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My AI Adoption Journey

mitchellh.com

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Re: My AI Adoption Journey

#111

Post by blibble »

throwup238 wrote: post #105
AlotOfReading wrote: post #100

Earlier quoted context omitted.

Don't take this as criticizing LLMs as a whole, but architects also don't call themselves engineers. Engineers are an entirely distinct set of roles that among other things validate the plan in its totality, not only the "new" 1/5th. Our job spans both of these. "Architect" is actually a whole career progression of people with different responsibilities. The bottom rung used to be the draftsmen, people usually withou…

> Engineers are an entirely distinct set of roles that among other things validate the plan in its totality, not only the "new" 1/5th. Our job spans both of these. Where this analogy breaks down is that the work you’re describing is done by Professional Engineers that have strict licensing and are (criminally) liable for the end result of the plans they approve. That is an entirely different role from the army of civ…

> Where this analogy breaks down is that the work you’re describing is done by Professional Engineers that have strict licensing and are (criminally) liable for the end result of the plans they approve.

there are plenty of software engineers that work in regulated industries, with individual licensing, criminal liability, and the ability to be struck off and banned from the industry by the regulator

... such as myself

Re: My AI Adoption Journey

#112

Post by AloysB »

datsci_est_2015 wrote: post #88
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 b…

Give it a read, he mentions briefly how he uses for PR triages and resolving GH issues.

He doesn't go in details, but there is a bit:

> Issue and PR triage/review. Agents are good at using gh (GitHub CLI), so I manually scripted a quick way to spin up a bunch in parallel to triage issues. I would NOT allow agents to respond, I just wanted reports the next day to try to guide me towards high value or low effort tasks.

> More specifically, I would start each day by taking the results of my prior night's triage agents, filter them manually to find the issues that an agent will almost certainly solve well, and then keep them going in the background (one at a time, not in parallel).

This is a short excerpt, this article is worth reading. Very grounded and balanced.

Re: My AI Adoption Journey

#113

Post by noosphr »

I've been building systems like what the OP is using since gpt3 came out.

This is the honeymoon phase. You're learning the ins and outs of the specific model you're using and becoming more productive. It's magical. Nothing can stop you. Then you might not be improving as fast as you did at the start, but things are getting better every day. Or maybe every week. But it's heaps better than doing it by hand because you have so much mental capacity left.

Then a new release comes up. An arbitrary fraction of your hard earned intuition is not only useless but actively harmful to getting good results with the new models. Worse you will never know which part it is without unlearning everything you learned and starting over again.

I've had to learn the quirks of three generations of frontier families now. It's not worth the hassle. I've gone back to managing the context window in Emacs because I can't be bothered to learn how to deal with another model family that will be thrown out in six months. Copy and paste is the universal interface and being able to do surgery on the chat history is still better than whatever tooling is out there.

Unironically learning vim or Emacs and the standard Unix code tools is still the best thing you can do to level up your llm usage.

Re: My AI Adoption Journey

#114

Post by tudelo »

noosphr wrote: post #113

I've been building systems like what the OP is using since gpt3 came out. This is the honeymoon phase. You're learning the ins and outs of the specific model you're using and becoming more productive. It's magical. Nothing can stop you. Then you might not be improving as fast as you did at the start, but things are getting better every day. Or maybe every week. But it's heaps better than doing it by hand because you…

First off, appreciate you sharing your perspective. I just have a few questions.

> I've gone back to managing the context window in Emacs because I can't be bothered to learn how to deal with another model family that will be thrown out in six months.

Can you expand more on what you mean by that? I'm a bit of a noob on llm enabled dev work. Do you mean that you will kick off new sessions and provide a context that you manage yourself instead of relying on a longer running session to keep relevant information?

> Unironically learning vim or Emacs and the standard Unix code tools is still the best thing you can do to level up your llm usage.

I appreciate your insight but I'm failing to understand how exactly knowing these tools increases performance of llms. Is it because you can more precisely direct them via prompts?

Re: My AI Adoption Journey

#116

Post by atomicnumber3 »

keyle wrote: post #79
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…

Architects went from drawing everything on paper, to using CAD products over a generation. That's a lot of years! They're still called architects. Our tooling just had a refresh in less than 3 years and it leaves heads spinning. People are confused, fighting for or against it. Torn even between 2025 to 2026. I know I was. People need a way to describe it from 'agentic coding' to 'vibe coding' to 'modern AI assisted s…

"When was the last time you reviewed the machine code produced by a compiler?"

Compilers will produce working output given working input literally 100% of my time in my career. I've never personally found a compiler bug.

Meanwhile AI can't be trusted to give me a recipe for potato soup. That is to say, I would under no circumstances blindly follow the output of an LLM I asked to make soup. While I have, every day of my life, gladly sent all of the compiler output to the CPU without ever checking it.

The compiler metaphor is simply incorrect and people trying to say LLMs compile English into code insult compiler devs and English speakers alike.

Re: My AI Adoption Journey

#117

Post by dotancohen »

IhateAI wrote: post #103
tptacek wrote: post #94

Earlier quoted context omitted.

So read the code.

[flagged]

So you have a hobby.

I have a profession. Therefore I evaluate new tools. Agents coding I've introduced into my auxiliary tool forgings (one-off bash scripts) and personal projects, and I'm just now comfortable to introduce into my professional work. But I still evaluate every line.

Re: My AI Adoption Journey

#118

Post by sunshinekitty »

noosphr wrote: post #113

I've been building systems like what the OP is using since gpt3 came out. This is the honeymoon phase. You're learning the ins and outs of the specific model you're using and becoming more productive. It's magical. Nothing can stop you. Then you might not be improving as fast as you did at the start, but things are getting better every day. Or maybe every week. But it's heaps better than doing it by hand because you…

> I've been building systems like what the OP is using since pgt3 came out.

OP is also a founder of Hashicorp, so.. lol.

> This is the honeymoon phase.

No offense but you come across as if you didn’t read the article.

Re: My AI Adoption Journey

#119

Post by re-thc »

chrysoprace wrote: post #93
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 think for a lot of people the turn off is the constant churn and the hype cycle. For a lot of people, they just want to get things done and not have to constantly keep on top of what's new or SOTA. Are we still using MCPs or are we using Skills now? Not long ago you had to know MCP or you'd be left behind and you definitely need to know MCP UI or you'll be left behind. I think. It just becomes really tiring, especi…

> For a lot of people, they just want to get things done and not have to constantly keep on top of what's new or SOTA

That hasn’t been tech for a long time.

Frontend has been changing forever. React and friends have new releases all the time. Node has new package managers and even Deno and Bun. AWS keeps changing things.

Re: My AI Adoption Journey

#120

Post by noosphr »

tudelo wrote: post #114
noosphr wrote: post #113

I've been building systems like what the OP is using since gpt3 came out. This is the honeymoon phase. You're learning the ins and outs of the specific model you're using and becoming more productive. It's magical. Nothing can stop you. Then you might not be improving as fast as you did at the start, but things are getting better every day. Or maybe every week. But it's heaps better than doing it by hand because you…

First off, appreciate you sharing your perspective. I just have a few questions. > I've gone back to managing the context window in Emacs because I can't be bothered to learn how to deal with another model family that will be thrown out in six months. Can you expand more on what you mean by that? I'm a bit of a noob on llm enabled dev work. Do you mean that you will kick off new sessions and provide a context that yo…

LLMs work on text and nothing else. There isn't any magic there. Just a limited context window on which the model will keep predicting the next token until it decides that it's predicted enough and stop.

All the tooling is there to manage that context for you. It works, to a degree, then stops working. Your intuition is there to decide when it stops working. This intuition gets outdated with each new release of the frontier model and changes in the tooling.

The stateless API with a human deciding what to feed it is much more efficient in both cost and time as long as you're only running a single agent. I've yet to see anyone use multiple agents to generate code successfully (but I have used agent swarms for unstructured knowledge retrieval).

The Unix tools are there for you to progra-manually search and edit the code base copy/paste into the context that you will send. Outside of Emacs (and possibly vim) with the ability to have dozens of ephemeral buffers open to modify their output I don't imagine they will be very useful.

Or to quote the SICP lectures: The magic is that there is no magic.

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