I've often wondered how viable it is to use AI to fill out the ecosystem gaps in awesome but niche languages (still looking at you OCaml...).
I've not gone too deep down this train of thought because a standard library/ecosystem should be solid and I don't think LLMs are quite there... but if we can use LLMs+Lean maybe we can get the quality we need to bootstrap more of the Lean ecosystem?
A couple of years ago I listened to a Lex Fridman podcast with a researcher at the MIT Media Lab. I don't know the status of it, but the researcher spoke about how people in developing countries were experimenting with using local resources as 3D printer feedstock - things like ground-up sea shells - as a way of using local supply lines.
One of the most interesting things he said was that the current waste from 3D printing (and other technology) is really a sign of technical immaturity; nature repurposes everything - there is no trash in an ecosystem, only food for something else. Maybe we'll eventually learn to build infrastructure like that.
Absolutely the same. Now that Fable is back, the Claude voice interface is... worth dealing with. The app mostly seems to have trouble recovering from networking issues which is jarring in a deep conversation.
I'm so mad that this might make me re-subscribe to ChatGPT. I wouldn't have believed how much I use the voice feature before LLMs and ChatGPT currently has the best voice interface. I think Grok's interface is the next best, then Claude.
One of the more counter-intuitive parts of management that I've found is that your focus shifts from delivering a technical outcome to care-taking a team that delivers technical outcomes. It's a meta-function.
A related physics metaphor - in general as you move from IC to SR to management, your focus shifts from changing the position to changing the velocity and acceleration of those around you.
It definitely violates DRY but if you keep passing the JWT down the call chain, you can do redundant permission checking in your business layer.
Now the reasonable response to the above is that this should be happening in a dedicated authn/z concern - and that is correct! But when paranoia is called for, it's not unreasonable to have redundant checks in logic where authz is critical.
His Blindsight is one of my all time favorite novels (sequel is good to). His short story Malak - about a military drone given a prototype ethical program - is so good.
Another suggestion for optimizing local inference - the Hermes team talks a lot on X about how much better results are when you use custom parsers tuned to the nuances of each model. Some models might like to use a trailing `,` in JSON output, some don't - so if your parser can handle the quirks of the specific model, then you get higher-performing functionality.
> Treat code design and architecture as the thing that lets your slop canons (90% of engineers even pre-ai) move fast without breaking things
I'm currently of the opinion that humans should be laser focused on the data model. If you've got the right data model, the code is simpler. If you've got the relevant logical objects and events in the database with the right expressivity, you have a lot of optionality for pivoting as the architecture evolves.
It's about that solid foundation - and of course lots of tests on the other side.
I've not read Aristotle directly but translating eudaimonia was an example in the book that I mentioned. The argument was that eudaimonia is often translated as happiness but that doesn't make sense in contexts where we talk about a soldier dying experiencing eudaimonia (suggesting a loose translation).
A few years ago I read a claim that the word 'happy' is relatively young - ~500 years old - and that translations of others words into 'happy' are somewhat approximate.
My takeaway is that (presuming the argument is correct) that much of human striving is probably better described with specific words (as you suggested - joy, accomplishment, fulfillment, excitement, etc). For most of human history, most people probably didn't think "I want to be happy" but "I want to have a good partner", "I want a big family", "I want my crop to grow so I don't die."
I wonder how much unhappiness is caused by seeking a poorly-defined ideal of happiness.
The book was called "Power, Pleasure, and Profit: Insatiable Appetites from Machiavelli to Madison".
On a related note, this type of reasoning is what made me flip my opinion on microservices. I've generally been skeptical of a many-microservice architecture for the last decade but LLMs change that - a small microservice is more likely to fit in a context window.
I think this gestures at a more general point - we're still focusing on how to integrate LLMs into existing dev tooling paradigms. We squeeze LLMs into IDEs for human dev ergonomics but we should start thinking about LLM dev ergonomics - what idioms and design patterns make software development easiest for AIs?