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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

#71

Post by cortesoft »

EnPissant wrote: post #61
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…

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.

I solve this problem by pointing Claude at existing code bases when I start a project, and tell it to use that approach.

Re: Two kinds of AI users are emerging

#72

Post by danielbln »

nebula8804 wrote: post #20
simmerup wrote: post #2

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

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+).

A decade+ is wishful copium.

Re: Two kinds of AI users are emerging

#73

Post by georgeburdell »

datsci_est_2015 wrote: post #67

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 changin…

“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

Re: Two kinds of AI users are emerging

#75

Post by Gigachad »

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.

Re: Two kinds of AI users are emerging

#76

Post by tonfreed »

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…

My observations match this. I can get fresh things done very quickly, but when I start getting into the weeds I eventually get too frustrated with babysitting the LLM to keep using it.

Re: Two kinds of AI users are emerging

#77

Post by Gigachad »

s-lambert wrote: post #9

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 s…

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.

Re: Two kinds of AI users are emerging

#78

Post by Gigachad »

with wrote: post #50

> 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 de…

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.

Re: Two kinds of AI users are emerging

#79

Post by singingbard »

majormajor wrote: post #24
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…

One of the dirty secrets of a lot of these "code adjacent" areas is that they have very little testing. If a data science team modeled something incorrectly in their simulation, who's gonna catch it? Usually nobody. At least not until it's too late. Will you say "this doesn't look plausible" about the output? Or maybe you'll be too worried about getting chided for "not being data driven" enough. If an exec tells an i…

I did a fair about of data analysis and deciding when or if my report was correct was a huge adrenaline rush.

A huge test for me was to have people review my analyses and poke holes. You feel good when your last 50 reports didn’t have a single thing anyone could point out.

I’ve been seeing a lot of people try to build analyses with AI who haven’t been burned with the “just because it sounds correct doesn’t mean it’s right” dilemma who haven’t realized what it takes before you can stamp your name on an analysis.

Re: Two kinds of AI users are emerging

#80

Post by stego-tech »

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…

Enterprise IT dinosaur here, seconding this perspective and the author’s.

When I needed to bash out a quick Hashicorp Packer buildfile without prior experience beyond a bit of Vault and Terraform, local AI was a godsend at getting me 80% of the way there in seconds. I could read it, edit it, test it, and move much faster than Packer’s own thin “getting started” guide offered. The net result was zero prior knowledge to a hardened OS image and repeatable pipeline in under a week.

On the flip side, asking a chatbot about my GPOs? Or trusting it to change network firewalls and segmentation rules? Letting it run wild in the existing house of cards at the core of most enterprises? Absolutely hell no the fuck not. The longer something exists, the more likely a chatbot is to fuck it up by simple virtue of how they’re trained (pattern matching and prediction) versus how infrastructure ages (the older it is or the more often it changes, the less likely it is to be predictable), and I don’t see that changing with LLMs.

LLMs really are a game changer for my personal sales pitch of being a single dinosaur army for IT in small to medium-sized enterprises.

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