[akhil08agrawal]

This resonates with what I'm experiencing, but I think the article misses the real shift happening now.

The conversation shouldn't be "will AI replace developers". It should be "how do humans stay competitive as AI gets 10x better every 18 months?"

I watched Claude Code build a feature in 30 minutes that used to take weeks. That moment crystallised something: you don't compete WITH AI. You need YOUR personal AI.

Here's what I mean: Frontier teams at Anthropic/OpenAI have 20-person research teams monitoring everything 24/7. They're 2-4 weeks ahead today. By 2027? 16+ weeks ahead. This "frontier gap" is exponential.

The real problem isn't tools or abstraction. It's information overload at scale. When AI collapses execution time, the bottleneck shifts to judgment. And good judgment requires staying current across 50+ sources (Twitter, Reddit, arXiv, Discord, HN).

Generic ChatGPT is commodity. What matters is: does your AI know YOUR priorities? Does it learn YOUR judgment patterns? Does it filter information through YOUR lens?

The article is right that tools don't eliminate complexity. But personal AI doesn't eliminate complexity. It amplifies YOUR ability to handle complexity at frontier speed.

The question isn't about replacement. It's about levelling the playing field. And frankly we all are figuring out on how will this shape out in the future. And if you have any solution that can help me level up, please hit me up.

[bflesch]

> And good judgment requires staying current across 50+ sources (Twitter, Reddit, arXiv, Discord, HN).

Your mention of the hellhole that is today's twitter as the first item in your list of sources to follow for achieving "good judgement" made it easy for me to recognize that in fact you have very bad judgement.

[teaearlgraycold]

What feature is it that Claude Code built in 30 minutes?

[pirates]

For some reason everyone that says things like this never follow up with anything concrete, don’t share prompts or snippets, etc.

[ako]

This project is completely built using claude code: https://github.com/ako/backing-tracks Most of the features take less than 30 minutes.

[shimman]

This isn't that impressive when there are mountains of training data dealing with exactly this... how about something truly unique and not something already available to the masses in hundreds of different forms?

Like cool, you killed boiled a few gallons of the ocean but are you really impressed that you made a basic music app that is extremely limited?

[ako]

So we’re now in a world where this isn’t impressive anymore? How quickly expectations change. Having started with basic and then 6502 assembly over 40 years ago, this still feels like science fiction to me.

But most enterprise software does not need to be innovative, its needs to be customizable enough that enterprises can differentiate their business. This makes existing software ideas so much more configurable. No more need for software to provide everything and the kitchen sink, but exactly that what you as a customer want.

Like in my example, I don’t know of any software that has exactly this feature set. Do you?

[teaearlgraycold]

It looks cool to me.

[jdiez17]

This looks pretty neat, thanks!

[teaearlgraycold]

I’ve seen first hand people talk big about how they used LLMs on a project and it’s clear they’ve only done the first 80%. Yeah they’re good tools. But they also enable laziness.

[Robdel12]

https://www.npmjs.com/package/@vizzly-testing/honeydiff

I worked for Percy for 4 years. We were “stuck” with imagemagik to do diffing (I’m sure they still might). I was able to build my own differ with Claude/LLM help.

That special enough for you? Or?

[teaearlgraycold]

I looked at the source. It seems most of the code is not included in the GitHub repo, which itself contains a bit of JS glue. The .tgz uploaded to npm has various prebuilt binaries. Can I take a look at the rust code?

I'm not trying to imply LLMs aren't useful. I just want more info from GP so that I can evaluate their claims.

[kukkeliskuu]

I have built many projects in hours that we can say would have reasonably taken me a month, to research the technology I did not know beforehand. 30 minutes is often enough to build a first version of the project. For example an audio book listener app, winter swimming iPhone/iWatch app combination, and markdown editor for OS X in Swift.

I have also added complex features in 30 minutes to existing projects, but I don't remember any that themselves would have taken me months though.

[Okx]

this comment is pretty obviously written by AI