Comment by user43928 | Hacker News Reader

Comment by user43928 | Hacker News Reader

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Those are good points, but some arguments are weak:

- Chatbot usage in $20 plans is likely nowhere close to a $200 cost.

Inference cost has come down rapidly, with reports from July claiming OpenAI can now serve all of the logged out ChatGPT traffic on just a few hundred GPUs.

- Measurable benefit: I doubt anything of value is being measured. MS Copilot with GPT 5.5 Instant processing SharePoint files? Developers using AI as a fancy autocomplete under a "I review every line" regime?

I rely on my personal value judgement, based on 30h/week I spend using AI outside of my regular job.

I am developing a mobile app, competing with companies with millions in revenue and entire dev teams. I know it is viable. Others lag in effective adoption, their opinion is likely to change soon with even more capable models.

- data center projects in the US: They look to me to mostly be constructed in the most remote backwater. If even there projects with such moderate environmental impact cannot be realized, that would be an embarrassing policy failure

- the grid: I think that one is true. AFAIK the constraint would be gas turbines, not diesel, and oil supply is not structurally constrained

- the loans: Anthropic is rumored to have become profitable earlier this year because of large growth in enterprise revenue. It does not look so bad to me

>I am developing a mobile app, competing with companies with millions in revenue and entire dev teams. I know it is viable. Others lag in effective adoption, their opinion is likely to change soon with even more capable models.

To add to that, as an ex-software dev that mostly works in a semi-unrelated field now (and can only code as a small part of my job): I think a lot of software devs are underestimating what someone with reasonable technical skills and specialised domain knowledge is able to create with AI.

I honestly wouldn't be surprised if, in 5 years' time, the majority of software used by (e.g.) potato farmers was primarily created by other potato farmers. The code might still be less elegant but I think it will be easier for the potato farmer to iterate with an AI than outsourcing to a dev firm.

On a tangent, because you mentioned five years for widely used software being implemented by domain experts rather than software engineers: this seems like a very conservative timeline.

I have little doubt that a competent potato farmer could possibly implement and sell such software today using Opus 5, Fable, or 5.6 Sol.

Now what I am going to say next may sound a bit crazy, and it is outside of my area of expertise. I hear the recent mathematical breakthroughs made by GPT-6/Astra are field medal worthy discoveries.

What if the current trajectory of improvement holds for another year or two?

Is it impossible that LLMs gain superhuman ability to reason over a large number of constraints so that they can make novel breakthroughs unimaginable to us today?

What I hope to see in five years is not potato farmers writing software, but programmable immune cells that safely kill cancer.

Perhaps I am an optimist.

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