With AI You Need to Think Much Bigger!

I have noticed something in the past 12 months, something a little profound. I have noticed that I am no longer scared that a project will be too big or too complex for me, or that a project will use a technology or programming language I don’t know.

Things that have normally made me hesitate, were things that required a lot of research, for example I once had to walk away from a project as it required more than 4-layers on a PCB to route out the 484-pin BGA FPGA/processor. Back then each FPGA/processor chip was $50 and the board would have cost me about $200 and 3 weeks to get made, after that I would somehow have to assemble and test it or fork out another $100 for assembly. While I am usually pretty good, the chances of this working first or even second time were pretty low, as high speed circuits can be finicky. And even though the customer offered the use of their test equipment it meant I had to work in Christchurch!

I remember working through the specifications of the project at the time, seeing the 1000+ pages datasheet on the processor, the 200 page errata, the hundreds of posts from developers about issues, and the dozens of other design and programming guides and I just thought to myself, well yes maybe I could do it, but it would probably take 6-9 months and most of that would be study, trial and error, then at the end of it the prospect of using that particular processor on another job would be effectively zero. I walked away.

In another case I had a similar offer to replace a production system at a chemical factory, this was in 2012 and I was at the time full-on with other clients. I did however look at the system and its multitude of simple machine interfaces and, less simple external ERP systems, again totally do-able, but in this case the time I would need to dedicate to write the development would have left me a burnt out wreck. Again I had to walk away.

Fast forward to 2025 and me coming to the end of the longest contract of my career, I re-looked at the timings I had allocated for the above two projects with the better tools and AI available now and realised how much easier everything could have been. Just the other day I dusted off a project I did 14 years ago, a fill level sensor for a bottling machine. A guy wrote to me about five years ago about the project, which at the time was terribly primitive and used none-machine-learning, conventional programming to get levels and trigger an accept/reject action. I told him the sensor was now obsolete and possibly it could be done these days with a camera and a fast ML algorithm but I stopped short of any more information as quite frankly I was out of my depth.

As an experiment this weekend I re-created this system using an RPi5 compute module and a $20 camera sensor plugged into it. Within two hours I wrote my first machine learning, using the AI to assist me and got the camera on a RPi board to read levels of wine in wine bottles on my test rig. The original project took me six weeks solid! I again used the google Gemini 2.0 AI for this assignment and it had no problem explaining every line of code, every library, and every concept, and on the spectrum of AI’s Gemini is not considered the best.

I am now at a real impasse, towards the end of my career and knowing I could happily start it all again with a new insight and much bigger visions for what I could take on. It feels like wining the lottery two weeks before you die 🙂

I am now re-examining some of the other things I often thought were too complex or too far above my abilities for hobby projects, and, so long as I can afford them, give them a go. It is an exciting time to be alive.

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