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Two kinds of AI users are emerging

martinalderson.com

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Re: Two kinds of AI users are emerging

#111

Post by holoduke »

decimalenough wrote: post #22
defrost wrote: post #12

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 simul…

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…

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

Re: Two kinds of AI users are emerging

#112

Post by pprotas »

defrost wrote: post #63
tharkun__ wrote: post #38

Earlier quoted context omitted.

This is a pet peeve of mine at work. Any and I mean any statistic someone throws at me I will try and dig in. And if I'm able to, I will usually find that something is very wrong somewhere. As in, the underlying data is usually just wrong, invalidating the whole thing or the data is reasonably sound but the person doing the analysis is making incorrect assumptions about parts of the data and then drawing incorrect co…

I've frequently found, over a few decades, that numerical systems are cyclically 'corrected' until results and performance match prior expectations. There are often more errors. Sometimes the actual results are wildly different in reality to what a model expects .. but the data treatment has been bug hunted until it does what was expected .. and then attention fades away.

Or the company just changes the definition of success, so that the metrics (that used to be bad last quarter) are suddenly good

Re: Two kinds of AI users are emerging

#113

Post by galaxyLogic »

Gigachad wrote: post #75
danpalmer wrote: post #29

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 b…

Similar experience. I love using Gemini to set up my home server, it can debug issues and generate simple docker compose files faster than I could have done myself. But at work on the 10 year old Rails app, I find it so much easier to just write all the code myself than to work out what prompt would work and then review/modify the results.

This makes me think how AI turns SW development upside down. In traditonal development we write code which is the answer to our problems. With AI we write questions and get the answers. Neither is easy, finding the correct questions can be a lot fo work, whereas if you have some existing code you already have the answers, but you may not have the questions (= "specs") written down anywhere, at least not very well, typically.

Re: Two kinds of AI users are emerging

#114

Post by fragmede »

irishcoffee wrote: post #83
smuhakg wrote: post #37

> 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 parse…

> 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.…

what would you have used?

Re: Two kinds of AI users are emerging

#115

Post by nnevatie »

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.

Re: Two kinds of AI users are emerging

#116

Post by hereme888 »

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?

Re: Two kinds of AI users are emerging

#117

Post by Antibabelic »

nnevatie wrote: post #115

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.

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."

Re: Two kinds of AI users are emerging

#118

Post by fragmede »

athrowaway3z wrote: post #99

> 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?

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.

Re: Two kinds of AI users are emerging

#119

Post by fragmede »

doom2 wrote: post #64

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…

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 
    # 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.

Re: Two kinds of AI users are emerging

#120

Post by dust42 »

somat wrote: post #104
danpalmer wrote: post #29

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 b…

Isn't this true of any greenfield project? with or without generative models. The first few days are amazingly productive. and then features and fixes get slower and slower. And you get to see how good an engineer you really are, as your initial architecture starts straining under the demands of changing real world requirements and you hope it holds together long enough to ship something. "I could make that in a week…

From personal experience I'd like to add the last 5% take 95% of the time - at least if you are working on a make over of an old legacy system.
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