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My AI Adoption Journey

mitchellh.com

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Re: My AI Adoption Journey

#81

Post by protocolture »

EastLondonCoder wrote: post #23

This matches my experience, especially "don’t draw the owl" and the harness-engineering idea. The failure mode I kept hitting wasn’t just "it makes mistakes", it was drift: it can stay locally plausible while slowly walking away from the real constraints of the repo. The output still sounds confident, so you don’t notice until you run into reality (tests, runtime behaviour, perf, ops, UX). What ended up working for m…

>The failure mode I kept hitting wasn’t just "it makes mistakes", it was drift: it can stay locally plausible while slowly walking away from the real constraints of the repo. The output still sounds confident, so you don’t notice until you run into reality (tests, runtime behaviour, perf, ops, UX).

Yeah I would get patterns where, initial prototypes were promising, then we developed something that was 90% close to design goals, and then as we try to push in the last 10%, drift would start breaking down, or even just forgetting, the 90%.

So I would start getting to 90% and basically starting a new project with that as the baseline to add to.

Re: My AI Adoption Journey

#82

Post by e40 »

For those of working on large proprietary, in fringe languages as well, what can we do? Upload all the source code to the cloud model? I am really wary of giving it a million lines of code it’s never seen.

Re: My AI Adoption Journey

#83

Post by majormajor »

libraryofbabel wrote: post #53

This is such a lovely balanced thoughtful refreshingly hype-free post to read. 2025 really was the year when things shifted and many first-rate developers (often previously AI skeptics, as Mitchell was) found the tools had actually got good enough that they could incorporate AI agents into their workflows. It's a shame that AI coding tools have become such a polarizing issue among developers. I understand the reasons…

GPT-4 showed the potential but the automated workflows (context management, loops, test-running) and pure execution speed to handle all that "reasoning"/workflows (remember watching characters pop in slowly in GPT-4 streaming API response calls) are gamechangers.

The workflow automation and better (and model-directed) context management are all obvious in retrospect but a lot of people (like myself) were instead focused on IDE integration and such vs `grep` and the like. Maybe multi-agent with task boards is the next thing, but it feels like that might also start to outrun the ability to sensibly design and test new features for non-greenfield/non-port projects. Who knows yet.

I think it's still very valuable for someone to dig in to the underlying models periodically (insomuch as the APIs even expose the same level of raw stuff anymore) to get a feeling for what's reliable to one-shot vs what's easily correctable by a "ran the tests, saw it was wrong, fixed it" loop. If you don't have a good sense of that, it's easy to get overambitious and end up with something you don't like if you're the sort of person who cares at all about what the code looks like.

Re: My AI Adoption Journey

#84

Post by majormajor »

Lich wrote: post #73
libraryofbabel wrote: post #53

This is such a lovely balanced thoughtful refreshingly hype-free post to read. 2025 really was the year when things shifted and many first-rate developers (often previously AI skeptics, as Mitchell was) found the tools had actually got good enough that they could incorporate AI agents into their workflows. It's a shame that AI coding tools have become such a polarizing issue among developers. I understand the reasons…

Is there any reason to use Claude Code specifically over Codex or Gemini? I’ve found the both Codex and Gemini similar in results, but I never tried Claude because of I keep hearing usage runs out so fast on pro plans and there’s no free trial for the CLI.

IME Gemini is pretty slow in comparison to Claude - but hey, it's super cheap at least.

But that speed makes a pretty significant difference in experience.

If you wait a couple minutes and then give the model a bunch of feedback about what you want done differently, and then have to wait again, it gets annoying fast.

If the feedback loop is much tighter things feel much more engaging. Cursor is also good at this (investigate and plan using slower/pricier models, implement using fast+cheap ones).

Re: My AI Adoption Journey

#85

Post by bthornbury »

AI is getting to the game-changing point. We need more hand-written reflections on how individuals are managing to get productivity gains for real (not a vibe coded app) software engineering.

Re: My AI Adoption Journey

#86

Post by mapontosevenths »

mjr00 wrote: post #8

> Break down sessions into separate clear, actionable tasks. Don't try to "draw the owl" in one mega session. This is the key one I think. At one extreme you can tell an agent "write a for loop that iterates over the variable `numbers` and computes the sum" and they'll do this successfully, but the scope is so small there's not much point in using an LLM. On the other extreme you can tell an agent "make me an app tha…

> Break down sessions into separate clear, actionable tasks.

What this misses, of course, is that you can just have the agent do this too. Agent's are great at making project plans, especially if you give them a template to follow.

Re: My AI Adoption Journey

#87

Post by FeteCommuniste »

henry_bone wrote: post #78

LLMs are not for me. My position is that the advantage we humans have over the rest of the natural world, is our minds. Our ability to think, create and express ideas is what separates us from the rest of the animal kingdom. Once we give that over to "thinking" machines, we weaken ourselves, both individually and as a species. That said, I've given it a go. I used zed, which I think is a pretty great tool. I bought a…

AI adoption is being heavily pushed at my work and personally I do use it, but only for the really "boilerplate-y" kinds of code I've already written hundreds of times before. I see it as a way to offload the more "typing-intensive" parts of coding (where the bottleneck is literally just my WPM on the keyboard) so I have more time to spend on the trickier "thinking-intensive" parts.

Re: My AI Adoption Journey

#88

Post by datsci_est_2015 »

libraryofbabel wrote: post #53

This is such a lovely balanced thoughtful refreshingly hype-free post to read. 2025 really was the year when things shifted and many first-rate developers (often previously AI skeptics, as Mitchell was) found the tools had actually got good enough that they could incorporate AI agents into their workflows. It's a shame that AI coding tools have become such a polarizing issue among developers. I understand the reasons…

I skimmed over it, and didn’t find any discussion of:

  - Pull requests
  - Merge requests
  - Code review
I feel like I’m taking crazy pills. Are SWE supposed to move away from code review, one of the core activities for the profession? Code review is as fundamental for SWE as double entry is for accounting.

Yes, we know that functional code can get generated at incredible speeds. Yes, we know that apps and what not can be bootstrapped from nothing by “agentic coding”.

We need to read this code, right? How can I deliver code to my company without security and reliability guarantees that, at their core, come from me knowing what I’m delivering line-by-line?

Re: My AI Adoption Journey

#89

Post by pixl97 »

ricardobeat wrote: post #75
EastLondonCoder wrote: post #23

This matches my experience, especially "don’t draw the owl" and the harness-engineering idea. The failure mode I kept hitting wasn’t just "it makes mistakes", it was drift: it can stay locally plausible while slowly walking away from the real constraints of the repo. The output still sounds confident, so you don’t notice until you run into reality (tests, runtime behaviour, perf, ops, UX). What ended up working for m…

No harm meant, but your writing is very reminiscent of an LLM. It is great actually, there is just something about it - "it wasn't.. it was", "it stopped being.. and started". Claude and ChatGPT seem to love these juxtapositions. The triplets on every other sentence. I think you are a couple em-dashes away from being accused of being a bot. These patterns seem to be picking up speed in the general population; makes t…

>makes the human race seem quite easily hackable.

If the human race were not hackable then society would not exist, we'd be the unchanging crocodiles of the last few hundred million years.

Have you ever found yourself speaking a meme? Had a catchy toon repeating in your head? Started spouting nation state level propaganda? Found yourself in crowd trying to burn a witch at the stake?

Hacking the flow of human thought isn't that hard, especially across populations. Hacking any one particular humans thoughts is harder unless you have a lot of information on them.

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