Your metric for “getting it to work” is wrong. Developing software is a means to an end, not a goal in and of itself.
The simplest metric you should be tracking is; has it generated income.
In this sense my use of agentic coding has performed very well. People asking for evidence and repos are a little naive to how capitalism works in the real world. If I’m making money on something I’m not going to let you copy it, and I’m sure as hell not going to devalue it by publicising that it was built by AI.
If the person can use AI to lead a noticeably better life, something that may have been impossible previously due to economic circumstance, then the first order benefits outweigh the second order drawbacks.
I’m not disputing what you’re saying, I just think that treating it like a zero sum game every time the conversation comes up is showing an immense amount of privilege.
You, me, the parent commenter; we’re all dying, we don’t have time to optimise for the best outcome.
I have a slightly similar frustration; Netflix, Disney et al requiring me to figure out the name of the film by deciphering the poster. I don’t know how this passes any kind of accessibility testing.
> Author: please write an article about this topic with examples of content you've created, discussions about dead ends and things that didn't work, and technical details about your setup.
I think the article itself serves as enough evidence to prove you should ignore their advice.
Is there a term for what I had previously understood Effective Altruism to be, since I don’t want to reference EA in a conversation and have the other person think I’m associated with these sorts of people.
I had assumed it was just simple mathematics and the belief that cash is the easiest way to transfer charitable effort. If I can readily earn 50USD/hour, rather than doing a volunteering job that I could pay 25USD/hour to do, I simply do my job and pay for 2 people to volunteer.
This is a more extreme example of the general hacker news group think about AI.
Geohot is easily a 99.999 percentile developer, and yet he can’t seem to reconcile that the other 99.999 percent are doing something much more basic than he can ever comprehend.
It’s some kind of expert paradox, if everyone was as smart and capable as the experts, then they wouldn’t be experts.
I have come across many developers that behave like the AI. Can’t explain codebases they’ve built, can’t maintain consistency.
It’s like a aerospace engineer not believing that the person that designs the toys in an Kinder egg doesn’t know how fluid sims work.
Watching my children learn how to talk, I have come to the conclusion that the current LLM concept is one part of a two part problem.
Kids learn to speak before they learn to think about what they're saying. A 2/3 year old can start regurgitating sentences and forming new ones which sound an awful lot like real speech, but it seems like it's often just the child trying to fit in, they don't really understand what they're saying.
I used to joke my kids talking was sometimes just like typing a word on my phone and then just hitting the next predictive word that shows up. Since then it's evolved in a way that seems similar to LLMs.
The actually process of thought seems slightly divorced from the ability to pattern match words, but the patter matching serves as a way to communicate it. I think we need a thinking machine to spit out vectors that the LLM can convert into language. So I don't think they are a dead end, I think they are just missing the other half of the puzzle.
It manifests as a sort of extension for Claude Code.
When I'm in the terminal I can call on Agents who can create standardised documents so there is a memory of the product management side of things that extends beyond the context window of Claude.
It guides you through the specification process so that you have extremely tight tasks for Claude to churn through, with any context, documentation and acceptance criteria.
Perhaps there are others similar, but I have found it completely transformative.
They don't necessarily want to be the gatekeepers of information, they just want your next click to be another news story on their website.
External links are bad for user retention/addiction.
This also has a side effect of back linking no longer being a measure of a 'good' website, so good quality content from inconsistently trafficked sites gets buried on search results.
I use OpenAI's batch mode for about 80% of my AI work at the moment, and one of the upsides is it reduces the frantic side of my AI work. When the response is immediate I feel like I can't catch a break.
I think once the sheen of Microsoft Copilot and the like wear off and people realise LLMs are really good at creating deterministic tools but not very good at being one, not only will the volume of LLM usage decline, but the urgency will too.
I think we need to start being more nuanced in the way we describe "AI Coding tools".
In the same way Claude Code is a different beast to Cursor, my own process is a different beast to Claude Code and the months I've spent building out a robust pipeline is now paying dividends.
I also think someone at The Register needs to go on a statistics course. Those figures seem to paint the picture that an overwhelming majority of those surveyed have had positive outcomes, which I don't think is represented by the slightly snarky headline.
I have managed to make some pretty incredible tools, it definitely feels like magic.
I would say I split my time 70% using BMAD as an assistant to build out my scope and clarify what I am trying to do in my own head, then 30% supervising Claude Code.
I have also managed to build out more simple tools using Streamlit to great effect
Astro with a good understanding of how to build using a coding agent (my go to is the BMAD method)