Insights
Field notes from production.
What we learn building AI systems for Gulf enterprises and government, written for the people who have to make it work, not for the algorithm.
Playbook · Featured
June 2026 · 7 min read
From pilot to platform: the 70% nobody demos
The distance between a working pilot and a governed production system is where most enterprise AI budgets die. A field guide to the unglamorous majority of the work.
Read the articlePerspective
The agentic enterprise: what actually changes
Beyond the hype cycle, agentic systems change three specific things about how work moves through an organization. The rest is continuity.
May 2026 · 5 min read
Technical
Arabic is not a translation target
The performance gap between English and Arabic is invisible in the vendor demo and everywhere in production. What Arabic-first engineering actually requires.
April 2026 · 6 min read
Technical
Evals are the new unit tests
If a model change can reach production without a number turning red, you do not have an AI system. You have a liability with a chat interface. How evaluation-driven delivery actually works.
April 2026 · 6 min read
Playbook
Build, buy, or wait: a decision framework for enterprise AI
The most expensive words in enterprise AI are “we should build that ourselves”, and perhaps only “let's wait and see” rival them. A framework for making the call per use case, with reversibility as the tiebreaker.
March 2026 · 6 min read
Regulation
PDPL and the architecture of trust
Saudi data law is not a compliance checkbox at the end of an AI project. It is a design input at the start. How residency, consent, and auditability shape system architecture.
March 2026 · 6 min read
Perspective
Why most enterprise AI pilots die in the demo
The pilot didn't fail in month six. It failed in week one, when nobody agreed what number it was supposed to move. On baselines, kill lists, and the discipline of starting.
February 2026 · 5 min read
Disagree with something we wrote?
Good. Those are our favorite conversations. Tell us where we’re wrong and what you’re seeing instead.