* 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

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.

  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.

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.

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.

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.

“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.

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"

I would argue if they're using all that tooling, they _are_ technical users.

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.

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.

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.

I think the results would be pretty shocking and I think mostly because the integrations to source services are abject messes.

Seems like Nadella is having his Baller moment

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.

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.

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.

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.

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.

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.

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...

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.

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.

Putting that first would have saved the bother of putting the second and third.

May we see the "agentic" replacement for Word, please?

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.

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.

What will be the expected work output for the average future worker?

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.

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.

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Can somebody for the love of god tell me why articles keep bringing up why this is so difficult?

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

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.

Ah yes, Monte Carlo simulations, regular part of a finance team's objectives.

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.