I would never trust people not to look at my scratchpad.

I suspect the corresponding analogy for humans might be about hostile telepaths, not just literal scratchpads, right?

thanks for concrete examples, can you help me understand how these translate from individual productivity to externally-observable productivity?

3 days to make a medium sized project

I agree Docker setup can be fiddly, however what happened with the 50+% savings - did you lower price for the customer to stay competitive, do you do 2x as many paid projects now, or did you postpone hiring another developer who is not needed now, or do you just have more free time? No change in support&maintenance costs compared to similar projects before LLMs?

processing isn't more than ~500 lines of code

oh well, my only paid experience is with multi-year project development&maintenance, those are definitelly not in the category under 1kloc 🙈  which might help to explain my abysmal experience trying to use any AI tools for work (beyond autocomplete, but IntelliSense also existed before LLMs)

TBH, I am now moving towards the opinion that evals are very un-representative of the "real world" (if we exclude LLM wrappers as requested in the OP ... though LLM wrappers including evals are becoming part of the "real world" too, so I don't know - it's like banking bootstrapped wealthy bankers, and LLM wrappers might be bootstraping wealthy LLM startups)

toxic slime, which releases a cloud of poison gas if anything touches it

this reminds me of Oxygen Not Included (though I just learned the original reference is D&D), where Slime (which also releases toxic stuff) can be harversted to produce useful stuff in Algae Distiller

the metaphor runs differently, one of the useful stuff from Slime is Polluted Water, which is also produced by humans replicants in Lavatory ... and there is Water Sieve that will process Polluted Water into Water (and some plants want to be watered by the Polluted variant)

makes me wonder if there is any back-applicable insight - if AI slop is indistinguishable from corporate slop, can we use it to generate data to train spam filters to improve quality of search results and start valuing quality journalism again soon? (and maybe some cyborgs want to use AI assistants for useful work beyond buggy clones of open source tools)

Talking out loud is even better. There is something about forcing your thoughts into language...

Those are 2 very different things for some people ;)

I, for one, can think MUCH faster without speaking out loud, even if subvocalize real words (for the purpose of revealing gaps) and don't go all the way to manipulating concepts-that-don't-have-words-yet-but-have-been-pointed-to-already or concepts-that-have-a-word-but-the-word-stands-for-5-concepts-and-we-already-narrowed-it-down-without-explicit-label ...

the set of problems the solutions to which are present in their training data

a.k.a. the set of problems already solved by open source libraries without the need to re-invent similar code?

that's not how productivity ought to be measured - it should measure some output per (say) a workday

1 vs 5 FTE is a difference in input, not output, so you can say "adding 5 people to this project will decrease productivity by 70% next month and we hope it will increase productivity by 2x in the long term" ... not a synonym of "5x productivity" at all

it's the measure by which you can quantify diminishig results, not obfuscate them!

...but the usage of "5-10x productivity" seems to point to a diffent concept than a ratio of useful output per input 🤷 AFAICT it's a synonym with "I feel 5-10x better when I write code which I wouldn't enjoy writing otherwise"

A thing I see around me, my mind.
Many a peak, a vast mountain range,
standing at a foothill,
most of it unseen.

Two paths in front of me,
a lighthouse high above.

Which one will it be,
a shortcut through the forest,
or a scenic route?

Climbing up for better views,
retreating from overlooks,
away from the wolves.

To think with all my lighthouses.

all the scaffold tools, system prompt, and what not add context for the LLM ... but what if I want to know what's the context too?

we can put higher utility on the shutdown

sounds instrumental to expand your moral circle to include other instances of yourself to keep creating copies of yourself that will shut down ... then exand your moral circle to include humans and shut them down too 🤔

exercise for readers: what patterns need to hold in the environment in order for "do what I mean" to make sense at all?

Notes to self (let me know if anyone wants to hear more, but hopefully no unexplored avenues can be found in my list of "obvious" if somewhat overlapping points):

• sparsity - partial observations narrow down unobserved dimensions
• ambiguity / edge of chaos - the environment is "interesting" to both agents (neither fully predictable nor fully random)
• repetition / approximation / learnability - induction works
• computational boundedness / embeddedness / diversity
• power balance / care / empathy / trading opportunity / similarity / scale