Two kinds of AI users are emerging. The gap between them is astonishing

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.

> 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.

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.

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 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.

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

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.

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.

> Microsoft itself is rolling out Claude Code to internal teams

Seems like Nadella is having his Baller moment

> 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.

> 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.

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?

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

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.