11 ms·

Two kinds of AI users are emerging

355 points by martinald 8mo ago

simmerup 8mo ago
Terrifying that people are creating financial models with AI when they don’t have the skills to verify the model does what they expect
- fatheranton 8mo ago
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- martinald 8mo ago
  They have an excel sheet next to it - they can test it against that. Plus they can ask questions if something seems off and have it explain the code.
  - karlgkk 8mo ago
    [flagged]
    - yomismoaqui 8mo ago
      You would be surprised at the volume of money made by businesses supported by Excel.
      - martinald 8mo ago
        Yes. I suspect there are thousands of Excel files that "process" >$1bn/yr out there.
        irishcoffee 8mo ago
        Allow me to introduce to you: ACH. It is truly fascinating.
  - AlotOfReading 8mo ago
    I'm not sure being able to verify that it's vaguely correct really solves the issue. Consider how many edge cases inhabit a "30 sheet, mind-numbingly complicated" Excel document. Verifying equivalence sounds nontrivial, to put it mildly.
    - Dylan16807 8mo ago
      Consider how many edge cases it misses. Equivalence probably shouldn't be the top priority here.
      - Nevermark 8mo ago
        Equivalence here would definitely be the worst test, except for all the alternatives.
    - Draiken 8mo ago
      They don't care. This is clearly someone looking to score points and impress with the AI magic trick. The best part is that they can say the AI will get some stuff wrong, they knew that, and it's not their fault when it breaks. Or more likely, it'll break in subtle ways, nobody will ever notice and the consequences won't be traced back to this. YOLO!
  - lmm 8mo ago
    > They have an excel sheet next to it - they can test it against that. It used to be that we'd fix the copy-paste bugs in the excel sheet when we converted it to a proper model, good to know that we'll now preserve them forever.
- nebula8804 8mo ago
  All we need is one major crash caused by AI to scare the capital owners. Then maybe us white collar workers can breath a bit for at least another few more years(maybe a decade+).
  - danielbln 8mo ago
    A decade+ is wishful copium.
    - nebula8804 8mo ago
      Well I did say "maybe". It all depends on how badly they get burned. A crash will hopefully scare enough of them from trying for a while.
  - onion2k 8mo ago
    All we need is one major crash caused by AI to scare the capital owners. All the previous human-driven crashes didn't change anything about capital owners' approach to money, so why would an AI-driven crash change things?
    - leptons 8mo ago
      The scapegoating is different. Using an LLM makes them more culpable for the failure, because they should have known better than to use a tech that is well known to systematically lie.
    - ktzar 8mo ago
      because we have an alternative that we humans can fix. The problem with AI is that it creates without leaving a trace of understanding.
  - pizzafeelsright 8mo ago
    Most of the large outages at Meta in the past 10 years were related to early AI automation.
- mkoubaa 8mo ago
  It's not terrifying at all, some shops will fail and some will succeed and in the aggregate it'll be no different for the rest of us
- myfakebadcode 8mo ago
  I’m trying to learn rust coming from python (for fun). I use various LLM for python and see it stumble. It is a beautiful experience to realize wtf you don’t know and how far over their skis so many will get trusting AI. The idea of deploying a rust project at my level of ability with an AI at the helm is is terrifying.
- derrida 8mo ago
  Business as usual.
  - deleted 8mo ago
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- taneq 8mo ago
  If they have the skills to verify the Excel model then they can apply the same approach to the numbers produced by the AI-generated model, even if they can’t inspect it directly. In my experience a lot of Excel models aren’t really tested, just checked a bit and them deemed correct.
- chrisjj 8mo ago
  That will get less terrifying when they move on to medical.
- riskable 8mo ago
  I work for a huge bank: The actual terrifying thing is that these financial models semi-technical management are creating in Excel are actually relied upon in the first place. If you convert bullshit from Excel to Python it's still bullshit. There's a reason why Claude can one-shot it and no one questions the result :D
  - theshrike79 8mo ago
    The Python bullshit at least can be unit tested bit by bit and easily improved. Nobody will see that on sheet 27 cell FG456 is actually a static number that Brian typoed in there in 2019 and not a formula.
- pizzafeelsright 8mo ago
  Someone recently had AI create a trading bot and it returns 131% on every transaction over a 30 day period - do you really think they care about code quality or ability to verify the math?
  - simmerup 8mo ago
    ANd I have a bridge to sell you in London
    - pizzafeelsright 8mo ago
      Someone bought that bridge and it stands in Arizona.
- riscii68 8mo ago
  Yep. And I think many are too focused on just the pure ability to build models now, when in reality a model is at its core a set of assumptions. Using models you don't understand, didn't build, and barely reviewed amplifies the magnitude of any assumption error, imo.
superkuh 8mo ago
The argument seems to be that having a corporation restrict your ability to present arbitrary text directly to the model and only being able to go through their abstract interface which will integrate your text into theirs (hopefully) is more productive than fully controlling the input text to a model. I don't think that's true generally. I think it can be true when you're talking about non-technical users like the article is.
- majormajor 8mo ago
  The use of specialization of interfaces is apparent if you compare Photoshop with Gemini Pro/Nano Banana for targeted image editing. I can select exactly where I want changes and have targeted element removal in Photoshop. If I submit the image and try to describe my desired changes textually, I get less easily-controllable output. (And I might still get scrambled text, for instance, in parts of the image that it didn't even need to touch.) I think this sort of task-specific specialization will have a long future, hard to imagine pure-text once again being the dominant information transfer method for 90% of the things we do with computers after 40 years of building specialized non-text interfaces.
  - fdsf2 8mo ago
    It behooves me that Gemini et al dont have these standard video editing tools. Do the engineers seriously think prompting by text is the way people want videos to be generated? Nope. People want to customise. E.g. Check out capcut in the context of social media. Ive been trying to create a quick and dirty marketing promo via an LLM to visualise how a product will fit into the world of people - it is incredibly painful to 'hope and pray' that by refining the prompt via text you can make slight adjustments come through. The models are good enough if you are half-decent at prompting and have some patience. But given the amount invested, I would argue they are pretty disappointing. Ive had to chunk the marketing promo into almost a frame-by-frame play to make it somewhat work.
    - suprstarrd 8mo ago
      Speaking as someone who doesn't like the idea of AI art so take my words with a grain of salt, but my theory is that this input method exclusivity is intentional on their part, for exactly the reason you want the change. If you only let people making AI art communicate what they want through text or reference attachments (the latter of which they usually won't have), then they have to spend time figuring out how to put it into words. It IS painful to ask for those refinements, because any human would clearly understands it. In the end, those people get to say that they spent hours, days, or weeks refining "their prompt" to get a consistent and somewhat-okay looking image; the engineers get to train their AI to better understand the context of what someone is saying; and all the while the company gets to further legitimize a false art form.
Havoc 8mo ago
The copilot button in excel at my work can’t access the excel file of the window it’s in. As in “what’s in cell A1” and it says I can’t read this file. Not even sure what the point is then frankly. I’m happily vibe coding at work but yeah article is right. MS has enterprise market share by default not by merit. Stunning contrast between what’s possible and what’s happening in big corp
- deleted 8mo ago
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- cmrdporcupine 8mo ago
  Meanwhile the people I know who work at Microsoft say there's a constant whip-cracking to connect everything they're doing to "AI" and prove that's what they're doing.
  - PunchyHamster 8mo ago
    so whole company decided to collectively half-ass it so managers fuck off ? :D
- bwat49 8mo ago
  yeah I actually use AI a lot, but copilot is... useless. When microsoft adds copilot to their various apps they don't seem to put any thought/effort behind it beyond sticking a copilot button somewhere. And if the copilot button does nothing but open a chat window without any real integration with the app, what the hell is the point of that when there's already a copilot button in the windows taskbar?
  - chrisjj 8mo ago
    You have overestimated the intelligence of the target audience :)
- deleted 8mo ago
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- Havoc 8mo ago
s-lambert 8mo ago
I don't see a divergence, from what I can tell a lot of people have only just started using agents in the past 3-4 months when they got good enough that it was hard to say otherwise. Then there's stuff like MCP, which never seemed good and was entirely driven by people who talked more about it than used it. There also used to be stuff like langchain or vector databases that nobody talks about anymore, maybe they're still used but they're not trendy anymore. It seems way too soon to really narrow down any kind of trends after a few months. Most people aren't breathlessly following the next twitter trend, give it at least a year. Nobody is really going to be left behind if they pick up agents now instead of 3 months ago.
- neom 8mo ago
  Not sure how much falling behind there is even going to be, I'm an old school linux type with D- programming skills, yet getting going building things has been ridiculously easy. The swarms thing makes is so fast. I've churned 2 small but tested apps out in 2 weekends just chatting with claude code, the only thing I had to do was configure the servers.
- Gigachad 8mo ago
  The only people I see talking about MCP are managers who don't do anything but read linked in posts and haven't touched a text editor in years if ever.
- _1tan 8mo ago
  What‘s used instead of MCP in reality? Just REST or other existing API things?
  - senordevnyc 8mo ago
    Yeah, I suspect the people railing against MCP don’t actually use agents much at all. MCP is super useful for giving your agent access to tools. The main alternative is CLI tools, if they exist, but they don’t always, or it’s just more awkward than a well-designed MCP. I let my agent use the GitHub CLI, but I also have MCPs for remote database access and bugsnag access, so they can debug issues on prod more easily.
defrost 8mo ago
The "upside" description: On the other you have a non-technical executive who's got his head round Claude Code and can run e.g. Python locally. I helped one recently almost one-shot converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code. Once the model is in Python, you effectively have a data science team in your pocket with Claude Code. You can easily run Monte Carlo simulations, pull external data sources as inputs, build web dashboards and have Claude Code work with you to really integrate weaknesses in your model (or business). It's a pretty magical experience watching someone realise they have so much power at their fingertips, without having to grind away for hours/days in Excel. almost makes me physically sick. I've a reasonably intense math background corrupted by application to geophysics and implementing real world numerical applications. To be fair, this statement alone: * 30 sheet mind numbingly complicated Excel financial model makes my skin crawl and invokes a flight reflex. Still, I'll concede that a Claude Code conversion to Python of a 30 sheet Excel financial model is unlikely to be significantly worse than the original.
- decimalenough 8mo ago
  I'm almost certain it will be significantly worse. The Excel sheet will have been tuned over the years by people who knew exactly what it was doing and fixed countless bugs along the way. The Claude Code copy will be a simulacrum that may behave the same way with some inputs, but is likely to get many of edge cases wrong, and, when you're talking about 30 sheets of Excel, there will be many, many of these sharp edges.
  - defrost 8mo ago
    I won't disagree - I suffered from insufficient damning praise in my last sentence above. IMHO, earned through years of bleeding eyeballs, the first will be riddled with subtle edge cases curiously patched and fettled such that it'll limp through to the desired goal .. mostly. The automated AI assisted transcoding will be ... interesting.
  - holoduke 8mo ago
    My assumption is that with the right approach you can create a much much better and reliable program using only Claude code. You are referring to yolo coding results
ed_mercer 8mo ago
> Microsoft itself is rolling out Claude Code to internal teams Seems like Nadella is having his Baller moment
- fdsf2 8mo ago
  Nothing but ego frankly. Apple had no problem settling for a small market share back in the day... look where they are now. It didnt come from make-believe and fantasy scenarios of the future based on an unpredictable technology.
  - leptons 8mo ago
    >look where they are now. Still with a small market share. They only figured out how to extort the maximum amount of money from a smaller user base, and app developers, really anyone they can.
    - Mentlo 8mo ago
      I guess a quarter of the smartphone market (leader), half of the tablet market (leader) and a tenth of the global pc market (2nd place) / 6th of the usa/europe market (2nd place) being a small market share is a take.
      - leptons 8mo ago
        >a quarter of the smartphone market (leader) Android is by far the leader. >half of the tablet market (leader) Half does not make someone a "leader" >a tenth of the global pc market (2nd place) 2nd place?? They're last place, by a wide margin. >6th of the usa/europe market (2nd place) Also last place. I guess the reality distortion field is still alive and well.
        Mentlo 8mo ago
        Os x has a 10% market share, which is 2nd after Windows, but i agree on that one i conflated terms. I couldn’t quickly find device manufacturers stats. If wiki is to be trusted - apple is 4th, with share not far behind dell [1]. If half doesn’t make you leader what does? Maybe you should elaborate your definition of leader? For me it’s “has the highest market share”. And in that definition half is necessarily true. It’s funny that for PC’s you went for manufacturers (apple is 4th) but for mobile you went for OS (Apple is 2nd). On mobile devices, Apple is 1st, having double market share compared to 2nd place (samsung). The need to paint Apple as purely a marketing company always fascinated me. Marketing is a big part of who they are though. [1] https://en.wikipedia.org/wiki/Market_share_of_personal_computer_vendors https://en.wikipedia.org/wiki/Market_share_of_personal_compu...
decimalenough 8mo ago
> I helped one recently almost one-shot[3] converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code. I'm sure Claude Code will happily one-shot that conversion. It's also virtually guaranteed to have messed up vital parts of the original logic in the process.
- linsomniac 8mo ago
  It depends on how easily testable the Excel is. If Claude has the ability to run both the Excel and the Python with different inputs, and check the outputs, it's stunningly likely to be able to one-shot it.
  - martinald 8mo ago
    That's exactly what it did (author here).
    - majormajor 8mo ago
      I'm having trouble reconciling "30 sheet mind numbingly complicated Excel financial model" and "Two or three prompts got it there, using plan mode to figure out the structure of the Excel sheet, then prompting to implement it. It even added unit tests to the Python model itself, which I was impressed with!" "1 or 2 plan mode prompts" to fully describe a 30-sheet complicated doc suggests a massively higher level of granularity than Opus initial plans on existing codebases give me or a less-than-expected level of Excel craziness. And the tooling harnesses have been telling the models to add testing to things they make for months now, so why's that impressive or suprising?
      - martinald 8mo ago
        No it didn't make a giant plan of every detail. It made a plan of the core concepts and then when it was in implementation mode it kept checking the excel file to get more info. It took around ~30 mins in implementation mode to build it. I was impressed because the prompt didn't ask it to do that. It doesn't normally add tests for me without asking, YMMV.
danpalmer 8mo ago
I've noticed a huge gap between AI use on greenfield projects and brownfield projects. The first day of working on a greenfield project I can accomplish a week of work. But the second day I can accomplish a few days of work. By the end of the first week I'm getting a 20% productivity gain. I think AI is just allowing everyone to speed-run the innovator's dilemma. Anyone can create a small version of anything, while big orgs will struggle to move quickly as before. The interesting bit is going to be whether we see AI being used in maturing those small systems into big complex ones that account for the edge cases, meet all the requirements, scale as needed, etc. That's hard for humans to do, and particularly while still moving. I've not see any of this from AI yet outside of either a) very directed small changes to large complex systems, or b) plugins/extensions/etc along a well define set of rails.
- data-ottawa 8mo ago
  It’s fantastic to be able to prototype small to medium complexity projects, figure what architects work and don’t, then build on a stable foundation. That’s what I’ve been doing lately, and it really helps get a clean architecture at the end.
  - johnrob 8mo ago
    I’ve done this in pure Python for a long time. Single file prototype that can mostly function from the command line. The process helps me understand all the sub problems and how they relate to each other. Best example is when you realize behaviors X, Y, and Z have so much in common that it makes sense to have a single component that takes a parameter to specify which behavior to perform. It’s possible that already practicing this is why I feel slightly “meh” compared to others regarding GenAI.
- EnPissant 8mo ago
  I have experienced much of the opposite. With an established code base to copy patterns from, AI can generate code that needs a lot less iteration to clean up than on green fields projects.
  - 8mo ago
smuhakg 8mo ago
> On one hand, you have Microsoft's (awful) Copilot integration for Excel (in fairness, the Gemini integration in Google Sheets is also bad). So you can imagine financial directors trying to use it and it making a complete mess of the most simple tasks and never touching it again. Microsoft has spent 30 years designing the most contrived XML-based format for Excel/Word/Powerpoint documents, so that it cannot be parsed except by very complicated bespoke applications with hundreds of developers involved. Now, it's impossible to export any of those documents into plain text that an LLM can understand, and Microsoft Copilot literally doesn't work no matter how much money they throw at it. My company is now migrating Word documents to Markdown because they're seeing how powerful AI is. This is karmic justice imo.
- martinald 8mo ago
  Totally agree, though ironically Claude code works way better with Excel than I expected. I even tried telling Copilot to convert each sheet to a CSV on one attempt THEN do calculations. It just ignored it and failed miserably, ironically outputting me a list of files that it should have made, along with the broken python script. I found this very amusing.
  - mattmanser 8mo ago
    Think why an LLM might really struggle with csvs. You're asking a chat bot to make a weird sentence with tons of commas in it. I've read that they're supposed to be great with XML as it's so structured, better than JSON, but haven't actually found that to be the case.
- QuantumGood 8mo ago
  Tim Berners-Lee thought pages would become machine-readable long ago, with "obvious" benefits, and that idea partly drove XML, RDF and HTML 5. Now the benefit of doing so seems even bigger (but are they?), and the time spent making existing documents AI readable seems to keep growing.
- irishcoffee 8mo ago
  > Microsoft has spent 30 years designing the most contrived XML-based format for Excel/Word/Powerpoint documents, so that it cannot be parsed except by very complicated bespoke applications with hundreds of developers involved. I had interns use c++ to unzip, parse, and repackage to json a standardized visio doc. I had no say in the standard, but specific blocks meant specific things, etc. The project was successful. The xml was parse-able... at least for our needs. The overall project died a swift death and this tidbit will probably be forgotten forever in the depths of repo heirarchy.
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drsalt 8mo ago
what is the source data? the author says they've seen "far more non-technical people than I'd expect using Claude Code in terminal" so like, 3 people? who are these people?
- deleted 8mo ago
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wrs 8mo ago
Some minor editing to how this would have been written in the mid-1980s: “The real leaps are being made organically by employees, not from a top down [desktop PC] strategy. Where I see the real productivity gains are small teams deciding to try and build a [Lotus 123] assisted workflow for a process, and as they are the ones that know that process inside out they can get very good results - unlike a [mainframe] software engineering team who have absolutely zero experience doing the process that they are helping automate.” The embedded “power users” show the way, then the CIO-friendly packaged software follows much later.
- SubiculumCode 8mo ago
  The power is in the tails
with 8mo ago
> The bifurcation is real and seems to be, if anything, speeding up dramatically. I don't think there's ever been a time in history where a tiny team can outcompete a company one thousand times its size so easily. Slightly overstated. Tiny teams aren't outcompeting because of AI, they're outcompeting because they aren't bogged down by decades of technical debt and bureaucracy. At Amazon, it will take you months of design, approvals, and implementation to ship a small feature. A one-man startup can just ship it. There is still a real question that has to be answered: how do you safely let your company ship AI-generated code at scale without causing catastrophic failures? Nobody has solved this yet.
- Gigachad 8mo ago
  I swear in a month at a startup I used to build what takes a year at my current large corp job. AI agents don't seem to have sped up the corporate process at all.
  - NitpickLawyer 8mo ago
    > AI agents don't seem to have sped up the corporate process at all. I think there's a parallel here between people finding great success with coding agents vs. people swearing it's shit. But when prodded it turns out that some are working on good code bases while others work on shit code bases. It's probably the same with large corpos. Depending on the culture, you might get such convoluted processes and so much "assumed" internal knowledge that agents simply won't work ootb.
- mhink 8mo ago
  > how do you safely let your company ship AI-generated code at scale without causing catastrophic failures? Nobody has solved this yet. Ultimately, it's the same way you ship human-generated code at scale without causing catastrophic failure: by only investing trust in critical systems to people who are trustworthy and have skin in the game. There are two possibilities right now: either AI continues to get better, to the point where AI tools become so capable that completely non-technical stakeholders can trust them with truly business-critical decision making, or the industry develops a full understanding of their capabilities and is able to dial in a correct amount of responsibility to engineers (accounting for whatever additional capability AI can provide). Personally, I think (hope?) we're going to land in the latter situation, where individual engineers can comfortably ship and maintain about as much as an entire team could in years past. As you said, part of the difficulty is years of technical debt and bureaucracy. At larger companies, there is a *lot* of knowledge about how and why things work that doesn't get explicitly encoded anywhere. There could be a service processing batch jobs against a database whose URL is only accessible via service discovery, and the service's runtime config lives in a database somewhere, and the only person who knows about it left the company five years ago, and their former manager knows about it but transferred to a different team in the meantime, but if it falls over, it's going to cause a high-severity issue affecting seven teams, and the new manager barely knows it exists. This is a contrived example, but it goes to what you're saying: just being able to write code faster doesn't solve these kinds of problems.
DavidPiper 8mo ago
> To really underline this, Microsoft itself is rolling out Claude Code to internal teams, despite (obviously) having access to Copilot at near zero cost, and significant ownership of OpenAI. I think this sums up quite how far behind they are I think it sums up how thoroughly they've been disrupted, at least for coding AIs (independent of like-for-like quality concerns rightly mentioned elsewhere in this thread re: Excel/Python). I understand ChatGPT can do like a million other things, but so can Claude. Microsoft deliberately using competitors internally is the thing that their customers should pay attention to. Time to transform "Nobody gets fired for buying Microsoft" into "Nobody gets fired for buying what Microsoft buy", for those inclined.
doom2 8mo ago
I guess this is as good a thread as any to ask what the current meta is for agentic programming (in my case, as applied to data engineering). There are all these posts that make it to the front page talking about productivity gains but very few of them actually detail the setup that's working for the author, just which model is best. I guess it's like asking for people's vim configs, but hey, there are at least a few popular posts mainly around git/vim/terminal configs.
- energy123 8mo ago
  I push most work into chat interface (attach full codebase as a single file, paste in specs, describe what I want), then copy the tasklist from chat into codex. This is to reduce codex token usage to avoid breaching weekly limits. I'd use a more agent-heavy process if I didn't care about cost.
- fragmede 8mo ago
  There more stuff in mine, but at the top of my ~/.claude/CLAUDE.md file, I have: ## Important Instructions - update todo.md as items are completed **Commit to git after making code changes.** Check `git status` first - only commit if there are actual changes: ```bash # If not in a git repository, initialize it first: git init # Then commit changes: git add <FILES_UPDATED> # Be surgical - add only the changes you just made. git commit -m "Description of changes" This lets me have bite-sized git commits that I can marshall later, rather than having to wrangl git myself.
- swordsith 8mo ago
  In my opinion no frontier model is the best at everything, especially if you're having to catch it up with pre-existing information about your project or an esoteric scripting language, that being said, with Cursor you can try out all of the popular available models and get a feel for which do better with which tasks, in my experience - Codex is a okay model but use light thinking if you value your time, Gemini 3 flash is where its been at for me recently if I need to do big changes I go to that, And cursors model composer is good for making plans or doing refactors / making rules. Cursor gives you tools to make prompting feel like less of a repetition game, so you worry more about the task at hand and its been super efficient for me. I don't use proper version control so the fact it saves a history of every files dif's, and you can jump back easily in chats and regress the code base is the game changer.
datsci_est_2015 8mo ago
Thought this was going to be more about programmers, but it was actually about non technical users and Microsoft’s product development failure. One tidbit I’d disagree with is that only those using the bleeding edge AI tools are reaping the benefits. There seem to be a lot of highly specialized tools and a lot of specific configurations (and mystical incantations) to get them to work, and those are constantly changing and being updated. The bleeding edge is a dangerous place to be if you value your time (and sanity). Personally, as someone working on moderate-to-highly complex software (live inference of industrial IoT data), I can’t really open a merge / pull request for my colleagues to review unless I 100% understand what I’ve pushed, and can explain to them as well. My killer app for AI would just be a CLI that gets me to a commit based on moderately technical input: “Add this configuration variable for this entry point; split this class into two classes, one for each of the responsibilities that are currently crammed together; update the unit tests to reflect these changes, including splitting the tests for the old class into two different test classes; etc” But, all the hype of the bleeding edge is around abstracting away the entire coding process until you don’t even understand what code is being generated? Hard to see it as anything but a pipe dream. AI is useful, but it’s not a panacea - you can’t fire it and replace it when it fucks up.
- georgeburdell 8mo ago
  “Add this configuration variable for this entry point; split this class into two classes, one for each of the responsibilities that are currently crammed together; update the unit tests to reflect these changes, including splitting the tests for the old class into two different test classes; etc” Granted I'm way behind the curve, but is this not how actual engineers (and not influencers) are using it? I heavily micro-manage the implementation because my manager still expects me to know the code
  - datsci_est_2015 8mo ago
    You could hardly believe that this is how actual engineers are using it if you only browsed HN. Maybe HN is only influencers?
tiangewu 8mo ago
Microsoft's failure around copilot in Excel gave my partner a very poor impression on AI's ability to help with financial tasks. It took a lot of convincing, but I finally got her to start using ChatGPT to help her write SQL and walk her through setting up some SaaS accounting software formulas. It worked so well now she's trying to find more applications at work. Claude code is too scary for her though. That will need to be in some Web UI before she feels comfortable giving it a try.
- NookDavoos 8mo ago
  Install "Claude for Excel" addon directly in the Excel itself. Works well.
protocolture 8mo ago
tl;dr: If you are trying to protect your IP from AI you probably use Copilot or nothing. If you have no IP to protect you are free to mess about.
fortran77 8mo ago
I know it's fun to bash Microsoft, but--while Claude is better, Microsoft's Copilot is far from "awful". I've used it productively with the VS Code integration for some esoteric projects: PIC PIO programming and Verilog.
- mike_hearn 8mo ago
  He's talking about the Copilot in other apps for non-programmers.
FilosofumRex 8mo ago
Generally speaking, if you're using your coding agent as your assistant inside your IDE, you're missing out on 80% of its benefits... If anything you should ask it how to do something and then act as its assistant on implementing it
- PunchyHamster 8mo ago
  also missing out on 80% of bugs
nickphx 8mo ago
Three kinds, those who do not use it.
- anxoo 8mo ago
  yes, the third kind of AI user. kind of similar to the three kinds of soccer players: offence, defence, and people who don't play soccer. thanks for the comment!
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athrowaway3z 8mo ago
> sandboxing agents is difficult I use this amazingly niche and hipster approach of giving the agent its own account, which through inconceivably highly complex arcane tweaking and configurations can lock down what they can and cant do. --- Can somebody for the love of god tell me why articles keep bringing up why this is so difficult?
- deleted 8mo ago
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- fragmede 8mo ago
  It's a bunch of work, that takes a bunch of time, and I want it nowwwww-owwwww! ...is how I imagine that conversation goes.
- NitpickLawyer 8mo ago
  I have antigravity in its own account and that has worked pretty well so far. I also use devcontainers for the cli agents and that has also worked out well. It's one click away in my normal dev flow (I was using this anyway before for python projects).
- chrisjj 8mo ago
  Why? Because the purported benefit is to make everything easier and faster. Not safe.
viccis 8mo ago
>You can easily run Monte Carlo simulations Ah yes, Monte Carlo simulations, regular part of a finance team's objectives.
- Leynos 8mo ago
  https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance
nnevatie 8mo ago
I'd be very interested in seeing some statistics on what could be considered confidential material pasted on ChatGPT's chat interface. I think the results would be pretty shocking and I think mostly because the integrations to source services are abject messes.
- Antibabelic 8mo ago
  https://www.theregister.com/2025/10/07/gen_ai_shadow_it_secrets/ https://www.theregister.com/2025/10/07/gen_ai_shadow_it_secr... "With 45 percent of enterprise employees now using generative AI tools, 77 percent of these AI users have been copying and pasting data into their chatbot queries, the LayerX study says. A bit more than a fifth (22 percent) of these copy and paste operations include PII/PCI."
  - chrisjj 8mo ago
    No worse than MS Office on web, then?
hereme888 8mo ago
I'm still trying to wrap my head over the past decade: useful AI, self operating vehicles, real AI robots, immersive VR, catching reusable rockets with chopsticks, and of course the flying cars. What will be the expected work output for the average future worker?
jsattler 8mo ago
Some years ago, I was at a conference and attended a very interesting talk. I don't remember the title of the talk, but what stuck with me was: "It's no longer the big beating the small, but the fast beating the slow". This talk was before all the AI hype. Working at a big company myself, I think this has never been more true. I think the question is, how to stay fast.
- josters 8mo ago
  And, to add to that, how to know when to slow down. Also, having worked at a big company myself, I think the question shifts towards "how to get fast" without compromising security, compliance etc.
- swyx 8mo ago
  this is generic startup advice (doesnt mean its not true). you level up a bit when you find instances where slow beat fast (see: Teams vs Slack)
- chrisjj 8mo ago
  > the fast beating the slow This includes to the bottom of a cliff, note.
crystal_revenge 8mo ago
One the most reliable BS detectors I've found is when you have to try to convince other people of your edge. If you have found a model that accurately predicts the stock market, you don't write a blog post about how brilliant you are, you keep it quiet and hope no one finds out while you rake in profits. I still can't figure out quite what motivates these "AI evangelist" types (unlike crypto evangelists who clearly create value for themselves when they create credibility), but if you really have a dramatically better way to solve problems, you don't need to waste your breath trying to convince people. The validity of your method will be obvious over time. I was just interviewing with a company building a foundation model for supposedly world changing coding assistants... but they still can't ship their product and find enough devs willing to relocate to SF. You would think if you actually had a game changing coding assistant, your number one advantage would be that you don't need to spend anything on devs and can ship 10x as fast as your competition. > First, you have the "power users", who are all in on adopting new AI technology - Claude Code, MCPs, skills, etc. Surprisingly, these people are often not very technical. It's not surprising to me at all that these people aren't very technical. For technical people code has never been the bottleneck. AI does reduce my time writing code but as a senior dev, writing code is a very small part of the problems I'm solving. I've never had to argue with anyone that using a calculator is a superior method of solving simple computational math problems than doing it by hand, or that using a stand mixer is more efficient than using a wooden spoon. If there was a competing bakery arguing that the wooden spoon was better, I wouldn't waste my time arguing about the stand mixer, I would just sell more pastry then them and worry about counting my money.
- swordsith 8mo ago
  Agreed. I think even though the term is stupid calling them cognitive improvement tools makes sense. The models will get better but most people will never learn how to effectively prompt or plan with a agentic model.
- daliusd 8mo ago
  I guess I am kind of "AI evangelist" in my circles (team, ecosystem and etc). I personally see benefits in "AI" both for side-projects and main work. However according to my last measurements improvements is not dramatic, it is huge (about 30%), but not dramatic. I share my insights purely to have less on my shoulders (if my team members can do more it is less for me to do).
camgunz 8mo ago
I think this article is generally insightful, but I don't think the author really knows if they one shotted the excel to python transformation or not. Maybe they elided an extensive testing phase, but otherwise big bugs could be lurking. Maybe it's not a big deal, or maybe it's a compliance model with severe financial penalties for non-compliance. I just personally don't kind these tradeoffs going implicit.
- BolsunBacset 8mo ago
  The author also said "almost" one shotted. Almost can mean a lot of things. I'm almost rich and almost handsome. But just not there...
PunchyHamster 8mo ago
I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are interested only in results, and are not interested in knowing more about the topic or honing their skills in the topic The second group is one that thinks talking to a chatbot will replace senior developer
- Aardwolf 8mo ago
  The same person might be both kinds of users, depending on the topic or just the time of the day
  - mathgeek 8mo ago
    It's almost as if categorization is often an oversimplification.
- sevenzero 8mo ago
  I started to outsource thinking at my job as my company made it very clear that they do not want/cant afford thinking engineers. Thinking requires time and they want to deliver quickly. So they cater towards the very realistic deadlines our PMs set for features (/s). Funnily enough the features have to be implemented ASAP according to the customers, but the customer feedback takes like 6 months due to them using the new feature for the first time 6 months after delivery. I just dont care anymore. Gonna leave the learning part up to my time off, but getting generally tired of the industry as a whole, so just putting in minimal effort to pay my bills until things explode or get better. So for me its definitely outsourcing thinking at work.
  - gloomyday 8mo ago
    This is a fatalistic attitude, but I can totally get behind. It has become harder to associate my job with contributing with society.
anal_reactor 8mo ago
> This effectively leads to a situation where smaller company employees are able to be so much more productive than the equivalent at an enterprise. It often used to be that people at small companies really envied the resources & teams that their larger competitors had access to - but increasingly I think the pendulum is swinging the other way. Small companies are more agile and innovative while corporations often just shuffle papers around. Wow, what a bold claim, never seen before in the entire history of economics.
deafpolygon 8mo ago
There’s also an emerging group of users (such as myself) who essentially use it primarily as an “on-demand” teacher and not as a productivity tool. I am learning software development without having it generate code for me—preferring to have it explain each thing line-by-line. But… it’s not only for learning development, but I can query it for historical information and have it point me to the source of the information (so I can read the primary sources as much as possible). It allows me to customize the things I want to learn at my own pace, while also allowing me to diverge for a moment from the learning material. I have found it invaluable… and so far, Gemini has been pretty good at this (probably owing to the integration of Google search into Gemini). It lets me cut through the SEO crap that has plagued search engines in recent years.
wjholden 8mo ago
I remember a colleague jumping through hoops trying to get Python installed on an enterprise computer. We never did get to a yes and resorted to using PowerShell instead. The policy constraints at enterprises that this author describes are very real and very harmful. Perhaps the wildest thing to me is how you'll have senior leaders in a company talking about innovation, but their middle managers actively undermine change out of fear of liability. So many enterprise IT employees are really just trying to avoid punishment that their organization cannot try new things without substantial top-down efforts to accept risk.
- chrisjj 8mo ago
  > The policy constraints at enterprises that this author describes are very real and very harmful. This is like saying prison bars are harmful. It depends which side you are on.
  - wjholden 8mo ago
    That is an insightful response, I may quote you on this.
fauigerzigerk 8mo ago
>What I've come to realise is that the power of having a bash sandbox with a programming language and API access to systems, combined with an agentic harness, results in outrageously good results for non technical users. It can effectively replace nearly every standard productivity app out there - both classic Microsoft Office style ones - and also web apps. I very much doubt that tinkering with a non-repeatable, probabilistic process is how most non-technical users will routinely use software. I can imagine power users taking this approach to _create_ or extend productivity tools for themselves and others, just like they have been doing with Excel for decades. It will not _replace_ productivity tools for most non-technical users.
- deleted 8mo ago
  [deleted]
chrisjj 8mo ago
> Thirdly, this all needs to be wrapped up in some sort of secure mechanism Putting that first would have saved the bother of putting the second and third.
veunes 8mo ago
This is the birth of Shadow AI, and it’s going to be bigger than Shadow IT ever was in the 2000s Back then, employees were secretly installing Excel macros and Dropbox just to get work done faster. Now they’re quietly running Claude Code in the terminal because the official Copilot can’t even forma a CSV properly. CISOs are terrified right now and that’s understandable. Non-technical people with root access and agents that write code are a security nightmare. But trying to ban this outright will only push your most effective employees to places where they’re allowed to "fly"
- AdamN 8mo ago
  "they’re quietly running Claude Code" ... with their tokens or even worse full on usernames and passwords that have write/execute privileges.
anonymousDan 8mo ago
'some sort of security' - oh great, security as an afterthought.
chrisjj 8mo ago
> It can effectively replace nearly every standard productivity app out there May we see the "agentic" replacement for Word, please?
srinath693 8mo ago
The real divide isn't technical vs. non-technical: it's people with new problems vs. people maintaining old solutions. AI is incredible at generating first drafts of anything. It's terrible at understanding why the existing thing is the way it is.
maffyoo 8mo ago
this seems reasonable but isn't the conclusion a statement what we already know. These tools are really powerful, but with the ability to cause significant pain, need organisations to adapt, so that they can make best use of them but this is fraught with security problems. AI looks a lot like a technology problem but ultimately, to most small businesses, it's a procurement and change management problem. Also (I appreciate the authors message here but..) "Excel on the finance side is remarkably limiting when you start getting used to the power of a full programming ecosystem like Python" With the addition of lambdas Excel formulae are Turing complete. no more need for VBA in a (mostly) functional environment. Also on this, Claude for Excel needs a lot of work (as does any tool working with financial models) if you have ever used them in anger I dont think you'll be relying on them with your non-technical finance manager for a while...
rob 8mo ago
The number of people I've run into with a non-technical background that think ChatGPT is the definitive end-all for AI is very high. Most just don't know anything else even exists. I do wonder how long they'll be able to use this to their advantage before something "else" comes along. Like how IE had the largest market share before Chrome and other alternatives started catching up. Then again, some markets like YouTube still haven't had any real serious alternatives. Maybe ChatGPT will always be number one in the consumer eyes.
okokwhatever 8mo ago
You can see the fear all around this thread. And, tbh, it makes total sense. There is nothing we can do to stop this dropping ball, we can accept it or leave the room but the industry has changed for all of us. I mean, you can use it one way or another but the concept of critical thinking is our only survival tool if your relaying on a it job this days. How long it will last? Who cares, we're fucked anyways...
- enemyz0r 8mo ago
  Yep
iqandjoke 8mo ago
It is like saying Apple is using Claude Code internally while selling you to use Apple Intelligence https://x.com/tbpn/status/2016911797656367199 https://x.com/tbpn/status/2016911797656367199
mrbluecoat 8mo ago
> What I've come to realise is that the power of having a bash sandbox with a programming language and API access to systems, combined with an agentic harness, results in outrageously good results for non technical users. I would argue if they're using all that tooling, they _are_ technical users.
notepad0x90 8mo ago
I suspect there are much more than two kinds. there is a varying degree of understanding what these tools are capable of, and that multiplied by what people need and how much they care about outcomes and consequences is the number of "kinds" of AI users. Let's take the group of developers (to keep it simple) that have a deep understanding of LLMs and how they work. Even then, some don't care if it generates entire codebases for them, some know there will be bugs in it, they just don't care. Some care, but they know their job is to make their project managers happy. Others don't have apathy or pressure like that, but they'll still use it in the same way, because for one reason or the other it saves them time. I'm probably missing more examples, but it is the same usage, but different motivations, people, and environments.
fny 8mo ago
Software engineers don't understand how user hostile all these AI gizmos are. Terminals are scary. AI running local code is scary. Random Github software is scary. And in my experience, normies are far more security paranoid than developers when it comes to AI.
- riskable 8mo ago
  Normies have a much more realistic take on AI than technical people or semi-technical "power users": * They LOVE image-generating AI and AI that messes with their own photos/videos. * They will ask ChatGPT, Gemini, etc and just believe the result. * They will ask Copilot to help them make a formula in Excel and be happy to be done. The common theme here is they don't care. To them, AI is just a neat thing. It's not a huge difference in their lives. They don't think about the environmental impact much unless someone tells them it's bad, via a high-quality video stream that itself was vastly worse for the environment than any AI conversation or image generation ever could be. They will play a game 100% made by AI because their friend said it was fun. They don't care that some AAA publisher lost a sale on their "human made for sure, just trust us :nod:" identical game because the bored person was able to pull of something good enough with little effort (and better design decisions). They also don't care if some article or book or whatever was written partially or entirely by AI as long as it's good. The AI part just isn't important to them. Not even a little bit!
  - hxugufjfjf 8mo ago
    Its kind of funny how it’s the exact same discussion as we used to have about privacy in the advent of social media. "I’m not worried, I got nothing to hide!" The convenience benefits of Facebook (in the beginning, likely less nowadays) massively outweighed the privacy concerns of the layman or woman.
riazrizvi 8mo ago
I think the main divisions are 1) people who are using it in fields they have little knowledge of to get basic competence, 2) the same people using it for advanced competence who are kidding themselves, 3) experts who are battling it in their own fields to finally get better answers than they could without it. The first group are like Improved-Generalists. The third are Improved-Specialists. The second are delusional hype jockeys that drive the dumb talking points that extrapolate up the whazoo what AI is going to do and whatnot.
darepublic 8mo ago
On mobile Firefox the subscribe modal extends past the width of the viewport. I assume the close button is hanging out there outside of view. For all the peddlers of the astonishing power of agents.. why is your software subpar. This sounds like snark but I'm actually serious. Anyone crowing about the productivity gains I expect to see fast high quality software
waffletower 8mo ago
When confined to a Github Copilot Business license, you do have options, as the license does provide access to frontier Anthropic and Google models in addition to its other offerings. Unfortunately it will not work directly with Claude Code without proxy server hacks, but Opencode is an option, and I am interested in learning about others (save for Aider, which I have tried and discarded).
the__alchemist 8mo ago
I've made a similar observation. I'm clearly in camp #2: No agents, and use ChatGPT or Gemini to ask specific questions, and feed it only the context I want it to have. I have a parallel observation: Many people use code editors that have weak introspection and refactoring ability compared to IDEs like JetBrains'. This includes VSCode, Zed, Emacs etc. I have a suspicion there is a big overlap between this and Group 1. It is wild to me that people are generating AI code while skipping in-IDE error checking, deterministic autocomplete, and refactoring.
oakhaven 8mo ago
I really like that this article explained the title thesis in the first 4 paragraphs. At that point you can decide if you agree or if your want to read on. No unnecessary fluff baiting the reader to read the whole thing in order to find out what are the two kinds of users. More writing like this.
doginasuit 8mo ago
Here's how I'd break down the two types of users: People who are using AI to teach themselves how to work in the domain they are interested in, and people who are relying on AI to do all or most of the heavy lifting. I'd argue that the people using AI most effectively are in the mostly-chatters group that the author defines, and specifically they are using the AI to understand the domain on a deeper level. The "power users" are heading for a dead end, they will arrive as soon as AI is capable of figuring out what is actually valuable to people in the given domain, not generally a difficult problem to solve. These power users will eventually be outclassed by AIs that can self-navigate. But I would argue that a human that has a rich understanding of the domain will still beat self-navigating AI for a long time to come.
satiated_grue 8mo ago
This seems to be a bit of an echo of the 1980s and the power shift brought about by the introduction of the IBM PC - the decentralization of control over data and processes from the walled garden of the computer room to the people at their desks with VisiCalc and BASIC, and then the explosion of productivity software.
emeraudelinton 8mo ago
[dead]
kajolshah_bt 8mo ago
I see this split clearly in real products: some users treat AI like a tool to support their workflow, others treat it like a replacement for thinking. The first group uses AI to reduce repetitive work and interprets results critically; the second group abandons it when outcomes aren’t perfect. In practice, the users who end up valuing AI are the ones who see it as an assistant, not an oracle. That distinction matters because it shapes how you design UI, fallback flows, and trust signals. If the interface assumes perfect output, retention drops; if it assumes collaboration with the user, retention improves.

355 points by martinald 8mo ago

Terrifying that people are creating financial models with AI when they don’t have the skills to verify the model does what they expect

fatheranton 8mo ago
[dead]
martinald 8mo ago
They have an excel sheet next to it - they can test it against that. Plus they can ask questions if something seems off and have it explain the code.
- karlgkk 8mo ago
  [flagged]
  - yomismoaqui 8mo ago
    You would be surprised at the volume of money made by businesses supported by Excel.
    - martinald 8mo ago
      Yes. I suspect there are thousands of Excel files that "process" >$1bn/yr out there.
      - irishcoffee 8mo ago
        Allow me to introduce to you: ACH. It is truly fascinating.
- AlotOfReading 8mo ago
  I'm not sure being able to verify that it's vaguely correct really solves the issue. Consider how many edge cases inhabit a "30 sheet, mind-numbingly complicated" Excel document. Verifying equivalence sounds nontrivial, to put it mildly.
  - Dylan16807 8mo ago
    Consider how many edge cases it misses. Equivalence probably shouldn't be the top priority here.
    - Nevermark 8mo ago
      Equivalence here would definitely be the worst test, except for all the alternatives.
  - Draiken 8mo ago
    They don't care. This is clearly someone looking to score points and impress with the AI magic trick. The best part is that they can say the AI will get some stuff wrong, they knew that, and it's not their fault when it breaks. Or more likely, it'll break in subtle ways, nobody will ever notice and the consequences won't be traced back to this. YOLO!
- lmm 8mo ago
  > They have an excel sheet next to it - they can test it against that. It used to be that we'd fix the copy-paste bugs in the excel sheet when we converted it to a proper model, good to know that we'll now preserve them forever.
nebula8804 8mo ago
All we need is one major crash caused by AI to scare the capital owners. Then maybe us white collar workers can breath a bit for at least another few more years(maybe a decade+).
- danielbln 8mo ago
  A decade+ is wishful copium.
  - nebula8804 8mo ago
    Well I did say "maybe". It all depends on how badly they get burned. A crash will hopefully scare enough of them from trying for a while.
- onion2k 8mo ago
  All we need is one major crash caused by AI to scare the capital owners. All the previous human-driven crashes didn't change anything about capital owners' approach to money, so why would an AI-driven crash change things?
  - leptons 8mo ago
    The scapegoating is different. Using an LLM makes them more culpable for the failure, because they should have known better than to use a tech that is well known to systematically lie.
  - ktzar 8mo ago
    because we have an alternative that we humans can fix. The problem with AI is that it creates without leaving a trace of understanding.
- pizzafeelsright 8mo ago
  Most of the large outages at Meta in the past 10 years were related to early AI automation.
mkoubaa 8mo ago
It's not terrifying at all, some shops will fail and some will succeed and in the aggregate it'll be no different for the rest of us
myfakebadcode 8mo ago
I’m trying to learn rust coming from python (for fun). I use various LLM for python and see it stumble. It is a beautiful experience to realize wtf you don’t know and how far over their skis so many will get trusting AI. The idea of deploying a rust project at my level of ability with an AI at the helm is is terrifying.
derrida 8mo ago
Business as usual.
- deleted 8mo ago
  [deleted]
taneq 8mo ago
If they have the skills to verify the Excel model then they can apply the same approach to the numbers produced by the AI-generated model, even if they can’t inspect it directly. In my experience a lot of Excel models aren’t really tested, just checked a bit and them deemed correct.
chrisjj 8mo ago
That will get less terrifying when they move on to medical.
riskable 8mo ago
I work for a huge bank: The actual terrifying thing is that these financial models semi-technical management are creating in Excel are actually relied upon in the first place. If you convert bullshit from Excel to Python it's still bullshit. There's a reason why Claude can one-shot it and no one questions the result :D
- theshrike79 8mo ago
  The Python bullshit at least can be unit tested bit by bit and easily improved. Nobody will see that on sheet 27 cell FG456 is actually a static number that Brian typoed in there in 2019 and not a formula.
pizzafeelsright 8mo ago
Someone recently had AI create a trading bot and it returns 131% on every transaction over a 30 day period - do you really think they care about code quality or ability to verify the math?
- simmerup 8mo ago
  ANd I have a bridge to sell you in London
  - pizzafeelsright 8mo ago
    Someone bought that bridge and it stands in Arizona.
riscii68 8mo ago
Yep. And I think many are too focused on just the pure ability to build models now, when in reality a model is at its core a set of assumptions. Using models you don't understand, didn't build, and barely reviewed amplifies the magnitude of any assumption error, imo.

superkuh 8mo ago

The argument seems to be that having a corporation restrict your ability to present arbitrary text directly to the model and only being able to go through their abstract interface which will integrate your text into theirs (hopefully) is more productive than fully controlling the input text to a model. I don't think that's true generally. I think it can be true when you're talking about non-technical users like the article is.

majormajor 8mo ago
The use of specialization of interfaces is apparent if you compare Photoshop with Gemini Pro/Nano Banana for targeted image editing. I can select exactly where I want changes and have targeted element removal in Photoshop. If I submit the image and try to describe my desired changes textually, I get less easily-controllable output. (And I might still get scrambled text, for instance, in parts of the image that it didn't even need to touch.) I think this sort of task-specific specialization will have a long future, hard to imagine pure-text once again being the dominant information transfer method for 90% of the things we do with computers after 40 years of building specialized non-text interfaces.
- fdsf2 8mo ago
  It behooves me that Gemini et al dont have these standard video editing tools. Do the engineers seriously think prompting by text is the way people want videos to be generated? Nope. People want to customise. E.g. Check out capcut in the context of social media. Ive been trying to create a quick and dirty marketing promo via an LLM to visualise how a product will fit into the world of people - it is incredibly painful to 'hope and pray' that by refining the prompt via text you can make slight adjustments come through. The models are good enough if you are half-decent at prompting and have some patience. But given the amount invested, I would argue they are pretty disappointing. Ive had to chunk the marketing promo into almost a frame-by-frame play to make it somewhat work.
  - suprstarrd 8mo ago
    Speaking as someone who doesn't like the idea of AI art so take my words with a grain of salt, but my theory is that this input method exclusivity is intentional on their part, for exactly the reason you want the change. If you only let people making AI art communicate what they want through text or reference attachments (the latter of which they usually won't have), then they have to spend time figuring out how to put it into words. It IS painful to ask for those refinements, because any human would clearly understands it. In the end, those people get to say that they spent hours, days, or weeks refining "their prompt" to get a consistent and somewhat-okay looking image; the engineers get to train their AI to better understand the context of what someone is saying; and all the while the company gets to further legitimize a false art form.

Havoc 8mo ago

The copilot button in excel at my work can’t access the excel file of the window it’s in. As in “what’s in cell A1” and it says I can’t read this file. Not even sure what the point is then frankly. I’m happily vibe coding at work but yeah article is right. MS has enterprise market share by default not by merit. Stunning contrast between what’s possible and what’s happening in big corp

deleted 8mo ago
[deleted]
cmrdporcupine 8mo ago
Meanwhile the people I know who work at Microsoft say there's a constant whip-cracking to connect everything they're doing to "AI" and prove that's what they're doing.
- PunchyHamster 8mo ago
  so whole company decided to collectively half-ass it so managers fuck off ? :D
bwat49 8mo ago
yeah I actually use AI a lot, but copilot is... useless. When microsoft adds copilot to their various apps they don't seem to put any thought/effort behind it beyond sticking a copilot button somewhere. And if the copilot button does nothing but open a chat window without any real integration with the app, what the hell is the point of that when there's already a copilot button in the windows taskbar?
- chrisjj 8mo ago
  You have overestimated the intelligence of the target audience :)
deleted 8mo ago
[deleted]
Havoc 8mo ago

s-lambert 8mo ago

I don't see a divergence, from what I can tell a lot of people have only just started using agents in the past 3-4 months when they got good enough that it was hard to say otherwise. Then there's stuff like MCP, which never seemed good and was entirely driven by people who talked more about it than used it. There also used to be stuff like langchain or vector databases that nobody talks about anymore, maybe they're still used but they're not trendy anymore. It seems way too soon to really narrow down any kind of trends after a few months. Most people aren't breathlessly following the next twitter trend, give it at least a year. Nobody is really going to be left behind if they pick up agents now instead of 3 months ago.

neom 8mo ago
Not sure how much falling behind there is even going to be, I'm an old school linux type with D- programming skills, yet getting going building things has been ridiculously easy. The swarms thing makes is so fast. I've churned 2 small but tested apps out in 2 weekends just chatting with claude code, the only thing I had to do was configure the servers.
Gigachad 8mo ago
The only people I see talking about MCP are managers who don't do anything but read linked in posts and haven't touched a text editor in years if ever.
_1tan 8mo ago
What‘s used instead of MCP in reality? Just REST or other existing API things?
- senordevnyc 8mo ago
  Yeah, I suspect the people railing against MCP don’t actually use agents much at all. MCP is super useful for giving your agent access to tools. The main alternative is CLI tools, if they exist, but they don’t always, or it’s just more awkward than a well-designed MCP. I let my agent use the GitHub CLI, but I also have MCPs for remote database access and bugsnag access, so they can debug issues on prod more easily.

defrost 8mo ago

The "upside" description: On the other you have a non-technical executive who's got his head round Claude Code and can run e.g. Python locally. I helped one recently almost one-shot converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code. Once the model is in Python, you effectively have a data science team in your pocket with Claude Code. You can easily run Monte Carlo simulations, pull external data sources as inputs, build web dashboards and have Claude Code work with you to really integrate weaknesses in your model (or business). It's a pretty magical experience watching someone realise they have so much power at their fingertips, without having to grind away for hours/days in Excel. almost makes me physically sick. I've a reasonably intense math background corrupted by application to geophysics and implementing real world numerical applications. To be fair, this statement alone: * 30 sheet mind numbingly complicated Excel financial model makes my skin crawl and invokes a flight reflex. Still, I'll concede that a Claude Code conversion to Python of a 30 sheet Excel financial model is unlikely to be significantly worse than the original.

decimalenough 8mo ago
I'm almost certain it will be significantly worse. The Excel sheet will have been tuned over the years by people who knew exactly what it was doing and fixed countless bugs along the way. The Claude Code copy will be a simulacrum that may behave the same way with some inputs, but is likely to get many of edge cases wrong, and, when you're talking about 30 sheets of Excel, there will be many, many of these sharp edges.
- defrost 8mo ago
  I won't disagree - I suffered from insufficient damning praise in my last sentence above. IMHO, earned through years of bleeding eyeballs, the first will be riddled with subtle edge cases curiously patched and fettled such that it'll limp through to the desired goal .. mostly. The automated AI assisted transcoding will be ... interesting.
- holoduke 8mo ago
  My assumption is that with the right approach you can create a much much better and reliable program using only Claude code. You are referring to yolo coding results

ed_mercer 8mo ago

> Microsoft itself is rolling out Claude Code to internal teams Seems like Nadella is having his Baller moment

fdsf2 8mo ago
Nothing but ego frankly. Apple had no problem settling for a small market share back in the day... look where they are now. It didnt come from make-believe and fantasy scenarios of the future based on an unpredictable technology.
- leptons 8mo ago
  >look where they are now. Still with a small market share. They only figured out how to extort the maximum amount of money from a smaller user base, and app developers, really anyone they can.
  - Mentlo 8mo ago
    I guess a quarter of the smartphone market (leader), half of the tablet market (leader) and a tenth of the global pc market (2nd place) / 6th of the usa/europe market (2nd place) being a small market share is a take.
    - leptons 8mo ago
      >a quarter of the smartphone market (leader) Android is by far the leader. >half of the tablet market (leader) Half does not make someone a "leader" >a tenth of the global pc market (2nd place) 2nd place?? They're last place, by a wide margin. >6th of the usa/europe market (2nd place) Also last place. I guess the reality distortion field is still alive and well.
      - Mentlo 8mo ago
        Os x has a 10% market share, which is 2nd after Windows, but i agree on that one i conflated terms. I couldn’t quickly find device manufacturers stats. If wiki is to be trusted - apple is 4th, with share not far behind dell [1]. If half doesn’t make you leader what does? Maybe you should elaborate your definition of leader? For me it’s “has the highest market share”. And in that definition half is necessarily true. It’s funny that for PC’s you went for manufacturers (apple is 4th) but for mobile you went for OS (Apple is 2nd). On mobile devices, Apple is 1st, having double market share compared to 2nd place (samsung). The need to paint Apple as purely a marketing company always fascinated me. Marketing is a big part of who they are though. [1] https://en.wikipedia.org/wiki/Market_share_of_personal_computer_vendors https://en.wikipedia.org/wiki/Market_share_of_personal_compu...

decimalenough 8mo ago

> I helped one recently almost one-shot[3] converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code. I'm sure Claude Code will happily one-shot that conversion. It's also virtually guaranteed to have messed up vital parts of the original logic in the process.

linsomniac 8mo ago
It depends on how easily testable the Excel is. If Claude has the ability to run both the Excel and the Python with different inputs, and check the outputs, it's stunningly likely to be able to one-shot it.
- martinald 8mo ago
  That's exactly what it did (author here).
  - majormajor 8mo ago
    I'm having trouble reconciling "30 sheet mind numbingly complicated Excel financial model" and "Two or three prompts got it there, using plan mode to figure out the structure of the Excel sheet, then prompting to implement it. It even added unit tests to the Python model itself, which I was impressed with!" "1 or 2 plan mode prompts" to fully describe a 30-sheet complicated doc suggests a massively higher level of granularity than Opus initial plans on existing codebases give me or a less-than-expected level of Excel craziness. And the tooling harnesses have been telling the models to add testing to things they make for months now, so why's that impressive or suprising?
    - martinald 8mo ago
      No it didn't make a giant plan of every detail. It made a plan of the core concepts and then when it was in implementation mode it kept checking the excel file to get more info. It took around ~30 mins in implementation mode to build it. I was impressed because the prompt didn't ask it to do that. It doesn't normally add tests for me without asking, YMMV.

danpalmer 8mo ago

I've noticed a huge gap between AI use on greenfield projects and brownfield projects. The first day of working on a greenfield project I can accomplish a week of work. But the second day I can accomplish a few days of work. By the end of the first week I'm getting a 20% productivity gain. I think AI is just allowing everyone to speed-run the innovator's dilemma. Anyone can create a small version of anything, while big orgs will struggle to move quickly as before. The interesting bit is going to be whether we see AI being used in maturing those small systems into big complex ones that account for the edge cases, meet all the requirements, scale as needed, etc. That's hard for humans to do, and particularly while still moving. I've not see any of this from AI yet outside of either a) very directed small changes to large complex systems, or b) plugins/extensions/etc along a well define set of rails.

data-ottawa 8mo ago
It’s fantastic to be able to prototype small to medium complexity projects, figure what architects work and don’t, then build on a stable foundation. That’s what I’ve been doing lately, and it really helps get a clean architecture at the end.
- johnrob 8mo ago
  I’ve done this in pure Python for a long time. Single file prototype that can mostly function from the command line. The process helps me understand all the sub problems and how they relate to each other. Best example is when you realize behaviors X, Y, and Z have so much in common that it makes sense to have a single component that takes a parameter to specify which behavior to perform. It’s possible that already practicing this is why I feel slightly “meh” compared to others regarding GenAI.
EnPissant 8mo ago
I have experienced much of the opposite. With an established code base to copy patterns from, AI can generate code that needs a lot less iteration to clean up than on green fields projects.
- 8mo ago

smuhakg 8mo ago

> On one hand, you have Microsoft's (awful) Copilot integration for Excel (in fairness, the Gemini integration in Google Sheets is also bad). So you can imagine financial directors trying to use it and it making a complete mess of the most simple tasks and never touching it again. Microsoft has spent 30 years designing the most contrived XML-based format for Excel/Word/Powerpoint documents, so that it cannot be parsed except by very complicated bespoke applications with hundreds of developers involved. Now, it's impossible to export any of those documents into plain text that an LLM can understand, and Microsoft Copilot literally doesn't work no matter how much money they throw at it. My company is now migrating Word documents to Markdown because they're seeing how powerful AI is. This is karmic justice imo.

martinald 8mo ago
Totally agree, though ironically Claude code works way better with Excel than I expected. I even tried telling Copilot to convert each sheet to a CSV on one attempt THEN do calculations. It just ignored it and failed miserably, ironically outputting me a list of files that it should have made, along with the broken python script. I found this very amusing.
- mattmanser 8mo ago
  Think why an LLM might really struggle with csvs. You're asking a chat bot to make a weird sentence with tons of commas in it. I've read that they're supposed to be great with XML as it's so structured, better than JSON, but haven't actually found that to be the case.
QuantumGood 8mo ago
Tim Berners-Lee thought pages would become machine-readable long ago, with "obvious" benefits, and that idea partly drove XML, RDF and HTML 5. Now the benefit of doing so seems even bigger (but are they?), and the time spent making existing documents AI readable seems to keep growing.
irishcoffee 8mo ago
> Microsoft has spent 30 years designing the most contrived XML-based format for Excel/Word/Powerpoint documents, so that it cannot be parsed except by very complicated bespoke applications with hundreds of developers involved. I had interns use c++ to unzip, parse, and repackage to json a standardized visio doc. I had no say in the standard, but specific blocks meant specific things, etc. The project was successful. The xml was parse-able... at least for our needs. The overall project died a swift death and this tidbit will probably be forgotten forever in the depths of repo heirarchy.

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drsalt 8mo ago

what is the source data? the author says they've seen "far more non-technical people than I'd expect using Claude Code in terminal" so like, 3 people? who are these people?

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wrs 8mo ago

Some minor editing to how this would have been written in the mid-1980s: “The real leaps are being made organically by employees, not from a top down [desktop PC] strategy. Where I see the real productivity gains are small teams deciding to try and build a [Lotus 123] assisted workflow for a process, and as they are the ones that know that process inside out they can get very good results - unlike a [mainframe] software engineering team who have absolutely zero experience doing the process that they are helping automate.” The embedded “power users” show the way, then the CIO-friendly packaged software follows much later.

SubiculumCode 8mo ago
The power is in the tails

with 8mo ago

> The bifurcation is real and seems to be, if anything, speeding up dramatically. I don't think there's ever been a time in history where a tiny team can outcompete a company one thousand times its size so easily. Slightly overstated. Tiny teams aren't outcompeting because of AI, they're outcompeting because they aren't bogged down by decades of technical debt and bureaucracy. At Amazon, it will take you months of design, approvals, and implementation to ship a small feature. A one-man startup can just ship it. There is still a real question that has to be answered: how do you safely let your company ship AI-generated code at scale without causing catastrophic failures? Nobody has solved this yet.

Gigachad 8mo ago
I swear in a month at a startup I used to build what takes a year at my current large corp job. AI agents don't seem to have sped up the corporate process at all.
- NitpickLawyer 8mo ago
  > AI agents don't seem to have sped up the corporate process at all. I think there's a parallel here between people finding great success with coding agents vs. people swearing it's shit. But when prodded it turns out that some are working on good code bases while others work on shit code bases. It's probably the same with large corpos. Depending on the culture, you might get such convoluted processes and so much "assumed" internal knowledge that agents simply won't work ootb.
mhink 8mo ago
> how do you safely let your company ship AI-generated code at scale without causing catastrophic failures? Nobody has solved this yet. Ultimately, it's the same way you ship human-generated code at scale without causing catastrophic failure: by only investing trust in critical systems to people who are trustworthy and have skin in the game. There are two possibilities right now: either AI continues to get better, to the point where AI tools become so capable that completely non-technical stakeholders can trust them with truly business-critical decision making, or the industry develops a full understanding of their capabilities and is able to dial in a correct amount of responsibility to engineers (accounting for whatever additional capability AI can provide). Personally, I think (hope?) we're going to land in the latter situation, where individual engineers can comfortably ship and maintain about as much as an entire team could in years past. As you said, part of the difficulty is years of technical debt and bureaucracy. At larger companies, there is a *lot* of knowledge about how and why things work that doesn't get explicitly encoded anywhere. There could be a service processing batch jobs against a database whose URL is only accessible via service discovery, and the service's runtime config lives in a database somewhere, and the only person who knows about it left the company five years ago, and their former manager knows about it but transferred to a different team in the meantime, but if it falls over, it's going to cause a high-severity issue affecting seven teams, and the new manager barely knows it exists. This is a contrived example, but it goes to what you're saying: just being able to write code faster doesn't solve these kinds of problems.

DavidPiper 8mo ago

> To really underline this, Microsoft itself is rolling out Claude Code to internal teams, despite (obviously) having access to Copilot at near zero cost, and significant ownership of OpenAI. I think this sums up quite how far behind they are I think it sums up how thoroughly they've been disrupted, at least for coding AIs (independent of like-for-like quality concerns rightly mentioned elsewhere in this thread re: Excel/Python). I understand ChatGPT can do like a million other things, but so can Claude. Microsoft deliberately using competitors internally is the thing that their customers should pay attention to. Time to transform "Nobody gets fired for buying Microsoft" into "Nobody gets fired for buying what Microsoft buy", for those inclined.

doom2 8mo ago

I guess this is as good a thread as any to ask what the current meta is for agentic programming (in my case, as applied to data engineering). There are all these posts that make it to the front page talking about productivity gains but very few of them actually detail the setup that's working for the author, just which model is best. I guess it's like asking for people's vim configs, but hey, there are at least a few popular posts mainly around git/vim/terminal configs.

energy123 8mo ago
I push most work into chat interface (attach full codebase as a single file, paste in specs, describe what I want), then copy the tasklist from chat into codex. This is to reduce codex token usage to avoid breaching weekly limits. I'd use a more agent-heavy process if I didn't care about cost.
fragmede 8mo ago
There more stuff in mine, but at the top of my ~/.claude/CLAUDE.md file, I have: ## Important Instructions - update todo.md as items are completed **Commit to git after making code changes.** Check `git status` first - only commit if there are actual changes: ```bash # If not in a git repository, initialize it first: git init # Then commit changes: git add <FILES_UPDATED> # Be surgical - add only the changes you just made. git commit -m "Description of changes" This lets me have bite-sized git commits that I can marshall later, rather than having to wrangl git myself.
swordsith 8mo ago
In my opinion no frontier model is the best at everything, especially if you're having to catch it up with pre-existing information about your project or an esoteric scripting language, that being said, with Cursor you can try out all of the popular available models and get a feel for which do better with which tasks, in my experience - Codex is a okay model but use light thinking if you value your time, Gemini 3 flash is where its been at for me recently if I need to do big changes I go to that, And cursors model composer is good for making plans or doing refactors / making rules. Cursor gives you tools to make prompting feel like less of a repetition game, so you worry more about the task at hand and its been super efficient for me. I don't use proper version control so the fact it saves a history of every files dif's, and you can jump back easily in chats and regress the code base is the game changer.

datsci_est_2015 8mo ago

Thought this was going to be more about programmers, but it was actually about non technical users and Microsoft’s product development failure. One tidbit I’d disagree with is that only those using the bleeding edge AI tools are reaping the benefits. There seem to be a lot of highly specialized tools and a lot of specific configurations (and mystical incantations) to get them to work, and those are constantly changing and being updated. The bleeding edge is a dangerous place to be if you value your time (and sanity). Personally, as someone working on moderate-to-highly complex software (live inference of industrial IoT data), I can’t really open a merge / pull request for my colleagues to review unless I 100% understand what I’ve pushed, and can explain to them as well. My killer app for AI would just be a CLI that gets me to a commit based on moderately technical input: “Add this configuration variable for this entry point; split this class into two classes, one for each of the responsibilities that are currently crammed together; update the unit tests to reflect these changes, including splitting the tests for the old class into two different test classes; etc” But, all the hype of the bleeding edge is around abstracting away the entire coding process until you don’t even understand what code is being generated? Hard to see it as anything but a pipe dream. AI is useful, but it’s not a panacea - you can’t fire it and replace it when it fucks up.

georgeburdell 8mo ago
“Add this configuration variable for this entry point; split this class into two classes, one for each of the responsibilities that are currently crammed together; update the unit tests to reflect these changes, including splitting the tests for the old class into two different test classes; etc” Granted I'm way behind the curve, but is this not how actual engineers (and not influencers) are using it? I heavily micro-manage the implementation because my manager still expects me to know the code
- datsci_est_2015 8mo ago
  You could hardly believe that this is how actual engineers are using it if you only browsed HN. Maybe HN is only influencers?

tiangewu 8mo ago

Microsoft's failure around copilot in Excel gave my partner a very poor impression on AI's ability to help with financial tasks. It took a lot of convincing, but I finally got her to start using ChatGPT to help her write SQL and walk her through setting up some SaaS accounting software formulas. It worked so well now she's trying to find more applications at work. Claude code is too scary for her though. That will need to be in some Web UI before she feels comfortable giving it a try.

NookDavoos 8mo ago
Install "Claude for Excel" addon directly in the Excel itself. Works well.

protocolture 8mo ago

tl;dr: If you are trying to protect your IP from AI you probably use Copilot or nothing. If you have no IP to protect you are free to mess about.

fortran77 8mo ago

I know it's fun to bash Microsoft, but--while Claude is better, Microsoft's Copilot is far from "awful". I've used it productively with the VS Code integration for some esoteric projects: PIC PIO programming and Verilog.

mike_hearn 8mo ago
He's talking about the Copilot in other apps for non-programmers.

FilosofumRex 8mo ago

Generally speaking, if you're using your coding agent as your assistant inside your IDE, you're missing out on 80% of its benefits... If anything you should ask it how to do something and then act as its assistant on implementing it

PunchyHamster 8mo ago
also missing out on 80% of bugs

nickphx 8mo ago

Three kinds, those who do not use it.

anxoo 8mo ago
yes, the third kind of AI user. kind of similar to the three kinds of soccer players: offence, defence, and people who don't play soccer. thanks for the comment!

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athrowaway3z 8mo ago

> sandboxing agents is difficult I use this amazingly niche and hipster approach of giving the agent its own account, which through inconceivably highly complex arcane tweaking and configurations can lock down what they can and cant do. --- Can somebody for the love of god tell me why articles keep bringing up why this is so difficult?

deleted 8mo ago
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fragmede 8mo ago
It's a bunch of work, that takes a bunch of time, and I want it nowwwww-owwwww! ...is how I imagine that conversation goes.
NitpickLawyer 8mo ago
I have antigravity in its own account and that has worked pretty well so far. I also use devcontainers for the cli agents and that has also worked out well. It's one click away in my normal dev flow (I was using this anyway before for python projects).
chrisjj 8mo ago
Why? Because the purported benefit is to make everything easier and faster. Not safe.

viccis 8mo ago

>You can easily run Monte Carlo simulations Ah yes, Monte Carlo simulations, regular part of a finance team's objectives.

Leynos 8mo ago
https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance https://en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

nnevatie 8mo ago

I'd be very interested in seeing some statistics on what could be considered confidential material pasted on ChatGPT's chat interface. I think the results would be pretty shocking and I think mostly because the integrations to source services are abject messes.

Antibabelic 8mo ago
https://www.theregister.com/2025/10/07/gen_ai_shadow_it_secrets/ https://www.theregister.com/2025/10/07/gen_ai_shadow_it_secr... "With 45 percent of enterprise employees now using generative AI tools, 77 percent of these AI users have been copying and pasting data into their chatbot queries, the LayerX study says. A bit more than a fifth (22 percent) of these copy and paste operations include PII/PCI."
- chrisjj 8mo ago
  No worse than MS Office on web, then?

hereme888 8mo ago

I'm still trying to wrap my head over the past decade: useful AI, self operating vehicles, real AI robots, immersive VR, catching reusable rockets with chopsticks, and of course the flying cars. What will be the expected work output for the average future worker?

jsattler 8mo ago

Some years ago, I was at a conference and attended a very interesting talk. I don't remember the title of the talk, but what stuck with me was: "It's no longer the big beating the small, but the fast beating the slow". This talk was before all the AI hype. Working at a big company myself, I think this has never been more true. I think the question is, how to stay fast.

josters 8mo ago
And, to add to that, how to know when to slow down. Also, having worked at a big company myself, I think the question shifts towards "how to get fast" without compromising security, compliance etc.
swyx 8mo ago
this is generic startup advice (doesnt mean its not true). you level up a bit when you find instances where slow beat fast (see: Teams vs Slack)
chrisjj 8mo ago
> the fast beating the slow This includes to the bottom of a cliff, note.

crystal_revenge 8mo ago

One the most reliable BS detectors I've found is when you have to try to convince other people of your edge. If you have found a model that accurately predicts the stock market, you don't write a blog post about how brilliant you are, you keep it quiet and hope no one finds out while you rake in profits. I still can't figure out quite what motivates these "AI evangelist" types (unlike crypto evangelists who clearly create value for themselves when they create credibility), but if you really have a dramatically better way to solve problems, you don't need to waste your breath trying to convince people. The validity of your method will be obvious over time. I was just interviewing with a company building a foundation model for supposedly world changing coding assistants... but they still can't ship their product and find enough devs willing to relocate to SF. You would think if you actually had a game changing coding assistant, your number one advantage would be that you don't need to spend anything on devs and can ship 10x as fast as your competition. > First, you have the "power users", who are all in on adopting new AI technology - Claude Code, MCPs, skills, etc. Surprisingly, these people are often not very technical. It's not surprising to me at all that these people aren't very technical. For technical people code has never been the bottleneck. AI does reduce my time writing code but as a senior dev, writing code is a very small part of the problems I'm solving. I've never had to argue with anyone that using a calculator is a superior method of solving simple computational math problems than doing it by hand, or that using a stand mixer is more efficient than using a wooden spoon. If there was a competing bakery arguing that the wooden spoon was better, I wouldn't waste my time arguing about the stand mixer, I would just sell more pastry then them and worry about counting my money.

swordsith 8mo ago
Agreed. I think even though the term is stupid calling them cognitive improvement tools makes sense. The models will get better but most people will never learn how to effectively prompt or plan with a agentic model.
daliusd 8mo ago
I guess I am kind of "AI evangelist" in my circles (team, ecosystem and etc). I personally see benefits in "AI" both for side-projects and main work. However according to my last measurements improvements is not dramatic, it is huge (about 30%), but not dramatic. I share my insights purely to have less on my shoulders (if my team members can do more it is less for me to do).

camgunz 8mo ago

I think this article is generally insightful, but I don't think the author really knows if they one shotted the excel to python transformation or not. Maybe they elided an extensive testing phase, but otherwise big bugs could be lurking. Maybe it's not a big deal, or maybe it's a compliance model with severe financial penalties for non-compliance. I just personally don't kind these tradeoffs going implicit.

BolsunBacset 8mo ago
The author also said "almost" one shotted. Almost can mean a lot of things. I'm almost rich and almost handsome. But just not there...

PunchyHamster 8mo ago

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are interested only in results, and are not interested in knowing more about the topic or honing their skills in the topic The second group is one that thinks talking to a chatbot will replace senior developer

Aardwolf 8mo ago
The same person might be both kinds of users, depending on the topic or just the time of the day
- mathgeek 8mo ago
  It's almost as if categorization is often an oversimplification.
sevenzero 8mo ago
I started to outsource thinking at my job as my company made it very clear that they do not want/cant afford thinking engineers. Thinking requires time and they want to deliver quickly. So they cater towards the very realistic deadlines our PMs set for features (/s). Funnily enough the features have to be implemented ASAP according to the customers, but the customer feedback takes like 6 months due to them using the new feature for the first time 6 months after delivery. I just dont care anymore. Gonna leave the learning part up to my time off, but getting generally tired of the industry as a whole, so just putting in minimal effort to pay my bills until things explode or get better. So for me its definitely outsourcing thinking at work.
- gloomyday 8mo ago
  This is a fatalistic attitude, but I can totally get behind. It has become harder to associate my job with contributing with society.

anal_reactor 8mo ago

> This effectively leads to a situation where smaller company employees are able to be so much more productive than the equivalent at an enterprise. It often used to be that people at small companies really envied the resources & teams that their larger competitors had access to - but increasingly I think the pendulum is swinging the other way. Small companies are more agile and innovative while corporations often just shuffle papers around. Wow, what a bold claim, never seen before in the entire history of economics.

deafpolygon 8mo ago

There’s also an emerging group of users (such as myself) who essentially use it primarily as an “on-demand” teacher and not as a productivity tool. I am learning software development without having it generate code for me—preferring to have it explain each thing line-by-line. But… it’s not only for learning development, but I can query it for historical information and have it point me to the source of the information (so I can read the primary sources as much as possible). It allows me to customize the things I want to learn at my own pace, while also allowing me to diverge for a moment from the learning material. I have found it invaluable… and so far, Gemini has been pretty good at this (probably owing to the integration of Google search into Gemini). It lets me cut through the SEO crap that has plagued search engines in recent years.

wjholden 8mo ago

I remember a colleague jumping through hoops trying to get Python installed on an enterprise computer. We never did get to a yes and resorted to using PowerShell instead. The policy constraints at enterprises that this author describes are very real and very harmful. Perhaps the wildest thing to me is how you'll have senior leaders in a company talking about innovation, but their middle managers actively undermine change out of fear of liability. So many enterprise IT employees are really just trying to avoid punishment that their organization cannot try new things without substantial top-down efforts to accept risk.

chrisjj 8mo ago
> The policy constraints at enterprises that this author describes are very real and very harmful. This is like saying prison bars are harmful. It depends which side you are on.
- wjholden 8mo ago
  That is an insightful response, I may quote you on this.

fauigerzigerk 8mo ago

>What I've come to realise is that the power of having a bash sandbox with a programming language and API access to systems, combined with an agentic harness, results in outrageously good results for non technical users. It can effectively replace nearly every standard productivity app out there - both classic Microsoft Office style ones - and also web apps. I very much doubt that tinkering with a non-repeatable, probabilistic process is how most non-technical users will routinely use software. I can imagine power users taking this approach to _create_ or extend productivity tools for themselves and others, just like they have been doing with Excel for decades. It will not _replace_ productivity tools for most non-technical users.

deleted 8mo ago
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chrisjj 8mo ago

> Thirdly, this all needs to be wrapped up in some sort of secure mechanism Putting that first would have saved the bother of putting the second and third.

veunes 8mo ago

This is the birth of Shadow AI, and it’s going to be bigger than Shadow IT ever was in the 2000s Back then, employees were secretly installing Excel macros and Dropbox just to get work done faster. Now they’re quietly running Claude Code in the terminal because the official Copilot can’t even forma a CSV properly. CISOs are terrified right now and that’s understandable. Non-technical people with root access and agents that write code are a security nightmare. But trying to ban this outright will only push your most effective employees to places where they’re allowed to "fly"

AdamN 8mo ago
"they’re quietly running Claude Code" ... with their tokens or even worse full on usernames and passwords that have write/execute privileges.

anonymousDan 8mo ago

'some sort of security' - oh great, security as an afterthought.

chrisjj 8mo ago

> It can effectively replace nearly every standard productivity app out there May we see the "agentic" replacement for Word, please?

srinath693 8mo ago

The real divide isn't technical vs. non-technical: it's people with new problems vs. people maintaining old solutions. AI is incredible at generating first drafts of anything. It's terrible at understanding why the existing thing is the way it is.

maffyoo 8mo ago

this seems reasonable but isn't the conclusion a statement what we already know. These tools are really powerful, but with the ability to cause significant pain, need organisations to adapt, so that they can make best use of them but this is fraught with security problems. AI looks a lot like a technology problem but ultimately, to most small businesses, it's a procurement and change management problem. Also (I appreciate the authors message here but..) "Excel on the finance side is remarkably limiting when you start getting used to the power of a full programming ecosystem like Python" With the addition of lambdas Excel formulae are Turing complete. no more need for VBA in a (mostly) functional environment. Also on this, Claude for Excel needs a lot of work (as does any tool working with financial models) if you have ever used them in anger I dont think you'll be relying on them with your non-technical finance manager for a while...

rob 8mo ago

The number of people I've run into with a non-technical background that think ChatGPT is the definitive end-all for AI is very high. Most just don't know anything else even exists. I do wonder how long they'll be able to use this to their advantage before something "else" comes along. Like how IE had the largest market share before Chrome and other alternatives started catching up. Then again, some markets like YouTube still haven't had any real serious alternatives. Maybe ChatGPT will always be number one in the consumer eyes.

okokwhatever 8mo ago

You can see the fear all around this thread. And, tbh, it makes total sense. There is nothing we can do to stop this dropping ball, we can accept it or leave the room but the industry has changed for all of us. I mean, you can use it one way or another but the concept of critical thinking is our only survival tool if your relaying on a it job this days. How long it will last? Who cares, we're fucked anyways...

enemyz0r 8mo ago
Yep

iqandjoke 8mo ago

It is like saying Apple is using Claude Code internally while selling you to use Apple Intelligence https://x.com/tbpn/status/2016911797656367199 https://x.com/tbpn/status/2016911797656367199

mrbluecoat 8mo ago

notepad0x90 8mo ago

I suspect there are much more than two kinds. there is a varying degree of understanding what these tools are capable of, and that multiplied by what people need and how much they care about outcomes and consequences is the number of "kinds" of AI users. Let's take the group of developers (to keep it simple) that have a deep understanding of LLMs and how they work. Even then, some don't care if it generates entire codebases for them, some know there will be bugs in it, they just don't care. Some care, but they know their job is to make their project managers happy. Others don't have apathy or pressure like that, but they'll still use it in the same way, because for one reason or the other it saves them time. I'm probably missing more examples, but it is the same usage, but different motivations, people, and environments.

fny 8mo ago

Software engineers don't understand how user hostile all these AI gizmos are. Terminals are scary. AI running local code is scary. Random Github software is scary. And in my experience, normies are far more security paranoid than developers when it comes to AI.

riskable 8mo ago
Normies have a much more realistic take on AI than technical people or semi-technical "power users": * They LOVE image-generating AI and AI that messes with their own photos/videos. * They will ask ChatGPT, Gemini, etc and just believe the result. * They will ask Copilot to help them make a formula in Excel and be happy to be done. The common theme here is they don't care. To them, AI is just a neat thing. It's not a huge difference in their lives. They don't think about the environmental impact much unless someone tells them it's bad, via a high-quality video stream that itself was vastly worse for the environment than any AI conversation or image generation ever could be. They will play a game 100% made by AI because their friend said it was fun. They don't care that some AAA publisher lost a sale on their "human made for sure, just trust us :nod:" identical game because the bored person was able to pull of something good enough with little effort (and better design decisions). They also don't care if some article or book or whatever was written partially or entirely by AI as long as it's good. The AI part just isn't important to them. Not even a little bit!
- hxugufjfjf 8mo ago
  Its kind of funny how it’s the exact same discussion as we used to have about privacy in the advent of social media. "I’m not worried, I got nothing to hide!" The convenience benefits of Facebook (in the beginning, likely less nowadays) massively outweighed the privacy concerns of the layman or woman.

riazrizvi 8mo ago

I think the main divisions are 1) people who are using it in fields they have little knowledge of to get basic competence, 2) the same people using it for advanced competence who are kidding themselves, 3) experts who are battling it in their own fields to finally get better answers than they could without it. The first group are like Improved-Generalists. The third are Improved-Specialists. The second are delusional hype jockeys that drive the dumb talking points that extrapolate up the whazoo what AI is going to do and whatnot.

darepublic 8mo ago

On mobile Firefox the subscribe modal extends past the width of the viewport. I assume the close button is hanging out there outside of view. For all the peddlers of the astonishing power of agents.. why is your software subpar. This sounds like snark but I'm actually serious. Anyone crowing about the productivity gains I expect to see fast high quality software

waffletower 8mo ago

When confined to a Github Copilot Business license, you do have options, as the license does provide access to frontier Anthropic and Google models in addition to its other offerings. Unfortunately it will not work directly with Claude Code without proxy server hacks, but Opencode is an option, and I am interested in learning about others (save for Aider, which I have tried and discarded).

the__alchemist 8mo ago

I've made a similar observation. I'm clearly in camp #2: No agents, and use ChatGPT or Gemini to ask specific questions, and feed it only the context I want it to have. I have a parallel observation: Many people use code editors that have weak introspection and refactoring ability compared to IDEs like JetBrains'. This includes VSCode, Zed, Emacs etc. I have a suspicion there is a big overlap between this and Group 1. It is wild to me that people are generating AI code while skipping in-IDE error checking, deterministic autocomplete, and refactoring.

oakhaven 8mo ago

I really like that this article explained the title thesis in the first 4 paragraphs. At that point you can decide if you agree or if your want to read on. No unnecessary fluff baiting the reader to read the whole thing in order to find out what are the two kinds of users. More writing like this.

doginasuit 8mo ago

Here's how I'd break down the two types of users: People who are using AI to teach themselves how to work in the domain they are interested in, and people who are relying on AI to do all or most of the heavy lifting. I'd argue that the people using AI most effectively are in the mostly-chatters group that the author defines, and specifically they are using the AI to understand the domain on a deeper level. The "power users" are heading for a dead end, they will arrive as soon as AI is capable of figuring out what is actually valuable to people in the given domain, not generally a difficult problem to solve. These power users will eventually be outclassed by AIs that can self-navigate. But I would argue that a human that has a rich understanding of the domain will still beat self-navigating AI for a long time to come.

satiated_grue 8mo ago

This seems to be a bit of an echo of the 1980s and the power shift brought about by the introduction of the IBM PC - the decentralization of control over data and processes from the walled garden of the computer room to the people at their desks with VisiCalc and BASIC, and then the explosion of productivity software.

emeraudelinton 8mo ago

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kajolshah_bt 8mo ago

I see this split clearly in real products: some users treat AI like a tool to support their workflow, others treat it like a replacement for thinking. The first group uses AI to reduce repetitive work and interprets results critically; the second group abandons it when outcomes aren’t perfect. In practice, the users who end up valuing AI are the ones who see it as an assistant, not an oracle. That distinction matters because it shapes how you design UI, fallback flows, and trust signals. If the interface assumes perfect output, retention drops; if it assumes collaboration with the user, retention improves.