Insights

Ideas on fractional talent, data & AI

Short, opinionated notes from the engagements we run — on hiring senior people, staffing data programmes, and shipping AI that survives contact with production.

When a fractional CXO beats a full-time hire

Fractional works when the problem is bounded: a platform decision, a governance model, a turnaround, or the first 12 months of a function. It stops working when the role becomes day-to-day operational ownership. If you can describe the outcome in a sentence and the horizon in months, fractional is usually the cheaper and faster route.

How to staff a data modernization programme

Most programmes fail on roles, not tooling. You need a solution architect owning target state, a governance lead owning standards and stewardship, and a delivery lead owning the plan and the client conversation — before you scale up engineers. Hire the shape of the programme, not a headcount number.

What 'production-ready' means for an AI agent

A demo is a prompt and an API key. Production means retrieval you can evaluate, guardrails you can audit, cost you can forecast, and failure modes you can observe. Budget as much for evaluation and observability as for the agent logic itself.

Reading a consultant CV without being fooled

Ask what broke and what they did about it. Senior delivery people can describe a specific failure in detail; CV inflation cannot survive a follow-up question. Two structured rounds — one technical deep-dive, one ways-of-working — filter better than five unstructured chats.

Want the longer version of any of these? Ask us directly.

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