> MCP, Apps, Skills, Gems - all this stuff seems to be tackling the wrong problem

My fairly negative take on all of this has been that we’re writing more docs, creating more apis and generally doing a lot of work to make the AI work, that would’ve yielded the same results if we did it for people in the first place. Half my life has been spent trying to debug issues in complex systems that do not have those available.

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XenophileJKO a day ago | parent | next [-]

This is true, but the reason the economics have inverted is that we can pay these new "people" <$20 for the human equivalent of ~300 hours worth of non-stop typing.

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throwaway127482 a day ago | parent | next [-]

Correct. And we know the AI will read the docs whereas people usually ignore 99% of docs so it just feels like a bad use of time sometimes, unfortunately.

	▲	threecheese a day ago \| parent [-]
		-ish; while you can be fairly certain it reads the docs, whether they’ve been used/synthesized is just about unknowable. The output usually looks great, but it’s up to us to ensure its accuracy; we can make it better in aggregate by tweaking dials and switches. To mitigate this we’re asking AIs to create plans and todo lists first, which adds some rigor but again we can’t know if the lists were comprehensive or even correct. It does seem to make the output better. And if the human doesnt read the docs, they can be beaten!

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darth_avocado a day ago | parent | prev [-]

That is not true at all. The economics you’re seeing right now are akin to Uber handing out $5 airport pickups to kill the taxi industry. And even then the models are nowhere as cheap as <$20 for ~300 hours of human work.

	▲	XenophileJKO a day ago \| parent [-]
		40 words per minute is equivalent to about 50 tokens a minute. I just took GPT-5, output is $10 per million tokens. Let's double the cost to account for input tokens which are ($1.25 per million / $0.125 if cached). For 1 million tokens it would take a 40 wpm typist.. around 20K minutes to output that $20 of worth of text. That is just typing. So about 300 hours of non-stop effort for that $20. So even if you say.. oh.. the real price is $100 not $20. The value changes are still shattering to the previous economic dynamics. Then layer in that also as part of that value, the "typist" is also more skilled than the average working person in linguistics, software engineering, etc. Then that value is further magnified. This is why I say we have only begun to barely see the disruption this will cause. Even if the models don't get better or cheaper, the potential impact is hard to grasp.

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ip26 a day ago | parent | prev | next [-]

If writing a good document and a strong API had to happen anyway, and now you can write just that and the rest will take care of itself, we may actually have progressed. Plus the documents would then have to be there, instead of skipped like today.

The counter-argument is that code is the only way to concisely and unambiguously express how everything should work.

	▲	joquarky a day ago \| parent [-]
		Honestly, we needed something to cap extreme programming and swing the pendulum back to a balance between XP and waterfall again.

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michael1999 a day ago | parent | prev | next [-]

I am also struck by how much these kinds of context documents resemble normal developer documentation, but actually good. What was the barrier to creating these documents before?

	▲	TeMPOraL a day ago \| parent [-]
		They're much more useful when an LLM stands between them and users - because LLMs can (re)process much more of them, and much faster, than any human could ever hope to. One way (and one use case) of looking at it is, LLM agents with access ("tools") to semantic search[0] are basically a search engine that understands the text it's searching through... and then can do a hundred different things with it. I found myself writing better notes at work for this very reason - because I know the LLM can see them, and can do anything from surfacing obscure insights from the past, to writing code to solve an issue I documented earlier. It makes notes no longer be write-only. -- [0] - Which, incidentally, is itself enabled by LLM embeddings.

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phlakaton a day ago | parent | prev [-]

What if the great boon of AI is to get us to do all the thinking and writing we should have been doing all along? What if the next group of technologists to end up on top are... the technical writers?

Haha, just kidding you tech bros, AI's still for you, and this time you'll get to shove the nerds into a locker for sure. ;-)

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quentindanjou a day ago | parent | next [-]

It might not be that wrong. After all, programming languages are a way to communicate with the machine. In the same way we are not doing binary manually, we might simply not have to do programming too. I think software architecture is likely to be what it should be: the most important part of every piece of software.

	▲	skydhash a day ago \| parent [-]
		You’ve got it wrong. The machine is fine with a bit soup and doesn’t care if it’s provided with punch card or python. Programming was always a tool for humans. It’s a formal “notation” for describing solutions that can be computed. We don’t do well with bit soup. So we put a lot of deterministic translations between that and the notation that we’re good with. Not having to do programming would be like not having to write sheet music because we can drop a cat from a specific height onto a grand piano and have the correct chord come out. Code is ideas precisely formulated while prompts are half formed wishes and prayers.

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CPLX a day ago | parent | prev [-]

This is actually my theory of the future. Basically, the ability to multiply your own effectiveness is now directly dependent on your ability to express ideas in simple plain English very quickly and precisely.

I’m attracted to this theory in part because it applies to me. I’m a below average coder (mostly due to inability to focus on it full time) and I’m exceptionally good at clear technical writing, having made a living off it much of my life.

The present moment has been utterly life changing.