Blog.

When does a multi-agent AI system beat a single agent, and when is it 15 times the bill for the same result? Findings from Anthropic, Cognition and the MAST study, a real scenario, and six questions for any proposal.

Embeddings represent the meaning of text as numbers. Model choice, the dimensions decision, non-English performance and the real cost of a 10,000-page archive, explained for whoever approves the purchase.

A vector database moves search from matching words to matching meaning. But most teams do not need a separate one. Here is where the threshold actually sits, and what it costs.

MCP became the common language for connecting AI to company systems. Here is what that connection actually costs, where it breaks, and what it means for your data.

Open-weight models have almost caught up with the closed ones, so running your own must be the obvious move by now. It sounds so reasonable that few people check it. What happens when you actually run the numbers?They come out badly for most companies. Against frontier APIs, self-hosting starts w...

Models invent answers because guessing is rewarded, not because they are broken. What that has cost real companies, and the layers production systems use to contain it.

Fine-tuning changes how a model behaves; RAG changes what it knows. Which problem needs which method, what each one costs, and which survives a deletion request? A three-question decision tree.

Beyond the AI agent definitions: a real invoice-processing setup, honest cost ranges, the tools people actually use, and why most agent projects fail.

RAG explained in plain business language: what it is, a realistic cost range for setup and running it, and a sample four-week plan to get a working pilot live.

Building AI infrastructure for your company means stacking four separate management decisions on top of each other: are you building a system that talks to your data, an autonomous agent that carries out tasks, a way to connect your existing systems together, or a decision about running models on...