No generic transformation commentary. The focus is on decisions that affect delivery quality, staffing speed, commercial risk and the Microsoft talent market.
Nearshore is not automatically cheaper once you include quality, management and transaction costs. The economics work when the talent is client-ready and the spread remains healthy for every party.
Read summary →Years of experience are a weak proxy. Better signals include end-to-end ownership, workshop capability, architectural judgement and the ability to explain trade-offs clearly.
Read summary →Agent requirements can range from business-led low-code scenarios to fully managed enterprise agent runtimes. The staffing requirement should match the implementation model.
Read summary →A low day rate is not an advantage if the client needs extra management or rework. A sustainable model needs three things at once: a rate the UK client sees as compelling, a contractor rate that attracts genuinely senior talent, and enough gross margin for the supplier to manage sourcing, compliance, payment risk and continuity.
That is why Cotiso focuses on seniority and client readiness before trying to scale headcount.
A strong interview should test a candidate against scenarios from real delivery: how they handled a difficult integration, how they designed Dataverse security, how they ran a workshop, what failed during migration, and what they would do differently.
The objective is not trivia. It is to see whether the person can reason through the problems they will face with the client.
Copilot Studio is suited to many business-agent scenarios inside the Microsoft ecosystem, while Microsoft Foundry supports more technical agent development and managed runtime capabilities. The right talent profile depends on whether the requirement is primarily business configuration, integration, custom development, governance or full agent engineering.
The commercial mistake is to label every AI requirement “agentic AI” and recruit against buzzwords rather than the actual architecture.
