Insights
Why Agentic Commerce Will be Won or Lost on Product Data Quality
Agentic commerce will be won on product data quality. Here is what we are learning from retail catalogues and how to make your products readable to AI agents.
No Figma MCP? How We Still Built 350+ Figma-Accurate Screens With Kiro
For security reasons, we couldn’t use the Figma MCP - so, what then? A context engineering and spec-driven development story from a regulated financial services company, and what it taught us about keeping AI-generated frontend code under control.
It’s Time to Understand Your Data’s True Value
Your data may be worth far more than brokers are offering. Learn why proprietary data matters in AI, how to fix it at source and whether to sell or license it.
From Signals to Strategy: Horizon Scanning for Energy Network Innovation
Discover how agentic AI, knowledge graphs and AI agents power horizon scanning for UK energy networks, mapping emerging technology to strategic objectives.
AI powered horizon scanning for energy networks. Learn how AI agents and context graphs turn emerging technology signals into insights mapped to RIIO-3 goals.
Why businesses need an AI kill switch strategy, not a single off button
A single off switch is an impractical response to AI risk when AI is spread across customer channels, internal tools, data pipelines and agents. In an exclusive Q&A with Digitalisation World, Ben Saunders explains how layered, proportionate controls over access, models, data and fallback processes keep businesses in control when AI systems fail or change.
Almost Right. The Hidden Cost of Code That Passes Every Check
"Suddenly I am a full-time code reviewer." Read Elena's full breakdown of how AI-generated code can pass every check and still be wrong, including the five patterns she now looks for in every diff.
What We Learned Testing Five Sensitive Data Detection Tools
We tested sensitive data detection tools Amazon Macie, Microsoft Purview and three open source tools on 18,049 documents to see how much sensitive data automated data classification really finds. Read for our recommendations and what a layered approach costs to run.
The missing foundations holding back AI in energy and utilities
AI adoption is accelerating across energy and utilities, yet many initiatives never progress beyond experimentation. Writing in Energy Manager Magazine, Mark Simpson explains why proprietary data, targeted use cases and explainable governance matter more than model capability when it comes to scaling AI in critical infrastructure.
Cutting Code AFK. How Ralph Wiggum can do the work for you
So it finally happened, I was pulled into a meeting and told to replace myself with AI.” Read Elena’s full breakdown on how to use the Ralph Wiggum Loop to speed up development, including learnings and a step-by-step guide.
The reality of sovereign AI: How to avoid dependency without building everything yourself
Ben Saunders, Co-Founder of WeBuild-AI, writes for Silicon Valleys Journal on why sovereign AI is about control and optionality, not building every model in-house, and how a multi-model control plane reduces vendor lock-in.
The AI-Native SDLC eBook
A comprehensive guide to what the software development lifecycle looks like now that AI agents are part of the team, and how to implement it at enterprise scale.
Why most AI strategies fail before they scale
Mark Simpson, Co-Founder of WeBuild-AI, writes for EnterpriseTalk on why AI tools spread while adoption stalls, and why outdated workflows and change management, not a skills gap alone, block AI strategies from scaling.
The real barrier to AI in financial services isn't regulation but trust
Ben Saunders, Co-Founder of WeBuild-AI, writes for The European Financial Review on why most financial services firms use AI in some form yet struggle to reach production, and why organisational confidence and accountability matter more than regulation alone.
Why will out-of-the-box AI fail in energy and utility operations?
Mark Simpson, Co-Founder of WeBuild-AI, writes for Energy Sustainability Solutions on why energy and utility AI programmes stall in pilot, and why generic models fail without connected operational data, domain context, and governance on critical infrastructure.
Why the future of AI in banking depends on trust, not trials
Ben Saunders, Co-Founder of WeBuild-AI, contributes to The Fintech Times on why banks stall after proof of concept, and why scaling AI in banking is an operating-model and trust problem, not only a regulatory one.
