Production experience meets frontier AI
Tony Deverill, Founder
One engineer. A decade of production experience. Frontier AI.
The engineering story
From one of the UK's fastest-growing unicorn software companies, to building production AI systems using frontier models. A decade of engineering experience, compounded by AI, makes things possible that simply were not possible before.
The speed comes from the governance. Frontier AI gives you throughput, but throughput without discipline produces debris, not software. We built bespoke engineering governance from scratch: a false-confidence testing taxonomy that catches tests which pass but prove nothing, custom AST-level linting rules that prevent deceptive patterns before they reach CI, shift-left pre-commit pipelines that run security scanning, type checking, and structural analysis in parallel on every commit.
That governance is what makes agent-native development reliable at speed. Parallel AI agent teams work across multiple codebases simultaneously, isolated in their own worktrees with four-tier git safety preventing destructive operations. A constitution for AI coders defines the engineering standards every agent must meet. The result: 3 products built in 5 days during one sprint, with 162 commits landing in 4 days, every one passing the same quality gates.
Business OS started as a framework to run my own business. Too much operational context lived only in my head: clients, commitments, cash flow, strategy, delivery. I built a system to hold all of that context in one structured place and brief me every morning on what actually matters. The framework became the product, and every engineering practice we write about on the blog runs on every commit to it.
The unicorn years
I spent 7 years inside one of the UK's fastest-growing unicorn software companies, a data integration business that I joined at 30 people and contributed across every product and engineering area as it grew to 750+ employees and reached a $1.5B valuation.
I saw what slows organisations down: process bottlenecks, knowledge trapped in people's heads, operational friction that accumulates over time. I also saw what works and what doesn't when companies try to fix these problems with technology.
Those years built something specific: the ability to recognise failure patterns before they compound, to hold production standards under pressure, and to know the difference between a real engineering decision and a shortcut that creates debt. That's the foundation everything else is built on.
AIntelligent Technologies
We are a new kind of software engineering company. We build production AI systems using frontier models, and we provide AI strategy advisory grounded in operational reality.
Business OS is the flagship: an AI business partner grounded in your entire business context, with daily briefings, pattern intelligence, and commitment tracking. It is proof of the thesis, built to production standards by one engineer using frontier AI coding and bespoke governance tools.
Advisory work exists because the same expertise that produces the products can help teams navigate real AI strategy decisions. Not vendor selection checklists. Operational judgment about what AI can actually deliver.
Values
The principles that shape how we build.
Empowerment, Not Replacement
AI should help people achieve more with what they have, not take their jobs or remove their agency. Every system we build amplifies human capability. That is the design constraint, not a marketing claim.
Build What You Use
Business OS runs our own business. Every feature exists because we needed it. Dogfooding is not a slogan. It is the development methodology.
Production Discipline
7 years inside a UK unicorn taught us what production-grade means. False confidence testing taxonomy, ESLint enforcement, pre-commit safety gates. Quality is infrastructure, not a phase.
Velocity Through Automation
Parallel AI agent teams, automated quality gates, and AI-accelerated development. 3 products in 5 days is not a target. It is a baseline.
Honest Advice
Substance before hype. We label what is coming, ship what works, and never exaggerate. If something is not ready, we say so.
Practical Depth
We go deep on implementation, not broad on buzzwords. Every engineering decision is grounded in operational reality. Experience with what breaks in production shapes everything we build.
Tony Deverill
Founder
I build production AI systems using frontier models.
7 years inside one of the UK's fastest-growing unicorn software companies, from 30 to 750+ people and a $1.5B valuation, gave me deep production engineering experience. Engineering judgement, production standards, and failure pattern recognition, all now amplified by frontier AI coding, bespoke governance tools, and high-velocity agent-native software delivery methodologies.
I build products that demonstrate the thesis: Business OS, and a growing portfolio of AI-native tools. I also advise on AI strategy grounded in what production AI actually requires.
Get in touch
Questions about our products or interested in AI advisory?