For those starting out using Claude Code it gives a structured way to get things done bypassing the time/energy needed to “hit upon something that several of us have evolved to naturally”.
Anyone who spends some time with these tools (and doesn't black out from smashing their head against their desk) is going to find substantial benefit in planning with clarity.
It was #6 in Boris's run-down: https://news.ycombinator.com/item?id=46470017
So, yes, I'm glad that people write things out and share. But I'd prefer that they not lead with "hey folks, I have news: we should *slice* our bread!"
#6 is about using plan mode whereas the author says "The built-in plan mode sucks".
The author's post is much more than just "planning with clarity".
I sometimes reference some of them to build context, e.g. after few unsuccessful tries to implement something, so that Claude doesn't try the same thing again.
Not much more, though.
It introduces "research", which is the central topic of LLMs since they first arrived. I mean, LLMs coined the term "hallucination", and turned grounding into a key concept.
In the past, building up context was thought to be the right way to approach LLM-assisted coding, but that concept is dead and proven to be a mistake, like discussing the best way to force a round peg through the square hole, but piling up expensive prompts to try to bridge the gap. Nowadays it's widely understood that it's far more effective and way cheaper to just refactor and rearchitect apps so that their structure is unsurprising and thus grounding issues are no longer a problem.
And planning mode. Each and every single LLM-assisted coding tool built their support for planning as the central flow and one that explicitly features iterations and manual updates of their planning step. What's novel about the blog post?
Seriously? Provide context with a prompt file, prepare a plan in plan mode, and then execute the plan? You get more detailed descriptions of this if you read the introductory how-to guides of tools such as Copilot.
There's nothing revolutionary, but yes, it's a workflow that's quite different from other posts I've seen, and especially from Boris' thread that was mentioned which is more like a collection of tips.
Having LLMs write their prompt files was something that became a thing the moment prompt files became a thing.
> then the plan and iterate on it by editing the plan file, then adding the todo list, then doing the implementation, and doing all that in a single conversation (instead of clearing contexts).
That's literally what planning mode is.
Do yourself a favor and read the announcement of support for planning mode in Visual Studio. Visual Studio code supported it months before.
https://devblogs.microsoft.com/visualstudio/introducing-plan...
I don't care about Visual Studio, I don't use it, but the page you've linked seems to describe yet another workflow (not very detailed).
That's obvious by now, and the reason why all mainstream code assistants now offer planning mode as a central feature of their products.
It was baffling to read the blogger making claims about what "most people" do when anyone using code assistants already do it. I mean, the so called frontier models are very expensive and time-consuming to run. It's a very natural pressure to make each run count. Why on earth would anyone presume people don't put some thought into those runs?
Personally I have been using a similar flow for almost 3 years now, tailored for my needs. Everybody who uses AI for coding eventually gravitates towards a similar pattern because it works quite well (for all IDEs, CLIs, TUIs)
It is to me, because it indicates the author didn't care about the topic. The only thing they cared about is to write an "insightful" article about using llms. Hence this whole thing is basically linked-in resume improvement slop.
Not worth interacting with, imo
Also, it's not insightful whatsoever. It's basically a retelling of other articles around the time Claude code was released to the public (March-August 2025)
However I do find the standard out-of-the-box style very grating. Call it faux-chummy linkedin corporate workslop style.
Why don't people give the llm a steer on style? Either based on your personal style or at least on a writer whose style you admire. That should be easier.
> Because they think this is good writing. You can’t correct what you don’t have taste for.
I have to disagree about:
> Most software engineers think that reading books means reading NYT non-fiction bestsellers.
There's a lot of scifi and fantasy in nerd circles, too. Douglas Adams, Terry Pratchett, Vernor Vinge, Charlie Stross, Iain M Banks, Arthur C Clarke, and so on.
But simply enjoying good writing is not enough to fully get what makes writing good. Even writing is not itself enough to get such a taste: thinking of Arthur C Clarke, I've just finished 3001, and at the end Clarke gives thanks to his editors, noting his own experience as an editor meant he held a higher regard for editors than many writers seemed to. Stross has, likewise, blogged about how writing a manuscript is only the first half of writing a book, because then you need to edit the thing.
Slop looks reasonable on the surface, and requires orders of magnitude more effort to evaluate than to produce. It’s produced once, but the process has to be repeated for every single reader.
Disregarding content that smells like AI becomes an extremely tempting early filtering mechanism to separate signal from noise - the reader’s time is valuable.
I think your sentence should have been "people who use ai do so to mostly rewrite or clean up content", but even then I'd question the statistical truth behind that claim.
Personally, seeing something written by AI means that the person who wrote it did so just for looks and not for substance. Claiming to be a great author requires both penmanship and communication skills, and delegating one or either of them to a large language model inherently makes you less than that.
However, when the point is just the contents of the paragraph(s) and nothing more then I don't care who or what wrote it. An example is the result of a research, because I'd certainly won't care about the prose or effort given to write the thesis but more on the results (is this about curing cancer now and forever? If yes, no one cares if it's written with AI).
With that being said, there's still that I get anywhere close to understanding the author behind the thoughts and opinions. I believe the way someone writes hints to the way they think and act. In that sense, using LLM's to rewrite something to make it sound more professional than what you would actually talk in appropriate contexts makes it hard for me to judge someone's character, professionalism, and mannerisms. Almost feels like they're trying to mask part of themselves. Perhaps they lack confidence in their ability to sound professional and convincing?
It's much more efficient and intentional for the writer to put the time into doing the condensing and organizing once, and review and proofread it to make sure it's what they mean, than to just lazily spam every human they want to read it with the raw prompt, so every recipient has to pay for their own AI to perform that task like a slot machine, producing random results not reviewed and approved by the author as their intended message.
Is that really how you want Hacker News discussions and your work email to be, walls of unorganized unfiltered text prompts nobody including yourself wants to take the time to read? Then step aside, hold my beer!
Or do you prefer I should call you on the phone and ramble on for hours in an unedited meandering stream of thought about what I intended to write?
Github repo or it didn't happen. Let's go.
Unfortunately, there's a lot of people trying to content-farm with LLMs; this means that whatever style they default to, is automatically suspect of being a slice of "dead internet" rather than some new human discovery.
I won't rule out the possibility that even LLMs, let alone other AI, can help with new discoveries, but they are definitely better at writing persuasively than they are at being inventive, which means I am forced to use "looks like LLM" as proxy for both "content farm" and "propaganda which may work on me", even though some percentage of this output won't even be LLM and some percentage of what is may even be both useful and novel.
If your "content" smells like AI, I'm going to use _my_ AI to condense the content for me. I'm not wasting my time on overly verbose AI "cleaned" content.
Write like a human, have a blog with an RSS feed and I'll most likely subscribe to it.
However, I use Claude for a few things:
1. Research buddy, having conversations about technical approaches, surveying the research landscape.
2. Document clarity and consistency evaluator. I don't take edits, but I do take notes.
3. Spelling/grammar checker. It's better at this than regular spellcheck, due to its handling of words introduced in a document (e.g., proper names) and its understanding of various writing styles (e.g., comma inside or outside of quotes, one space or two after a period?)
Every time I get into a one hour meeting to see a messy, unclear, almost certainly heavily AI generated document being presented to 12 people, I spend at least thirty seconds reminding the team that 2-3 hours saved using AI to write has cost 11+ person-hours of time having others read and discuss unclear thoughts.
I will note that some folks actually put in the time to guide AI sufficiently to write meaningfully instructive documents. The part that people miss is that the clarity of thinking, not the word count, is what is required.
This is clearly a standard AI exposition:
LLM's are like unreliable interns with boundless energy. They make silly mistakes, wander into annoying structural traps, and have to be unwound if left to their own devices. It's like the genie that almost pathologically misinterprets your wishes.
It's not just misleading — it's lazy. And honestly? That doesn't vibe with me.
[/s obviously]