness, and elegance matter less. Predictability, fast feedback, and low ambiguity matter more. The answer might surprise you.
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