~ stockholm, sweden · ai architect · 20 years shipping software
I'm Martin McCarthy - the architect leading the AI vision for Telenor Sweden's software development lifecycle. I design the systems, guardrails, and practices that bring agentic AI into how organisations deliver software: safely, measurably, and at scale - and I keep my architecture honest by building complete multi-agent systems hands-on, end to end.
I'm a solution architect and AI architect based in Stockholm, with twenty years of hands-on engineering behind the title. My career started in payment systems in Dublin, then ran through lead engineering roles across Swedish fintech, healthtech, and logistics - Qliro, Budbee, Doktor.se - followed by five years as an independent consultant for Nordic enterprises like Nobia and Capacent. I trained in deep learning back in 2017, when it was still a niche pursuit; today AI is the centre of everything I do.
Now I work at the intersection most organisations struggle with: making AI genuinely useful in how software gets built. At Telenor Sweden I'm the architect for DevBoost, the team chartered to drive AI uplift across the SDLC - and I lead its AI architectural vision: agentic development workflows, the knowledge systems that make large codebases consumable for AI, and the governance that keeps humans approving every stage. At the heart of it sits what I call the enterprise second brain - knowledge compiled by AI, validated by humans, governed centrally.
And I practise what I preach. As my own applied R&D, I've designed and built a complete multi-tenant agentic platform end to end - three cooperating AI agents for reception, accounts, and marketing - on Google Cloud with Gemini function calling, retrieval-augmented generation, and MCP tooling. Every layer is mine, from the data model to the guardrails - a zero-to-production build that automates real business operations (bookings, invoicing and tax compliance, campaigns) - and I use it to pressure-test every architectural opinion I hold.
That combination is my edge. I can stand in front of an executive team and argue the strategy, and then open a terminal and build the system. And I think in products, not just architectures: technology counts when it moves a business outcome. I don't just advise on AI - I test my ideas against reality before I recommend them.
Joined Telenor as a Solution Architect; since 2025 I'm the architect assigned to DevBoost, the team chartered to drive AI uplift across Telenor Sweden's software development lifecycle. I lead the AI architectural vision for that mission - agentic development workflows, AI knowledge systems that make large codebases consumable for models, multi-agent delivery pipelines spanning architecture to release, and the governance layer that keeps a human approving every stage. The remit runs from strategy and platform architecture to tool evaluation and hands-on delivery across the engineering organisation.
Five years of senior frontend and full-stack engineering consulting for Nordic enterprises and scale-ups - clients included Doktor.se (digital healthcare), Nobia (Europe's leading kitchen group), and Capacent (Nordic management consultancy). Alongside client delivery, I went deep on applied AI, designing and building a complete multi-tenant agentic platform end to end as personal R&D - the hands-on foundation for the AI architecture work I lead today.
Led frontend development and the agile process at one of Sweden's largest digital healthcare providers, building real-time patient-facing care flows.
Led frontend development at the logistics scale-up, building the real-time systems behind last-mile delivery.
Led a team of six engineers building online payments and checkout for one of the Nordics' largest e-commerce groups.
Opinions and working notes from building agentic systems and rolling AI out across engineering organisations.
Karpathy's LLM wiki became Google's OKF in eight weeks - the knowledge layer is being standardised. My architecture: compiled by AI, validated by domain owners, governed centrally.
read →Identity, guardrails, cost control, knowledge - how the two clouds' managed agent stacks compare on the four pillars that decide production-readiness, and what to build vs rent.
read →A chargeback dispute walked through an automation pipeline, stage by stage: extraction, policy retrieval, calibrated confidence, a decision-class routing table, and the audit trail - with real industry numbers.
read →Agents will draft every stage of delivery. The organisations that win won't be the ones with the most autonomy - they'll be the ones with the best gates.
read →Developers in a rigorous study felt 20% faster and measured 19% slower. How to evaluate AI tooling with evidence instead of vibes.
read →If you're working on agentic development, AI platform architecture, or automating real business processes with AI - the hard, ambiguous, high-trust kind - I'm always glad to compare notes.