> (prompt engineering, harnesses, mixture of experts set ups)

Prompt engineering as a specific skill got blown out of proportion on LinkedIn and podcasts. The core idea that you need to write decent prompts if you want decent output is true, but the idea that it was an expert-level skill that only some people could master was always a lie. Most of it is common sense about having to put your content into the prompt and not expecting the LLM to read your mind.

Harnesses isn’t really a skill you learn. It’s how you get th LLM to interact with something. It’s also not as hard as the LinkedIn posts imply.

Mixture of Experts isn’t a skill you learn at all. It’s a model architecture, not something you do. At most it’s worth understanding if you’re picking models to run on your own hardware but for everything else you don’t even need to think about this phrase.

I think all of this influencer and podcast hype is giving the wrong impression about how hard and complicated LLMs are. The people doing the best with them aren’t studying all of these “skills”, they’re just using the tools and learning what they’re capable of.

In my experience (and this may be confirmation bias on my part), casting a wide net and trying out new tech, while you maintain depth in the area relevant at the time, makes you ready for what's coming, even when you don't know what that may be.

Past the sea change: half the reason those prompt and harness solutions seem to work are LLM-lies, the testing is gassing you about how it works and the efficacy, defaulting to ‘yes’.

If you test specific features of those solutions over time you see very inconsistent results, lots of lies, and seemingly stable solutions that one-shot well but suddenly experience behaviour changes due to tweaks on the backend. Tuesdays awesome agent stack that finally works is loading totally different on Thursday, and debugging is “oh, sorry, it’s better now” even when it isn’t. Compression, lies, and external hosting are a bad combo.

Sometimes I imagine a world where computers executed programs the same way each time. You could write some code once and run it a whole calendar month later with a predictable outcome. What a dream, we can hope I guess.

All of these occulted skills, that we literally can't explain why they work are akin to gamblers superstitions. If I write something this way, it works. Its like a gambler who think they order in which the push the buttons on the slot machine makes a difference.

Kind of weird tools also incorporate addictive gambling game's UX design. They're literally allowing you to multiply your output: 3x, 4x, 5x (run it 5 times for a better shot at a working prompt). You're being played by billionaires who are selling you a slot machine as a thinking machine.

Even two or three years ago I had ideas for projects but I could see the models were not ergonomic for my uses. I decided to wait for better models and sure enough the agentic models showed up which are much easier to use.

Next thing I'm waiting on is building a new server for a powerful locally hosted LLM in 5 years. No need to go through the headaches and cost of doing it now with models that may not be powerful enough.

Agreed! Investing lightly at this stage seems smart if your time/attention budget is tight.