Speaking

I speak about AI deployment in production, engineering leadership, and the trust infrastructure that financial systems need before they can absorb AI's mistakes cheaply. The perspective comes from building these systems, not studying them from outside.

Topics

• Trust, not capability: what production AI actually needs
  The bottleneck in AI adoption is not model quality but whether your systems can observe, reverse, and enforce AI output. Drawn from building AI-integrated systems inside a regulated financial firm.
• Ten paradigm shifts: what 45 years of programming teaches you about AI
  From ZX81 BASIC in 1981 to AI agents in 2026. Pattern recognition across every major technology transition. What the previous nine shifts tell us about this one.
• Bainbridge's ironies, forty years on
  A 1983 paper about factory automation predicted the exact problems we now face with AI coding assistants. What it means for how we build teams and protect the cognitive work that matters.
• The suspicion tax: when AI erodes trust faster than it creates value
  Why self-reported AI productivity gains are structurally unreliable, what to measure instead, and why the organisations that get measurement right will compound the advantage.
• Building engineers when AI writes the code
  Junior developer training in the age of AI. What skills still matter, what formative work looks like now, and why optimising for today's velocity breaks tomorrow's capability.

Formats

Keynote, panel, fireside chat. I am comfortable with unscripted formats and extended audience Q&A.

Bio

Short (50 words): Ivan Cronyn is a Principal Engineer and Head of Solutions Technology at a major London hedge fund, where he leads engineering for bespoke investment mandates. He has spent 27 years building financial systems across risk, quant, and client technology, and writes about AI deployment in regulated environments.

Long (150 words): Ivan Cronyn leads engineering for bespoke investment mandates at one of the world's largest alternative investment managers in London. Over 27 years in financial technology - at Barclays Capital, Merrill Lynch, GLG Partners, Brevan Howard, and his current firm - he has built systems across risk technology, quantitative research, and solutions engineering: the full lifecycle from signal generation through risk management to client delivery. He has programmed since 1981, starting on a Sinclair ZX81 in Durban, South Africa, and has built production systems through every major paradigm shift from structured programming to AI agents. His writing argues that trust, not capability, is the real bottleneck in AI-assisted engineering - that the models are good enough, but systems must be designed to absorb their mistakes cheaply.

Headshot

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Get in touch

For speaking enquiries: ivan.cronyn@gmail.com or LinkedIn