Thoughts About AI, Specifically LLMs

It's hard to be a software developer at the moment without engaging with LLMs. Many workplaces are introducing the technology to their workflows in various ways as senior leadership is sold on promises of 10x productivity and developers are threatened with obsoletion if they don't embrace token maxing.

Meanwhile the big AI companies are rolling out data centres into any spare patch of earth close enough to a power station and water source. Energy consumption of data centres is significant and growing having an impact on nearby communities as well as contributing to overall energy demand at a time where it's crucial to be tackling climate change. Water consumption is also an issue and simply recycling water isn't on the cards. The problem of AI scraper bots is a significant burden on Internet infrastructure.

Then there are the ethical issues. Training of LLMs requires "large" volumes of "language" to form the "model". It's not just written language though - all forms of media are up for grabs: spoken language, music and visual art are all made into models. LLM companies have violated copyrights of countless creators to train their models. While the legal arguments can go around and around, no one can deny that the overwhelming majority of authors never anticipated that their work could become part of an LLM and so never could have had feelings or made decisions about that possibility. The LLM companies have not given creators a chance to make that decision, they have denied them agency.

On the generation side of things, LLMs are being used to replace creators. There is a strong economic incentive to use an LLM for creative work instead of employing a creator. LLM outputs have become known as "AI slop": derivative, surface quality works that fulfil the commercial goal of drawing someone's attention. While commercial creation is not the ambition of the majority of creators, it has been the thing that pays the bills and allowed people to develop skills for making true art that enriches our culture.

So basically LLMs suck. Right? So why am I using them, not just at work, but in my home projects too? Part of the problem for me personally is that I'm implicated through my profession. I use LLMs at work, all day, every day, and if I don't like it, my options are to change careers. Maybe I could find a company to work at that hasn't adopted AI yet, but that would be temporary. AI is here and it's not going away. A year ago I was resisting. A year ago I believed the bubble would burst and it would all come crashing down. We would then return to the better version of the world that existed before LLMs. I feel like I've read a "AI is over" / "the bubble has burst" article every day for the last year and yet every day I show up at work and Claude Code is still there, happy to do my bidding and my industry continues to be more and more reliant on it.

I like writing code. I like doing things with computers. I always have. In a way, I've always wanted LLMs. As a kid I dreamed of building my own R2D2 and C3PO - It's why I wanted to be a software developer and engineer. I got a thrill when K9 saved day on Doctor Who. I groaned with the crew of the Enterprise as Data attempted to learn how to tell a joke. Now I have something like that technology. It's awesome! It's truly like a miracle. I just wish that it hadn't come at such a cost.

I'm in the position where I can benefit greatly from AI for personal skill development. I could choose to boycott it and forego the benefits it offers but that sacrifice will not change anything except to make me angry at other people who don't make that same trade. My chosen path is to use AI as responsibly as I can and accept that modern life involves hypocrisy and guilt. Like the cartoon: We should improve society somewhat.

So while I maintain a political stance against what is going on with AI big tech right now, I have chosen to use AI for my own benefit where it makes sense and doesn't violate too many of my ideals. A guiding principal for me is that if I really care about the quality of something, then I will not generate it with an LLM - especially writing. (The converse is that when I'm consuming, if I can detect LLM generated content, then I form the opinion that the publisher is insulting me.) But I make full use of LLMs for tasks where it has proven to be truly useful.

For software development, LLMs are truly exceptional. Having access to an LLM agent is like having the highest ranked contributors to Stack Overflow sitting next to you. I use an LLM agent to guide me through unfamiliar code bases, generate boilerplate code and proof-of-concept solutions, generate tests, self-review code and debug stack dumps. It does all of these things within minutes if not seconds where it would usually take me hours.

Where I avoid using AI is for generating whole solutions at once. I find that if it does too much unsupervised, while it might eventually converge on working code, that code will be unreadable bloated garbage full of layers of contradictions. The token maxers will tell you the solution to that problem is bigger contexts and more agents (ie. spend more money) but I have found a cheaper solution that works great and is far more enjoyable for me: I call it using my own brain. I don't think I'll ever reach the point where I find joy in watching a machine do the part of my job that I most enjoy which is designing the solutions. I feel for people (including in my own profession) where that has already been taken away from them.

For home use, I have a subscription to MiniMax which is a cheap price-capped Chinese model with ok benchmarks (similar to GPT-5.6 Luna or Deepseek V4 Pro). It's smart enough for my needs at the right price. I would much prefer to run a local model but that is beyond my means at the moment.

I hope this has been helpful to others trying to find their way through this time and I hope that we can give each other grace for the positions we arrive at when it comes to AI.