Vendor Lock-in, AI Freedom, and an Engineering Lead's Mixed Emotions

Note: This post was a braindump of ideas, then refined a little using LLM’s, but have tried to minimise its the use as we all see way too much AI slop on the web now. I just to made it a little more coherent than my braindump.

From Autocomplete to Autonomous Agents: My AI Journey

I’ve been experimenting with AI since the GPT-2 days, playing with early versions that felt like slightly smarter autocomplete tools, and lately diving deep into full-blown coding agents that build entire solutions from simple specs. It’s been both fascinating and unsettling.

Redefining the Developer’s Role

Dread the AI

Watching an agent read a short description and then quickly churn out functional code, often within minutes, leaves me simultaneously amazed and slightly horrified. Immediately, my mind asks, "What's been the point of my last 20 years of coding?" It feels somewhat existential. But then again, maybe I comfort myself with thoughts of the past: when IDE autocomplete came about, plenty of developers saw it as cheating, worried it would dull our coding skills. Or think about the rise of low-code and no-code solutions. Great for simple tasks, sure, but that tricky 20% of customisation still takes up 90% of the headaches. Maybe these AI coding agents are on a similar trajectory.

Today, these agents still get stuck and need human engineers with experience and good system design intuition to nudge them along, much like mentoring junior developers, albeit ones who learn incredibly fast. But it’s clear they’re rapidly improving, and the line between junior dev (and to be honest mid to senior devs in certain domains) and agent is getting increasingly blurred.

Rethinking Vendors & Outsourcing: AI as the New Development Partner

What really intrigues me is what this means for the wider tech industry, especially in sectors reliant on big, expensive SaaS providers. Imagine, for instance, a bank (which I know a thing or two about) using costly vendors for compliance or KYC solutions. Typically, these systems are generic and built for broad markets, forcing banks to adapt their processes to the software. Integration becomes a hassle, costly and time-consuming. Now imagine cutting out that vendor, building something tailored directly to the bank’s needs using an AI agent. Integration suddenly becomes the easier part, and the business gets control over its solution roadmap. Sure, you’ll still need domain expertise, but guess what? AI’s ability to deep-dive into research could bridge that gap too. Of course, while AI can research regulations, the critical judgment and ultimate accountability for applying that knowledge correctly, especially in tightly regulated areas like finance, still has to rest firmly with experienced humans.

I’m also thinking about the outsourcing industry. In my experience, if your specs aren’t rock-solid, outsourcing can quickly turn into a frustrating, drawn-out ordeal. Interestingly, the same applies to working with AI agents: vague requirements mean poor outcomes. But here’s the thing: if you’re going to spend all that effort writing impeccable specs, why not feed them to an AI agent instead of negotiating contracts with an outsourcing firm? Could this mean the end of traditional software outsourcing? Mind you, ensuring the AI truly understood the nuances, or figuring out how to handle maintenance when the underlying AI model itself evolves, definitely presents a whole new set of hurdles to replace the old ones. (But I will hand wave that away for now as I don’t have the answers)

But before panic sets in, let’s step back a moment. Is this really a doomsday scenario for software developers, or could it actually be more like the internet boom of the late 90s, full of opportunities for those who adapt? Certainly, if you’re not keeping pace with these new developments, things look bleak. But, let’s face it, keeping up is exhausting. Perhaps adaptation for experienced devs means shifting focus even more towards the things AI doesn’t easily replicate: robust architecture, insightful system design, rigorous validation, mastering the art of guiding the AI (prompt engineering, if you like), and providing that crucial human-in-the-loop oversight. Maybe the best we can do right now is leverage AI tools to stay ahead, at least temporarily.

Empowering Non-Engineers: The Rise of Citizen Developers

One thing that genuinely excites me is seeing non-engineers build things with tools like Replit or Lovable. Watching their ideas quickly come to life gives them the same spark of joy that initially drew me into programming, without the barrier of years of coding experience. This might feel threatening initially, “Are they taking our jobs?”, but actually, these fresh minds often bring completely new perspectives and ideas that can birth entirely new businesses overnight. And new businesses mean new opportunities, especially for integration, support, and infrastructure.

“Touch Grass”

Local Village Mayfayre

This weekend, while walking around a local village market, I found myself surrounded by stalls selling food, crafts, beer, with kids running around playing cricket and a band playing. People were interacting naturally, and the pace felt refreshingly slower. Not a single conversation touched on AI (and don’t worry, I didn’t bring it up either). Being at this village market made me realise how much my head has been spinning recently with AI, coding, and researching stuff online. It was nice just slowing down a bit, being around real things and chatting to actual people about everyday stuff. It reminded me how important it is to step away, slow down, and, as my son likes to say, "touch grass" now and then. Staying connected to your local community and chatting with people face-to-face matters. If AI really does end up taking over a lot of stuff, at least we're all in the same boat, and looking after each other becomes even more important.

Challenges and Opportunities Ahead

Ultimately, I’m conflicted, but mostly excited. Having ridden the rollercoaster of AI hype for several years now, I sense we’re hitting a maturity plateau, where these tools become genuinely useful, integrated into our workflows rather than replacing them completely. Of course, another explosive breakthrough could be just around the corner. But even if there isn’t, one thing is clear: AI isn’t going away. Our challenge, and opportunity, lies in figuring out how best to adapt.

I can talk for hours about this topic, but tried to keep it relatively focused and I would like to expand on how this is affecting non developers too. I will try keep putting my thoughts out there as I get some time and I am not either vibe coding, or “Touching Grass”