AI agents' biggest problem is not intelligence. It is memory.
The practical bottleneck for AI agents is no longer just intelligence. It is a fast, reliable and user-editable memory layer.
AI's biggest risk is not hallucinations. It is bad management.
AI's biggest risk is not only hallucination, but using it like an answer machine instead of managing the work it does.
AI is moving onto your own computer
Local AI brings large models closer to a company's own data, costs and everyday workflows.
I tendered insurance from five companies and did not open a single offer myself
A practical example of how an AI agent turned five insurance offers and policy terms into one clear comparison.
We let an AI agent prepare a company tax return
What happens when an AI agent is taken into a real authority form, accounting figures and multi-step back-office work.
Model comparisons are an easy story. In agent work, workflow decides.
Why companies should look past model hype and build agents around clear workflows, sources, limits and outputs.
AI stopped being a search engine. Most people did not notice.
AI agents are no longer just answer machines. A well-scoped agent performs tasks, follows changes and removes repeated friction.
Agents turn multi-step research into a five-minute workflow
A practical example of how an AI agent turns slow tax and data work into a fast, reviewable workflow.
AI agents are not demos for us. They are part of daily work.
Practical lessons from AI Generation on OpenClaw and Hermes agents, model layers, tools and reliability.