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My AI Adoption Journey

mitchellh.com

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Re: My AI Adoption Journey

#231

Post by snayan »

lelanthran wrote: post #203
snayan wrote: post #200

Earlier quoted context omitted.

I don't see a flaw, I think you're just gatekeeping software creation. Anyone can pick up some CAD software and design a house if they so desire. Is the town going to let you build it without a certified engineer/architect signing off? Fuck no. But we don't lock down CAD software. And presumably, mission critical software is still going to be stamped off on by a certified engineer of some sort.

> Anyone can pick up some CAD software and design a house if they so desire. Is the town going to let you build it without a certified engineer/architect signing off? Fuck no. But we don't lock down CAD software. No, we lock down using that output from the CAD software in the real world. > And presumably, mission critical software is still going to be stamped off on by a certified engineer of some sort. The "mission…

I am not really sure what you are getting at here. Are you suggesting that people should need to acquire some sort of credential to be allowed to code?

Re: My AI Adoption Journey

#232

Post by lelanthran »

snayan wrote: post #231
lelanthran wrote: post #203

Earlier quoted context omitted.

> Anyone can pick up some CAD software and design a house if they so desire. Is the town going to let you build it without a certified engineer/architect signing off? Fuck no. But we don't lock down CAD software. No, we lock down using that output from the CAD software in the real world. > And presumably, mission critical software is still going to be stamped off on by a certified engineer of some sort. The "mission…

I am not really sure what you are getting at here. Are you suggesting that people should need to acquire some sort of credential to be allowed to code?

> Are you suggesting that people should need to acquire some sort of credential to be allowed to code?

No, I am saying that you are comparing professional $FOO practitioners to professional $BAR practitioners, but it's not a valid comparison because one of those has review and safety built into the process, and the other does not.

You can't use the assertion "We currently allow $FOO practitioners to use every single bit of automation" as evidence that "We should also allow $BAR practitioners to use every bit of automation", because $FOO output gets review by certified humans, and $BAR output does not.

Re: My AI Adoption Journey

#233

Post by jvillasante »

This are all valid points and a hype-free pragmatic take, I've been wondering about the same things even when I'm still in the skeptics side. I think there are other things that should be added since Mitchell's reality won't apply to everyone:

- What about non opensource work that's not on Github?

- Costs! I would think "an agent always running" would add up quickly

- In open source work, how does it amplify others. Are you seeing AI Slop as PRs? Can you tell the difference?

Re: My AI Adoption Journey

#235

Post by mlrtime »

swordsith wrote: post #214
mapontosevenths wrote: post #86

Earlier quoted context omitted.

> 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.

If you've got a plan for the plan, what else could you possibly need!

You joke, but the more I iterate on a plan before any code, the more successful the first pass is.

1) Tell claude my idea with as much as I know, ask it to ask me questions. This could go on for a few rounds. (Opus)

2) Run a validate skill on the plan, reviewer with a different prompt (Opus)

3) codex reviews the plan, always finds a few small items after the above 2.

4) claude opus implements in 1 shot, usually 99% accurate, then I manually test.

If I stay on target with those steps I always have good outcomes, but it is time consuming.

Re: My AI Adoption Journey

#236

Post by dns_snek »

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…

> We don't call architects 'vibe architects' even though they copy-paste 4/5th of your next house and use a library of things in their work!

Architect's copy-pasting is equivalent to a software developer reusing a tried and tested code library. Generating or writing new code is fundamentally different and not at all comparable.

> We don't call builders 'vibe builders' for using earth-moving machines instead of a shovel...

We would call them "vibe builders" if their machines threw bricks around randomly and the builders focused all of their time on engineering complex scaffolding around the machines to get the bricks flying roughly in the right direction.

But we don't because their machines, like our compilers and linters, do one job and they do it predictably. Most trades spend obscene amounts of money on tools that produce repeatable results.

> That's a lot of years! They're still called architects.

Because they still architect, they don't subcontract their core duties to architecture students overseas and just sign their name under it.

I find it fitting and amusing that people who are uncritical towards the quality of LLM-generated work seem to make the same sorts of reasoning errors that LLMs do. Something about blind spots?

Re: My AI Adoption Journey

#237

Post by elAhmo »

hollowturtle wrote: post #226

I don't understand how Agents make you feel productive. Single/Multiple agents reading specs, specs often produced with agents itself and iterated over time with human in the loop, a lot of reviewing of giant gibberish specs. Never had a clear spec in my life. Then all the dancing for this apperantly new paradigm, of not reviewing code but verifying behaviour, and so many other things. All of this to me is a total UN…

> Never had a clear spec in my life.

Just because you haven't or you work in a particular way, doesn't mean everyone does things the same way.

Likewise, on your last point, just because someone is using AI in their work, doesn't mean they don't have hard skills and know-how. Author of this article Mitchell is a great example of that - someone who proved to be able to produce great software and, when talking about individuals who made a dent in the industry, definitely had/has an impactful career.

Re: My AI Adoption Journey

#238

Post by suddenlybananas »

keyle wrote: post #160
bigstrat2003 wrote: post #138

Earlier quoted context omitted.

Maybe. But it's been 3 years and it still isn't good enough to actually trust. That doesn't raise confidence that it will ever get there.

You need to put this revolution in scale with other revolutions. How long did it take for horses to be super-seeded by cars? How long did powertool take to become the norm for tradesmen? This has gone unbelievably fast.

>super-seeded

Cute eggcorn there.

Re: My AI Adoption Journey

#239

Post by hollowturtle »

elAhmo wrote: post #237
hollowturtle wrote: post #226

I don't understand how Agents make you feel productive. Single/Multiple agents reading specs, specs often produced with agents itself and iterated over time with human in the loop, a lot of reviewing of giant gibberish specs. Never had a clear spec in my life. Then all the dancing for this apperantly new paradigm, of not reviewing code but verifying behaviour, and so many other things. All of this to me is a total UN…

> Never had a clear spec in my life. Just because you haven't or you work in a particular way, doesn't mean everyone does things the same way. Likewise, on your last point, just because someone is using AI in their work, doesn't mean they don't have hard skills and know-how. Author of this article Mitchell is a great example of that - someone who proved to be able to produce great software and, when talking about ind…

Never mentioned Mitchell I'm generally speaking, 95% of industry is not Mitchell

Re: My AI Adoption Journey

#240

Post by yourapostasy »

LiamPowell wrote: post #222
rhubarbtree wrote: post #178

Earlier quoted context omitted.

This argument is disingenuous and distracts rather than addresses the point. Yes, it is possible for a compiler to have a bug. No, that is I’m mo way analogous to AI producing buggy code. I’ve experienced maybe two compiler bugs in my twenty year career. I have experienced countless AI mistakes - hundreds? Thousands? Already. These are not the same and it has the whiff of sales patter trying to address objections. Pl…

I'm not arguing that LLMs are at a point today where we can blindly trust their outputs in most applications, I just don't think that 100% correct output is necessarily a requirement for that. What it needs to be is correct often enough that the cost of reviewing the output far outweighs the average cost of any errors in the output, just like with a compiler. This even applies to human written code and human mistakes…

The challenge not addressed with this line of reasoning is the required sheer scale of output validation on the backend of LLM-generated code. Human hand-developed code was no great shakes at the validation front either, but the scale difference hid this problem.

I’m hopeful what used to be tedious about the software development process (like correctness proving or documentation) becomes tractable enough with LLM’s to make the scale more manageable for us. That’s exciting to contemplate; think of the complexity categories we can feasibly challenge now!

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