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The exact same thing happened with xClaw where people where going "look at this app that got thousands of stars on GitHub in only a few days!".
How is that different than the followers/likes counts on the usual social networks?
Given how much good it did to give power to strangers based on those counts, it's hard not to think that we're going in the completely wrong direction.
With AI, it feels like deterministic outcomes are not valued as experience taught us it should. The absence of means to measure outcomes of these prompt documents makes me feel like the profession is regressing further into cargo culting.
1. Reproducibility
2. Chain of custody/SBOM
3. Verification of artifacts of CI
All three of which are not simply difficult but in fact by nature impossible when using an LLM
LLMs are the eternal September for software, in that the sort of people who couldn’t make it through a bootcamp can now be “programming thought leaders”. There’s no longer a reliable way to filter signal from noise. Those 3000 early adopters who are bookmarking a trivial markdown file largely overlap with the sort of people who breathlessly announce that “the last six months of model development have changed everythi…
Earlier quoted context omitted.
I just packaged the extension for the fun of it! And I do want people to try for themselves, that is the point. About people that are not dumb; surely many people are not dumb; many people are very smart indeed. But that does not prove there are no dumb or gullible people!
I wonder if someone could explore creating a standalone product out of that markdown, just for the fun of it.
You know, it's good old prompt/context engineering. To be fair, markdowns actually can be useful because of LLM's (Transformer's) gullible/susceptible nature... At least that's what I discovered developing a prompting framework. Of course it's hilarious a single markdown got 4000 starts, but it looks like just another example of how people chase a buzzing x post in tech space.
With AI, it feels like deterministic outcomes are not valued as experience taught us it should. The absence of means to measure outcomes of these prompt documents makes me feel like the profession is regressing further into cargo culting.
That is because nothing in the world is deterministic, they are just all varying degrees of probability.
https://rationalwiki.org/wiki/Deepity
Determinism concerns itself with the predictability of the future from past and present states. If nothing were deterministic, you wouldn’t be able to set your clock or plan when to sow and when to harvest. You wouldn’t be able to drive a car or rest a glass on a table. You wouldn’t be able to type the exact same code today and tomorrow and trust it to compile identically. The only reason you can debug code is determinism, it is because you can make a prediction of what should happen and by inspecting what did happen you can can deduce what went wrong several steps before.
My probably incorrect, uninformed hunch is that users convinced of how AI should act actually end up nerfing its capabilities with their prompts. Essentially dumbing it down to their level, losing out on the wisdom it's gained through training.
I've experienced in times of gpt 3, and 3.5 that existence of any, even 1-word system message changed output drastically in the worse direction. I did not verify this behaviour with recentl models.
Since then I don't impose any system prompts on users of my tg bot. This is so unusual and wild in relation to what others do that very few actually appreciate it. I'm happy I don't need to make money for living with this project thus I and can keep it ideologically clean: user's control over system prompts, temperature, top_p, giving selection of the top barebones LLMs.