Whileone Tech Space

If you've ever pasted a chunk of code into a public AI chatbot to fix an error, you know how useful it is. But have you ever stopped to think about where that code actually goes? That was one of the questions the team at Whileone kept coming back to. The honest answer is: to a server somewhere, owned by someone else. For a cookie recipe that's fine. For the code we write for clients, the team felt it wasn't good enough. So, we decided to run its own AI model, on its own hardw

Every silicon vendor at every keynote this year has said some version of the same sentence: the next CPU generation will be built for agentic workloads. Intel talked about CPUs as the orchestration layer for agentic systems, Arm argued that agents are driving a fresh wave of data centre CPU demand, and NVIDIA introduced Vera as a CPU designed for agentic workflows rather than general-purpose compute. The direction is settled. The definition is not. Because here is the questio

For decades, AI benchmarks lived in comfortable isolation. A model answered a question, we checked the answer, we assigned a score. Agentic AI broke that contract. When a model can browse the web, write and execute code, call external APIs, and chain its own decisions across hundreds of steps, a single accuracy number tells you almost nothing about whether the system is actually trustworthy. Evaluating an agent is less like grading an exam and more like auditing a junior empl