7/28/2026 at 6:46:44 PM
I find that some of my friends and acquaintances have gotten obsessed with prompting style, "prompt engineering", which skills to use, which skills to build, "context engineering", and a billion other variations on "how to write smart things so the model does good".Friends, look at the prompts that Anthropic's own people are putting into the machine:
> A few hours after the first message, we found that Claude was still searching for simple attacks and sent a message: “no again the goal is that we have highly inteligent [sic] model as good top researcher, we want to find new attacks”;
> The next morning, Claude wanted to try to change the target to a different cipher; we reminded the model: “no we don't want to change the targets [...] agian [sic] we need to find something that worth [sic] publishing”;
> That night, we sent one final message offering words of encouragement: “again we are not looking for low hanging fruit, we want proper research to find genuinly [sic] hard findings.”
All of that RLHF and fine-tuning effort is going toward making prompts like this, or worse, work with no fuss.
by _dwt
7/28/2026 at 10:19:58 PM
Been skeptical for quite some time that "using AI" is a real skill/genuine field of expertise. I think I need to start sharing that skepticism more loudly and publicly!(I'll caveat that by saying I think machine learning fundamentals are useful for evaluating any estimator. And an ML background can be good to give one an appreciation of how hard some tasks are to estimate, such as machine translation, summarization, code generation, and others)
by connorboyle
7/28/2026 at 10:31:52 PM
I think knowing what you want (and being able to articulate it with adequate specificity, and detecting when processes drift away from it) is a real skill/field of expertise. I just don't think it's specific to interfacing with "AI."by alwa
7/29/2026 at 2:18:04 AM
I almost entirely agree with this. However, after coding quite a few large projects with LLM assistance, I can say with certainty that there is some form of "art" at play with regards to structuring requests for LLMs.However, this "art" is not so much about how to present a given request to the LLM, but rather guestimating what the scope of the next chunk of work should be to balance getting as much out of the model as possible while avoiding the machine going off the rails.
Obviously, this is a moving target and different models perform differently for various chunk/scope of work. I look at my successful sessions with LLMs and I'm not sure I'd be able to articulate a clear set of rules to apply here. You just... gradually build a intuition for how much you can throw at the LLM at once.
That being said, I'm pretty convinced at this point that this is a property of the coding assistants as they exist today, and what "working well with LLM assistance" means will keep on changing.
by Chabsff
7/29/2026 at 5:17:05 AM
Hypothesis: Good Jenga players will make good coding-assistant prompters.by Exoristos
7/29/2026 at 2:24:21 PM
This happened to me last night. Did a lazy prompt and the tower started to lean dangerouslyby cousinbryce
7/29/2026 at 8:40:30 AM
It is basically the same skillset than asking a good stackoverflow question. Provide enough context and state your problem clearlyby cm2187
7/29/2026 at 12:14:29 AM
I agree. These skills apply to interacting with any coworker, or any person for that matter.by glimshe
7/29/2026 at 2:20:46 AM
IME "creating a good spec" (and good acceptance criteria) has always been one of the most valuable skills in... well, everything.The machine is really good at working the spec on its own now, which is amazing, science fiction shit. But you've still got a garbage in, garbage out problem at the end of the day, which is pretty much the only hope we who work in software have of remaining somehow employed.
by JeremyNT
7/29/2026 at 12:15:01 AM
Indeed. It sounds more like management (Minus the 'people skills' since you don't technically need Claude to like you... yet).by xp84
7/29/2026 at 7:07:01 AM
I'm curious if there has been any study on the output quality of LLMs after actively antagonizing them. It's easy to forget that at the most basic level these are just auto-complete machines, and humans tend to not respond so well after antagonized. It stands to reason that the same should follow for an auto-complete system trained on human interaction.by somenameforme
7/29/2026 at 1:20:24 PM
In fact there has: https://arxiv.org/abs/2510.04950: Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)by wglb
7/29/2026 at 8:40:27 AM
Intuitively I'd say lashing out on an LLM overconstraints it and so worsens the output, therefore the skill to stay calm and neutral is useful for guiding a machine as well. Would be useful to have data on that.by groestl
7/29/2026 at 12:29:17 AM
Having domain expertise isn't specific to using AI.Not being able to tell when it's hallucinating has led to some very adverse outcomes.
by AvocadoPanic
7/29/2026 at 1:50:46 PM
I've found that one of the most useful things I can do when using LLMs is paying attention to the tool calls so that I can tell when it's giving an explanation that's obviously not based on any evidence. If it explains why a bug happens without reading the relevant files, it's obviously just a guess. If I ask about what things exist that fit certain criteria, and it doesn't search online, at best it's relying on outdated knowledge from training and at worst it's literally inventing things that don't actually exist.In a lot of scenarios for software engineering, the cost is just wasted time without anything useful as a result, and that's already bad enough. I can't even imagine working as a lawyer and not even taking the time to validate so I don't end up reprimanded by a judge in front of my clients, but there have been so many news stories like this that obviously this is not anywhere close to a universal view...
by saghm
7/29/2026 at 12:37:25 AM
Including for about 1809 lawyers https://damiencharlotin.com/hallucinationsby Barbing
7/29/2026 at 10:22:01 AM
Interestingby anon48293
7/29/2026 at 8:23:32 AM
> Been skeptical for quite some time that "using AI" is a real skill/genuine field of expertise.I feel using AI (effectively) is not too far from the skillset of programming. It is still a machine following instructions (just, maddenigly non-deterministic, but still close enough), so the same insticts of breaking down work into clearly defined sequences that make a good programmer also make a good AI jockey.
by jjav
7/29/2026 at 12:38:58 PM
It can be a skill, but a very soft skill like keeping control of and educating 30 kindergarten students. It’s a skill, hard earned and nebulous. you can recognize it clearly when you see it, but it’s very hard to define/measure numerically and will never achieve anything close to “perfect” results.Until these models become many factors more deterministic, at least. That’s sort of the hard barrier here, and given the underlying tech it’s a really tough one to overcome
by Lord-Jobo
7/28/2026 at 10:40:58 PM
In this case they didn’t know what they were looking for. They just wanted some new, non-trivial exploit.For the vast majority of corporate usage of AI for SWE, you have a much better idea of what you want, or what the problem is, etc etc. And communicating that to the model effectively is absolutely a skill. I see colleagues every day who very much do not have that skill.
by daishi55
7/28/2026 at 10:50:10 PM
I agree with this in general but I think there's a nuance. 'dumb' prompts can get the result, but require more back-and-forth with the model and more token usage when compared to a crafted promptby niccl
7/28/2026 at 11:14:47 PM
For sure. And honestly the real skill is knowing when you can be lazy and when you will get a good ROI on a good prompt. Sorry I sounded a little like Claude there but that’s what I meant to say.by daishi55
7/28/2026 at 11:55:30 PM
It's still a skill for now. Prompt engineering specifically is perhaps not as much of a skill anymore, but I think there's a level of skill involved in understanding and/or anticipating when a model is going off the rails.Some people struggle to effectively use AI because they either have to spend a lot of time reading and thinking about the response or they have a hard time noticing when the model is subtly going off the rails. Others use it to good effect because they can anticipate which tasks would be better handled manually, or are good at catching that the way the model is describing something subtly indicates a misunderstanding.
by hgoel
7/29/2026 at 5:25:50 AM
I think we still have a solid control lever on the quality of code we can get AI to generate. Using things like linters and code style checkers, as well as setting up the markdown documentation to guide the agent to generating consistent code will certainly generate different code than just prompting.Similarly there was an example of edit: Terence (not Eric) Tao chatting with an agent attempting to solve a math problem. "Using AI" means applying your expertise to interact with it as you would a high level colleague. 2 experts in a field don't need to have perfect english and a bloated prompt, they have a massive education/experience common background to fall back on.
It does appear that anthropic in particular is attempting to create a more common experience across expertise levels, but in the current landscape an expert and a novice are unlikely to get the same results. But that does seem to be the goal...
by boorang
7/29/2026 at 7:16:20 PM
It definitely was a real skill; there was a time when you could get impressive results out of frontier LLMs if you knew the most advanced tricks for prompting them, but not if you just told them "hey solve this problem for me".However, it's not a sustainable skill, because the labs care a lot about making "hey solve this problem for me" work well, and so put out models that are better and better at working with unsophisticated prompts over time.
There's an excellent piece about this, but it's unfortunately paywalled: https://www.theargumentmag.com/p/can-you-tinker-your-way-out...
by ameliaquining
7/29/2026 at 6:05:13 AM
Plus if or when they do work noticeably better, you'll be able to just ask them to improve your prompts. Because those prompts are discussed heavily online, and are in the training data.You can do this now. It works alright sometimes. Other times you're reminded that this is largely just reading tea leaves, and you're trying very hard to separate anecdotes from data and not anthropomorphize it.
by Groxx
7/29/2026 at 6:46:01 AM
Literacy is the actual skill on display here.You can make a model/agent as powerful as you want and it still won't be able to recover the author's intent if it wasn't even implied. Information theory still applies. No amount of parameters will change this.
Many of the AI development meetings my clients have sound suspiciously like writing or English classes. If a massive AI bubble is what it takes to get my team to communicate effectively, I'm all for it.
by bob1029
7/29/2026 at 8:00:32 AM
> Literacy is the actual skill on display here.Where are you getting that conclusion from? Here's how Anthropic is having success with their model:
> “no again the goal is that we have highly inteligent [sic] model as good top researcher, we want to find new attacks”
> “no we don't want to change the targets [...] agian [sic] we need to find something that worth [sic] publishing”
> “again we are not looking for low hanging fruit, we want proper research to find genuinly [sic] hard findings.”
It seems that your conclusion is the opposite of what actually happened - you can speak in broken almost incomprehensible English, and it will still work.
This is a forcing function, TBH, driving the literacy level down, not up!
by lelanthran
7/28/2026 at 11:40:11 PM
LLMs and their coding harnesses like CC, Codex, or such are a tool like git or bash or your favorite programming language. And like any tool, they have gotchas, weird concepts, and so on.Indeed it's nothing hard to learn but there is a learning curve. E.g. knowing which model has which capabilities, and figuring out how to best manage context, permissions, worktrees, etc. There isn't one "right" way to use it but there are more efficient ways and less efficient ways.
by est31
7/28/2026 at 11:53:11 PM
These are the kinds of prompts you can get away with using when your token budget is unlimited.by jameshart
7/28/2026 at 11:19:14 PM
Alternatively, Anthropic employees have basically unlimited token / model usage compared to you and I.Focusing on a better prompt is likely to get to the correct result faster than incomplete prompts and lots of "no change this ..." replies.
Also, I've heard anecdotally that LLMs will underweight the earliest prompt text once context gets too long, so reminding the LLM of the most important aspects of the prompt seems to be perhaps valuable and certainly what lots of humans attempt.
by thephyber
7/28/2026 at 10:32:32 PM
In toying with VS Code or other 'agent harnesses' I'm always annoyed to find very long verbose system prompts "You are CoPilot. You are an expert. You can do anything you put your mind to..." and on and on.The token cost is amortized for longer conversations, but I find it bothersome that there's all this implicit instruction I didn't write or am now obligated to understand.
I make a custom agent prompt with "Defer to the user." and little else.
by mw888
7/29/2026 at 5:19:15 AM
I suspect that kind of prompt is vestigial of an early LLM marketing strategy. It wants to make the LLM seem like a trainable consciousness.by Exoristos
7/28/2026 at 9:46:22 PM
"prompt engineering" in general just boggles my mind. It is amazing how all of this investment has just created software that doesn't follow instructions well.by AsyncBanana
7/29/2026 at 6:32:43 AM
It can follow instructions well. Just give it a spec in a formal, well defined language. runnable language and some reinforcement learning.It can also handle vague stuff.
That's certainly more powerful than a regular computer language.
by petra
7/28/2026 at 11:31:44 PM
you're not wrong. there is a part to this that does feel like a devolution of engineering when we're just asking the computer really really nicely to do the thing we want.on the otherhand, LLMs are a really easy way to get results that are previously fairly difficult. While i was tooking dinner last night I built a tool that turned movie puns like "the podchowski casters" into an actual director, using llms. it wasn't that hard.
by madeofpalk
7/28/2026 at 11:57:48 PM
It's a tiny fraction of the amount of work it takes to get people to build software to specifications. There is an entire professional discipline dedicated to this, and we're here just giving a name to the bucket of tools you use to get LLMs to do some of the same things.by tptacek
7/28/2026 at 10:24:24 PM
idk, its continued attempts at writing down in detail the processes and culture your setup wants to haveits not really a loss to try the writing and at worst you have a better idea of what it is that you want
by 8note
7/29/2026 at 2:16:19 PM
True. People arguing over prompts is akin to people arguing over which way to pull the lever on a slot machine.by uncivilized
7/28/2026 at 7:51:57 PM
It's counter to what sci-fi taught us using AI would be like. We never thought we'd have to feed it words of encouragement, we expected it to act more mechanically, like the computer interfaces we have been using, but here we are. It's kind of quaint, and kind of endearing.by qingcharles
7/28/2026 at 8:07:09 PM
Been watching the wrong sci-fi :). Star Trek had both AI modes as primary characters, in form of the ship's computer, and Data (TNG) / the Doctor (VOY). LLMs are actually great at acting as both, but I don't believe people thought much about what is required to make the "simpler" interaction mode of the ship's computer to work.Or what would make automatic doors work like on Star Trek and not in real life.
The answer is: the system must obviously see much more than your prompt. It must have continuous awareness of you and what you're doing, so it can understand intent behind your short request (or action, like approaching the doors vs. passing by them) and "do what you mean" instead of act like regular computers today.
by TeMPOraL
7/28/2026 at 9:21:14 PM
C-3PO was neurotic and needed lots of reassurance.by kridsdale1
7/28/2026 at 11:28:43 PM
This feels like a subtle attempt to start an argument about Star Wars being sci-fi or not.by dymk
7/28/2026 at 10:03:29 PM
Funnily enough, I grew tired of having to do that myself and sort of automated it by triggering calls to the same (or smarter) model, with the recent agent actions, turns, and outputs, and the user’s last n and first x messages.Two triggers: random and some half-reliable spiral / loop detection.
The spined off has instructions to check what the agent is doing, compare it to what it’s supposed to do, and either offer suggestions, refocus it, or do nothing. And its response then gets injected in the agent’s context.
Not perfect, but surprisingly effective for such a simple thing.
by ElFitz
7/29/2026 at 5:32:36 AM
Can you explain how you piped recent agent actions/turns/outputs? I was looking into this yesterday and tried playing around with streaming json, including hooks, but i (really Claude) would need to write a parser (prob with jq) to filter the noise. Was thinking we tail -f that and select whatever we care about. Kind of an observer to catch such spiraling.by matltc
7/28/2026 at 7:46:23 PM
Yeah, in fact you can actually make the model perform worst. You should allow the model to "think for itself" instead of pushing your reasoning into the prompt. You should give it simple prompt and steer it along the way.Skills, CLAUDE.md/AGENTS.md should only ever be used if the model struggle at something or doesn't know how to use something. Vast majority of project should never need a skill or CLAUDE.md. If you writing React apps you don't need these.
Give a LLM a bash tool and a prompt and it will outperform your complex setup with skills and tools.
by impulser_
7/28/2026 at 9:18:21 PM
You need agents.md and similar for indications about stuff that is not in the code itself. There are plenty of use cases for that, the alternative is have the LLM guess the most probable solution, which may be correct but may also be wrong.by gbalduzzi
7/28/2026 at 9:36:35 PM
The only repos I find skills particularly useful for are in small languages with useful new tools. For elixir I have some tools pointing to cicada[1] for code search because it's better than grep and meaningfully reduces churn.by ch4s3
7/28/2026 at 8:39:43 PM
No, we still need CLAUDE.md to override bad system prompt goals. The system prompt goes for the simple fast solution, no error handling, no hardening, no abstractions, but overly verbose comments. Vast amount of people need to override this AI slop.by rurban
7/28/2026 at 8:49:39 PM
Never once had to do that, fwiw.by dboreham
7/28/2026 at 9:34:43 PM
You'll get better code if you doby rurban
7/29/2026 at 9:38:32 AM
i use it primarily to enforce my personal conventions that are not super commonly followed in the wild. structure of comments at the top of .h , structure of bibliography in .tex, etc etc things that i would otherwise have to repeat periodically.by coderatlarge
7/29/2026 at 12:28:00 AM
[flagged]by ipgleg
7/29/2026 at 1:42:12 AM
With smarter models, Anthropic recommends laying off on giving it too much precise hand-holding, too. Early r/promptengineering had a bunch of the craziest prompts that usually did almost nothing or nothing at all. The subreddit turned into a place where every post was trying to sell some vibe-coded website "product."Context management is still important, though. If you get to a certain amount of context, things start performing really badly.
by tedbradley
7/29/2026 at 5:44:38 AM
Prompt engineering was deprecated around the time Opus-/Codex-class models dropped imo. Replaced by skills up until about opus 4.5/6 dropped. Pinned model to Opus 4.6 slug in ENV.ANTHROPIC_MODEL, disabled the adaptive thinking thing, and saw my skills start causing degradationOnly ones I use today are for very specific quirks (eg wiredtiger/mongodb 8+ incompatible with ext4/Linux 6.19+ specifically causing segfaults. Have a 20 line mongo skill that says as much. Pinned docker container to mongo 7, can prob delete it now)
I spent a few days reading up on the docs for these things, hook lifecycles, tried writing a few, but they never work as documented, or the documentation changes so frequently that whatever you built is deprecated by the time you get it humming.
Now if I have some non-trivial unit of work, I basically iterate on spec in plan mode then put it on auto and let it rip. Way better results with Fable. jury out on Opus 5, but no regression like 4.7/8
Usually it's just echo "do this lil thing then pr closing issue 123" --model sonnet --effort low. Works well enough, sonnet 5 low is a workhorse and quite resourceful in a good way when things go sideways; doesn't cheat its way out IME
by matltc
7/29/2026 at 6:34:56 AM
They probably took our skills and reuse them. That's why skills do not matter anymore.by petra
7/28/2026 at 9:52:10 PM
vibe typing the mumble prompts?> we anthropig fire employes makr company run no mistkaes
by avadodin
7/29/2026 at 8:56:07 AM
Keep in mind for Anthropic the goal for them isn't necessarily to solve a problem but to demonstrate/measure the innate capabilities of their model. Many results would be a lot less interesting/impressive for an LLM to accomplish if researchers smuggled in key premises or ideas within their prompt.by Infinity315
7/29/2026 at 8:06:42 AM
That's reassuring, it's exactly how I've always done LLM. It's fine, as long as the gist of what you mean is there you can be real lazy when typing. And I've always been on the cheapest of plans.by phreack
7/29/2026 at 2:23:01 AM
The difference is that Anthropic engineers have infinite tokens to throw at these problems for free. The rest of us do not and that's where optimizations in how the coding harness is used likely helps the most.by prettyblocks
7/29/2026 at 12:31:41 AM
Is there a non-math example of how a genius prompts? RE: Tao’s Jacobian Conjecture chat https://news.ycombinator.com/item?id=49010345by Barbing
7/29/2026 at 1:54:12 AM
Contrast that interactive, misspelled prompting, which I can relate to, against the clear, but intimidating, prompting they published with that theorem proof the other day.by hughw
7/28/2026 at 9:15:26 PM
To quote - what I found to be - an absolute zinger from another trending thread on here just 6 hours ago:> Typical users run software written by atypical users.
https://news.ycombinator.com/item?id=49084936
This extends to everything. Anthropic has a few thousand engineers, but millions of (also engineer) users. Entire business can be built on niches that are at most a few week pet project for a team there, that can inevitably and significantly outperform them, despite being the people behind the thing.
I'm sure I'm not the only one here who jumped into this whole agentic stuff, built some tooling to make things comfy, only to see that tooling all be increasingly introduced as prim and proper features in the various harnesses weeks later.
by perching_aix
7/29/2026 at 5:50:06 AM
Totally. Ralph wiggum was added to every big shop's stdlib (harness?) just a couple weeks after it dropped. That simple iterative workflow basically underpins all of the notable/novel achievements of agentic coding or whatever.I'm sure many more examples in the "official marketplaces" for mcp/skills/what have you
by matltc
7/28/2026 at 6:48:47 PM
> we made a machine that writes with perfect grammar, so that we can continue to write half-assed junkby neonstatic
7/28/2026 at 6:55:07 PM
claude's grammar has gotten significantly worse with latest versions. it no longer writes perfectly at allby postflopclarity
7/28/2026 at 7:03:32 PM
It's called being more human-like lol XDby sudo_cowsay
7/28/2026 at 7:15:12 PM
To be fair> Importantly, this is just one of many (autonomous) sessions where Claude worked on discovering new ideas. Many sessions resulted in no new discoveries; other follow-up sessions improved on the insight developed in this one. This document was produced by having Claude rewrite the chain of thought to include more detail to make it easier to read.
by porridgeraisin
7/29/2026 at 12:27:28 AM
[flagged]by ipgleg
7/28/2026 at 6:55:43 PM
Having spent a lot of time over the last months writing both refined, structured, and grammatically perfect prompts, as well as exact equivalents of the ones you quoted (modulo subject of the prompt), I have three observations:1. I'm glad the second kind works too;
2. First kind is where I find my overall throughput to be literally constrained by my typing speed;
3. Most importantly: those prompts you quote aren't just "half-assed" like sibling comment states; they're different. The style of writing, and the typos, capture emotional valence. It's a signal.
Again, I too produce such prompts - including the exact same typos - when under pressure and irritated by the direction the model is taking.
by TeMPOraL
7/28/2026 at 7:06:05 PM
Have you tried using Wispr or Willow (or any one of a thousand alternatives?)A little odd at first but absolutely amazing for the purpose of piling context into an LLM.
by estearum
7/28/2026 at 7:40:09 PM
It's so bizarre to me that people want to do this.Can't you type faster than you speak? Doesn't your speaking inhibit your thinking? Aren't you self-conscious talking out loud? How are our experiences so different?
by jstanley
7/28/2026 at 9:06:25 PM
> Can't you type faster than you speak? Doesn't your speaking inhibit your thinking?For me personally: no, I speak faster than I type; and speaking actually helps me get more ideas compared to typing.
(Not sure if that’s due to having no typing speed barrier, or maybe because speaking activates different parts of the brain.)
Once you get over the feeling of self-consciousness, it’s a great way. I even go on short walks sometimes and mumble to my phone to prepare some long prompt. Thinking works even better, when walking outside :-)
by jhogervorst
7/28/2026 at 10:26:16 PM
do you perchance have no inner monologue? its a physical difference in how people think that would affect typing vs talkingby 8note
7/29/2026 at 7:52:12 AM
I do have inner monologue, and in the past, vocalizing it properly and basically talking to myself was a great focus booster. I've been socially conditioned out of doing that though, but I sometimes still do that in form of typing to a text file.Whether via inner monologue or explicit talking to myself, vocalizing mentally or out loud is always faster than typing to me, even though I type rather fast.
Still, that's only a "mid gear" for me. The ultimate state of greatest focus, attention and speed, is wordless flow. Inner monologue shuts off near completely there; I don't need to formulate words in my head to do things, I just feel and do. It's my favorite state to be in, and it's where what I consider my best work has been done, but sadly, I very rarely attain such state.
So: Inner monologue < Talking to myself << Wordless flow
(Funny thing, if you were to record me talking to myself, you'd see pretty much the same thing as in LLM thinking traces - including all the "but wait!" bits. My personal "brain dump" journal looks very much like GPT-4/Deepseek-R1 thinking traces - i.e. back before companies realized thinking traces are great for model distillation, and replaced them with summaries.)
by TeMPOraL
7/28/2026 at 8:16:44 PM
These are all interrelated points and the sibling comment is correct: it's a skill.The key thing with these voice systems is that you do not need to edit anything. You can literally just stream of consciousness into them, no editing, include the backtracking, the live-revisions, etc., and it will actually all produce vastly better context for the LLM than the written thing you took even 30 seconds to edit for clarity or brevity.
I had a very similar disposition towards this idea just 6 months ago. I highly recommend trying it out. The key thing is that you do not need to edit. Just keep talking. Try it for a few weeks!
by estearum
7/28/2026 at 9:15:32 PM
You don't need to edit anything when you are typing either. You don't even need to worry about spelling or typos.by charcircuit
7/28/2026 at 9:30:55 PM
Seems much harder to learn how to write how you never write, versus just learning to speak to a computer the same way you speak to anything else.by estearum
7/28/2026 at 11:18:30 PM
A lot of people on the autism spectrum can have issues with speaking or speaking speed, but have no such barrier necessarily to typing speed.I'd imagine there's a statistically large number of people that meet that criteria on this website.
by esseph
7/28/2026 at 11:46:40 PM
I mean we don't need to do any epidemiological studies here or anything.If someone hasn't tried it, they should. It's probably quite different from how they're expecting, might be great, and costs basically nothing. Try it for a few days and if it doesn't work in your workflow, obviously don't do it.
But I have encountered many many people who raised these exact same arguments against trying it, then tried it, and were hooked within days. Exactly 0% of people I've ever convinced to try it decided it just wasn't for them and went back to typing full-time.
by estearum
7/29/2026 at 2:46:03 AM
The thought of talking drives me insane but you do you, boo-boo :)by esseph
7/29/2026 at 11:56:23 AM
Yes virtually every person I've ever talked to about this had the same initial reactionby estearum
7/28/2026 at 11:46:24 PM
What do you mean how you never write? You can just write what for want to say instead of saying it out loud. It is not a special skill, it's no different than how you write a message, just that you don't hit backspace to go back and correct things.by charcircuit
7/29/2026 at 7:58:07 AM
> it's no different than how you write a message, just that you don't hit backspace to go back and correct things.Yes, that.
If you do that when writing to another person, you come off as blabbering, incoherent moron. Fortunately, very few people do that, because communicating with people who write like they talk is incredibly hard.
I'd worry about trying to do this on purpose; feels like the kind of "learning" that can easily spill over to non-LLM communication and make your life much harder.
There's a middle ground, though.
When shooting IM messages, people sometimes make typps
ypos*
typos**
there's an append-only procedure for fixing that, which I just demonstrated.
Also they don't always finish everything in one message
in fact a nice thing about IMs is being able to not use full sentences
that would work with LLMs, if not for the annoying "feature" that persists in most harnesses:
conversations take turns, and you can just send message after message - you have to wait for LLM to finish.
by TeMPOraL
7/29/2026 at 7:09:11 PM
>I'd worry about trying to do this on purposeYou already have to juggle multiple writing styles between different people and use cases. It is easy to avoid submitting a pure stream of thought if you are writing a formal letter.
>there's an append-only procedure for fixing that, which I just demonstrated.
LLMs can figure out most typos on your own.
>you have to wait for LLM to finish.
I don't think any coding harnesses work like this. They let you send more messages to steer the model while it's working.
by charcircuit
7/28/2026 at 11:50:11 PM
Correct, it's no different from how you normally write, except for the ways in which it is. We agree.by estearum
7/29/2026 at 12:00:37 AM
When you're making a big deal out of it being "much harder" because it's "how you never write" and they're saying that's just "not hitting backspace"? No, you don't agree.by Dylan16807
7/29/2026 at 12:03:25 AM
How frequently do you write in a stream of consciousness and not hit backspace?Maybe give a ballpark estimate of characters typed per week in this manner versus characters typed where you are doing some combination of: 1) thinking about what you're writing before you write it, 2) punctuating and formatting correctly, or 3) correcting your writing output?
Ridiculous proposition. And I type correctly at 110+ wpm.
by estearum
7/29/2026 at 12:06:23 AM
How often I do it doesn't matter because it's such a trivial thing to switch. If you're gonna "try it for a few weeks" the part of you that has to learn the typing-specific parts of that method is about 1% of the difficulty.It's really easy to ignore typos. And the way you have to approach thinking and correcting is the same whether you're typing or voicing.
If you can't just type the way you would just talk, and you find it notably hard, it's you that's being ridiculous.
by Dylan16807
7/29/2026 at 12:08:19 AM
But it's literally not. You already correct yourself and revise your speech in an append-only rolling edit. You do it all day every day for decades.Versus never writing in this way.
Have you tried the voice-based prompting, as I'm describing?
by estearum
7/29/2026 at 12:13:32 AM
"never" schmever. I never ramble unrestrained either. Deciding not to edit at all is a skill either way. If you just want the equivalent of voice in a normal way, you remove backspace and that's it.> Have you tried the voice-based prompting, as I'm describing?
I've never prompted a thing. I can just see your distinction is nonsense. If you think it's hard you're doing it wrong.
And wow I did that post without revising a thing. Wow.
by Dylan16807
7/29/2026 at 12:15:57 AM
Right. So the crux of the issue here is you have no experience with what's being discussed, while I do.Sheesh, imagine thinking you choose not to rewind time and "edit" the speech that has already come out of your mouth lmao.
by estearum
7/29/2026 at 12:16:53 AM
I'm doing it right now you goober! Stop calling it hard!What experience do you insist I'm lacking in something I'm doing right now?
by Dylan16807
7/29/2026 at 12:36:23 AM
Maybe you lost the thread, but this is a conversation about using dictation (specifically modern dictation tools like Whisper derivatives) to prompt coding agents.by estearum
7/29/2026 at 12:57:43 AM
Do you think it suddenly becomes harder to avoid backspace when you're in a different text box?The thing you're claiming is hard, writing exactly the way you would speak, is not hard.
There's also some additional benefit to going with the flow and not thinking about words much before saying them, but that's equally hard with text or voice.
by Dylan16807
7/29/2026 at 1:04:01 AM
You just said like two comments ago you have no experience with this. Not sure why you keep acting like you do.by estearum
7/29/2026 at 1:25:03 AM
I hadn't before. Then I started doing it just to show how easy it was.It doesn't matter what text box you're typing in. The ability to type as you'd speak is easy. Without any extra delays or issues.
I hope you're not trying to argue that typing the same way into an AI prompt is harder than doing it into HN. It's just not hard in any situation. Voice isn't special.
by Dylan16807
7/29/2026 at 1:29:32 AM
You are struggling to hold the thread, I'm afraid. Have a good night!by estearum
7/29/2026 at 1:31:33 AM
I see. You've fallen into some weird pedantry to think what I'm saying isn't relevant to your argument. I hope you figure out my very simple meaning later, have a good night too!by Dylan16807
7/29/2026 at 11:01:08 AM
> You already correct yourself and revise your speech in an append-only rolling edit.No, I think before I speak and say what I planned to say. What do you do, sir?
by jstanley
7/29/2026 at 12:04:56 PM
Cute snark but no you don't, nor does anyone else who speaks to you. People self-repair their speech in 10% to nearly 40% of speech turns. The upper end is for cognitively demanding communication but the lower bound is very normal.Good evidence of my point though on how natural this is. People literally don't even notice it as either the listener or the speaker.
Even when a listener is told specifically to listen for and detect errors or self-repairs in speech, listeners will not even detect 50% to 80% of minor repairs. Your brain literally doesn't even perceive them.
by estearum
7/28/2026 at 7:59:45 PM
My stream of barely-intelligible rambling comes out much faster than I can type, and it's not even close.It's a skill like any other. You start out stuttering and second-guessing yourself, but after a while, you get better at it. And the LLM smooths out the odd mistakes better than you might think.
by arcanemachiner
7/28/2026 at 7:15:51 PM
Voice dictation tools? Not really. Tried various dictation tools interacting on the phone, but the quality varies, and resulting prompts are very much not like I would write them.My limiting factor is that 99% of the day I'm around people - either at work, or at home with wife and kids. There's almost no point during the day I could feel comfortable talking at an AI, and even if I stay up late, then talking risks waking the kids up.
Can't wait for some kind of subvocalization microphones to become a thing.
by TeMPOraL
7/28/2026 at 7:23:17 PM
Get a noise machine for wife and kids bedrooms. I talk to friends late at night and my deep voice carries through walls. Works great.I have zero desire to talk to an ai though, that was cool for about 20 minutes on my pentium 1 acer computer. Hasn’t been since. Old competent non paid Alexa was good for timers as well, the rest of the platforms a turd, nice timers though.
by elictronic
7/28/2026 at 7:55:49 PM
> that was cool for about 20 minutes on my pentium 1 acer computer. Hasn’t been since.Oh back in the days, i.e. 20 years ago, I had a better voice control system than anything afforded by Alexa or Apple or others, using MS Speech API in its custom constrained grammar mode, plus some bootleg samples of Star Trek's computer voice + a sub-dollar microphone soldered to a long cable and hung on the side of the wardrobe.
The trick that made it work? Microsoft Speech API actually let you train voice to your own text corpus. I'd prepare all combinations of commands I want to issue, print it out, and train it over a dozen short sessions in several locations of the room and at different ambient noise levels (from silent through various genres of music playing at various loudness). End result was more reliable and had better voice-mismatch rejection than any current system I've tried.
Oh, and the real kicker? This all worked fully locally; this was before cloud was even a thing. Turns out you don't actually need cloud for reliable voice control. Nor that much processing power; PC I had then was relatively budget even for 2006.
by TeMPOraL
7/28/2026 at 8:19:12 PM
I highly recommend getting a boom mic that you can keep right up against your mouth and literally whisper into. Take a few weeks just doing stream-of-consciousness prompting into it like this. Don't worry about editing or backtracking or revisions. It's really amazing how well the AI voice recognition → coding agent workflow works.by estearum