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Johnny
Startup Engineering Leader | Founding Engineer | Product Systems & AI-native Delivery
Startup engineering leader and founding-engineer type with 20+ years of experience turning ambitious ideas, messy operational reality, and business complexity into scalable software systems. I work at the intersection of product, engineering, delivery, and operations: shaping what should be built, why it matters, how it should work in practice, and how to get it delivered in a way that is fast, safe, and verifiable. I am most effective in startup and scale-up environments, where speed matters but so do trust, clarity, and long-term thinking. My background spans product shaping, architecture, operational workflows, integrations, reliability, and technical leadership. More recently, I have focused on AI-native software delivery: agent-friendly systems, explicit workflows, strong validation, and dark-factory approaches that improve execution without compromising quality.
Sunderland, UK
Selected work
View all work →In-house Engineering Transition
Established engineering standards, CI/CD discipline, and operational readiness.
Rails Marketplace Scale-Up
Grew monthly GMV from roughly GBP thousands to GBP millions while maintaining reliability.
Business-Critical Integrations
Improved delivery throughput with explicit appetites and risk containment.
Experience
View full experience →Explore My Profile
Founder / Founding Engineer
Building a product that turns static professional profiles into richer, more inspectable experiences for both people and AI agents.
Materials Market
First Engineer -> Head of Engineering (hands-on) / Tech Lead, Ruby on Rails
Joined as the first technical hire and helped transition the business from agency dependence to an in-house engineering function.
Kudocs
Tech Lead, Ruby on Rails
Led development of a LegalTech SaaS platform, owning delivery across feature work and operational maintenance.
Writing
View all writing →Early Error Handling Gives Away an Agent Built the Feature in the Wrong Order
This post argues that speculative error handling is a review smell that often reveals a coding agent built too much before learning from a working path. It makes the case for...
The Capability Is Real. The Discipline Is Sold Separately.
This post argues that autonomous-agent demos prove capability, not production readiness. It makes the case that token limits, realistic repositories, verification, operational...
I'm Learning Go the Way I Learned Python — By Shipping It
This post argues that agents can let engineers ship code they do not understand, making judgement rather than output the learning gap to solve. It describes learning a new...
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