Building AI Systems That Work: Lessons From Day 1,984 of My Running Streak

Today was day 1,984 of my barefoot running streak, and as I covered another 10km through the streets, my mind was processing something that's been consuming my thoughts lately: the evolution from basic AI tools to actual AI agents that work alongside my team.

I'm 19,840km into this journey towards 40,075km - a lap of the world - and what strikes me most about both this mission and building AI systems is the importance of gradual, sustainable progress. You don't wake up one morning and suddenly run ultramarathons, just like you don't build sophisticated AI agents overnight.

The parallel became clear to me as I reflected on how I've approached AI implementation over the past year. I started with simple ChatGPT queries - the equivalent of those first tentative runs when I began this streak. Basic questions, basic answers. Nothing revolutionary, but it built familiarity and confidence.

Then I moved to what I call "conversational AI" - having deeper, more contextual discussions with the technology. This mirrors how my running evolved from short, careful distances to longer, more challenging routes. You build capacity gradually.

The real breakthrough came when I started creating custom GPTs. These aren't just chatbots; they're specialised tools trained on specific datasets from my business operations. I've built five so far, each serving a distinct purpose.

My Runpreneur GPT contains transcriptions from every video I've recorded. When my team publishes content on my behalf, they run it through this system to maintain my tone of voice. It's remarkably accurate - something that's historically been one of the hardest things to delegate consistently.

The Boardroom Mentor GPT fascinates me most. I've fed it comprehensive documentation from business leaders I respect, creating an AI advisor I can consult when making difficult decisions. It doesn't replace human insight, but it provides another perspective for stress-testing my thinking.

Then there's my Knowledge Base GPT - essentially every standard operating procedure from every business I've ever run, all accessible through simple questions. Instead of hunting through folders or trying to remember which Loom video contains specific processes, I can ask direct questions and get immediate answers.

My Meetings GPT serves as an institutional memory. Every internal meeting transcript goes in, creating a searchable database of decisions, discussions, and commitments. No more "I'm sure we discussed this, but I can't remember when" moments.

The Airtable GPT represents something more advanced - actual integration between AI and our core business systems. While Airtable has built-in AI, I've found ChatGPT superior for analytical conversations and perspective-driven queries.

What excites me most is the next evolution: converting these GPTs into actual AI agents that execute tasks autonomously. Imagine an Executive Assistant GPT that can triage emails, assign tasks, and update our project management system following established protocols. We're not quite there yet, but the foundation is being built.

The lesson for me was about progression and patience. Just like this running streak, effective AI implementation isn't about dramatic leaps - it's about consistent, incremental improvement. I'm ahead of many people in AI adoption, but behind many others. The key is progressing at a pace that allows for proper integration and learning.

I avoid what I call "AI rabbit holes" - those complex projects that consume enormous time without delivering immediate value. Instead, I align AI development with quarterly business objectives, ensuring each implementation serves a real purpose.

The broader insight from today's run is about the compound effect of consistent effort. Every day I lace up my Vibram FiveFingers and head out, I'm not just maintaining a streak - I'm building capacity for the days ahead. The same principle applies to AI capability building. Each custom GPT, each integration, each small automation adds to our overall operational efficiency.

This isn't about replacing human capability; it's about amplifying it. The best AI implementations I've seen enhance human decision-making rather than replace it. My Boardroom Mentor GPT doesn't make decisions for me - it helps me think through them more thoroughly.

As I approach the 20,000km mark with just over 20,000km remaining, I'm reminded that significant achievements come from daily discipline rather than sporadic intensity. The same truth applies to building AI systems that actually work.

Whether you're building AI capabilities or pursuing any long-term goal, the message is clear: start where you are, progress at your own pace, but start now. The gap between those who act and those who don't only widens with time.

Every step forward on this 40,075km journey brings me closer to the £1M target for children's causes. Every AI system we implement makes our operations more efficient, creating more capacity to focus on what matters most - the mission to save children's lives through this ultimate ultramarathon of run vlogging.

The technology is remarkable, but the purpose behind it is what drives consistent action, day after day.