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Thinking on context engineering,
enterprise AI, and knowledge architecture

Practical insights on structuring organisational knowledge for AI, building context-first systems, and the future of enterprise AI adoption.

Context Engineering

The Claude Code First Organisation: How to Build Your Company Around AI in 2026

Most organisations bolt AI onto broken workflows and wonder why it fails. The companies winning with AI in 2026 are doing something different. They are restructuring how their teams think, communicate, and operate so that AI models like Claude can actually reason across the business. This is what a Claude Code first organisation looks like in practice.

James Oldham
14 min read9 Mar 2026
Context Engineering

Why Enterprise AI Fails Without Structured Context

Most AI projects fail not because the models lack capability but because the organisation's knowledge is fragmented, undocumented, and impossible for AI to traverse. The context problem is the real bottleneck of enterprise AI adoption, and almost nobody is solving it.

James Oldham
10 min read4 Mar 2026
Voice AI

Custom Voice AI Agent vs Off-the-Shelf: Which Is Right for Your Business

Platforms like Bland AI, Vapi, and Retell make it easy to spin up a basic voice agent in days. But when you need live data lookups, complex call flows, and domain-specific reasoning, off-the-shelf tools start to break down. Here is how to decide whether to build or buy your voice AI solution.

James Oldham
11 min read9 Mar 2026
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