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My AI Adoption Journey

mitchellh.com

31–40 of 420 posts

Re: My AI Adoption Journey

#31

For the AI skeptics reading this, there is an overwhelming probability that Mitchell is a better developer than you. If he gets value out of these tools you should think about why you can't.

The AI skeptics instead stick to hard data, which so far shows a 19% reduction in productivity when using AI.

Re: My AI Adoption Journey

#32
post #26

[flagged]

"Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something."

"Don't be snarky."

"Don't be curmudgeonly. Thoughtful criticism is fine, but please don't be rigidly or generically negative."

https://news.ycombinator.com/newsguidelines.html

Re: My AI Adoption Journey

#34
post #11
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…

This is actually an aspect of using AI tools I really enjoy: Forming an educated intuition about what the tool is good at, and tastefully framing and scoping the tasks I give it to get better results. It cognitively feels very similar to other classic programming activities, like modularization at any level from architecture to code units/functions, thoughtfully choosing how to lay out and chunk things. It's always b…

I agree that framing and scoping tasks is becoming a real joy. The great thing about this strategy is there's a point at which you can scope something small enough that it's hard for the AI to get it wrong and it's easy enough for you as a human to comprehend what it's done and verify that it's correct.

I'm starting to think of projects now as a tree structure where the overall architecture of the system is the main trunk and from there you have the sub-modules, and eventually you get to implementations of functions and classes. The goal of the human in working with the coding agent is to have full editorial control of the main trunk and main sub-modules and delegate as much of the smaller branches as possible.

Sometimes you're still working out the higher-level architecture, too, and you can use the agent to prototype the smaller bits and pieces which will inform the decisions you make about how the higher-level stuff should operate.

Re: My AI Adoption Journey

#35
> babysitting my kind of stupid and yet mysteriously productive robot friend

LOL, been there, done that. It is much less frustrating and demoralizing than babysitting your kind of stupid colleague though. (Thankfully, I don't have any of those anymore. But at previous big companies? Oh man, if only their commits were ONLY as bad as a bad AI commit.)

Re: My AI Adoption Journey

#36
This seems like a pretty reasonable approach that charts a course between skepticism and "it's a miracle".

I wonder how much all this costs on a monthly basis?

Re: My AI Adoption Journey

#37

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…

This is the most common answer from people that are rocking and rolling with AI tools but I cannot help but wonder how is this different from how we should have built software all along. I know I have been (after 10+ years…)

I think you are right, the secret is that there is no secret. The projects I have been involved with thats been most successful was using these techniques. I also think experience helps because you develop a sense that very quickly knows if the model wants to go in a wonky direction and how a good spec looks like.

With where the models are right now you still need a human in the loop to make sure you end up with code you (and your organisation) actually understands. The bottle neck has gone from writing code to reading code.

Re: My AI Adoption Journey

#38
There are so many stories about how people use agentic AI but they rarely post how much they spend. Before I can even consider it, I need to know how it will cost me per month. I'm currently using one pro subscription and it's already quite expensive for me. What are people doing, burning hundreds of dollars per month? Do they also evaluate how much value they get out of it?

Re: My AI Adoption Journey

#39
post #36

This seems like a pretty reasonable approach that charts a course between skepticism and "it's a miracle". I wonder how much all this costs on a monthly basis?

As long as we're on the same page that what he's describing is itself a miracle.
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