I help businesses design, build, and govern AI agent infrastructure. With the same engineering rigour you'd give any critical system. Not a consultancy. Not a dev shop. One senior technical person embedded in your business.
Most businesses don't have a model problem. They have an infrastructure problem, a governance problem, and a "who actually owns this" problem.
You've seen the demos. Maybe you've even built a prototype. But nobody on the team can take it from proof of concept to something the business can rely on every day.
You have budget and intent, but no senior technical person who understands how to design AI agent systems with proper standards, governance, and auditability from the start.
Without standards and infrastructure underneath, every AI initiative starts from zero. The first build should make the next one easier. Most don't.
Three phases. Each one stands on its own. No obligation to continue, but each makes the next more valuable.
Two weeks embedded in your business. I map your operations, find where AI fits, identify the human middleware holding things together, and build a concrete plan.
Take the top priority and build it properly. Production-grade, with standards, governance, and handover from day one. Not a prototype that gets thrown away.
Stay in the business after the build. Review what's running, plan what's next, and be the person you call when something comes up.
AI doesn't create fragility.
It reveals it.
Most AI failures aren't model problems. They're architecture decisions that were already fragile but hadn't been stress-tested yet.
A B2B advertising platform with a managed service layer that included campaign reporting and optimisation. The service worked, but it was labour-intensive. Each report took a full day to produce, limiting how many clients the team could support.
I stabilised the platform architecture, rebuilt the team's capabilities, and then designed an AI agent that automated the campaign analysis. The service offering scaled without scaling the headcount. Same quality, fraction of the time.
Pattern recognition from real systems, applied to decisions leaders are making now.
Effective AI guardrails must be enforced through system architecture and access controls, not prompt instructions that can be bypassed.
Read articleFour architectural properties that must be designed in, not bolted on after something goes wrong.
Read articleWhen AI acts rather than suggests, responsibility becomes undeniable. The AI Employee Maturity Model.
Read articleThe pattern across every role is consistent: walk into a situation where the technology isn't working, work out why, fix the foundations, then build what the business actually needs.
Tigerspike: scaled EMEA technology from 10 to 70+, delivering for The Economist, Shell, and Emirates Airlines. Radiate B2B: rebuilt the platform and team, then built an AI agent that transformed campaign operations.
Binary Glide applies that pattern to AI agent infrastructure for SMEs. Based in West Sussex, working across the UK.
Whether you've got a specific problem or want to explore whether this makes sense for your business.