Insights from the hive
Your AI pilot worked. Here’s why production won’t.
The position, stated up front Production has no such person. What looked like a high success rate on curated cases becomes an unknown success rate on everything, and…
RAG or fine-tuning? A decision guide that isn’t vendor marketing
The position, stated up front The default order is retrieval first, then prompt work, then fine-tuning for form and unit cost once you have an eval set. Most…
Self-healing systems: agents that fix themselves
The position, stated up front Everything below is organized around that claim. Self healing systems AI: the loop, in five parts Most products stop at three. The last…
What AI agents actually cost (per task, not per seat)
The position, stated up front We quote no provider prices anywhere in this article. Prices change quarterly and a number written today would be wrong by the time…
How to choose the first process to hand to an agent
The position, stated up front Value matters. It is the second question, and every scoring method that puts it first produces the same expensive result. Which processes to…
Multi-agent orchestration, explained with a beehive
The position, stated up front The corollary matters just as much. The orchestrator’s job is bookkeeping, not intelligence. Most of the value in a working hive comes from…
AI agents vs RPA: when rules stop being enough
The position, stated up front That point is measurable, it arrives earlier than most teams expect, and it has nothing to do with how clever the model is.…
What is an AI agent? (And why it isn’t a chatbot)
What is an AI agent, stripped to one sentence Most definitions of an agent list capabilities. Reasoning, planning, tool use, memory. Those are components, and a system can…
START SMALL, SCALE THE HIVE
One process. One agent. Thirty days.
Tell us the task that eats your team’s week. We’ll tell you - honestly - whether an agent should do it, what it would cost, and what you’d get back. No slide deck required.