impizulu

> "Throw nine autonomous agents at a single codebase without crystal-clear orchestration, and they will happily rewrite each other's work in a high-speed loop."

Is it not the same with people? Just slower? Poor management leads to duplication of work all the time.

Nowadays it feels like every software engineer also needs to learn management skills (to orchestrate AI agents) no matter how junior you are.

Fair enough. It's a mix. But for the most part it's a net positive.

We have replaced external tools with in-house tools written by largely AI. These are not one-prompt tools made in a day. We have built our own analytics stack which non-technical coworkers use everyday - they are not interested in "bullshit", they need real, accurate data and visualisations. And we had a cross-over period where our internal tooling was compared to our (now legacy) 3rd party analytics tools. It was done properly.

At least where I work, I don't think there is much automation of "bullshit jobs" - people don't typically just waste time chasing fairy tales (for the most part). But for things like report generation or tracing issues or generating presentations or infographics, there is certainly a much higher volume of these things getting pushed around which may or may not actually achieve anything, or be at all correct. So I reckon a large chunk of these would fall under into the "bullshit" bucket.

Because everyone can produce so much more "stuff" with AI assistance / automations, a good portion does end up spewed straight out of the slop factory. How much / what proportion kind of differs person-to-person tbh.

100%. Most people are not programmers. Most people do not see software as something interesting to figure out. It's just a tool for them to do their job.

To get the average office worker to want to switch, you not only have to provide a finished product that works smoothly, but also one that feels familiar. Most office workers grind through their day doing repetitive tasks in familiar software they have been using for a decade. When the top of the food chain says they are overhauling the entire software suite that people have been grown accustomed to for their entire career, the new software better have real benefits that incentivise employees to actually engage with learning it. Otherwise productivity will simply crater.

Most office workers do not care to learn new software. They just want to get on with their job. For better or for worse. But if you can demonstrate a switch will make their lives easier and the UI UX of the new software is very familiar and intuitive (and it actually works) you may be able to pull off a clean switch and keep your employees happy.

An MVP is fine but I think it's crucial that the UI UX is very similar to the software that it is replacing because it means people don't have to relearn whatever habits they have developed over the years in the old stack. I think that's what creates the most resistance to change.

Yes, AI is still not particularly prevalent in the customer-facing / consumer-facing things you described. But internally, I think these companies are up to their eyeballs in AI automations. At the company I work for, the customer-facing side of our business has not really been changed by AI (except for faster iteration of website design, and a somewhat limited customer service chatbot - not particularly good like your experience). But internally we are using it for so many things, for example we have brought 3rd party analytics tools in-house (cost reduction and ownership over our data) by writing our own internal tools, we have setup custom systems to give ourselves better visibility over the business to try catch issues earlier, we use it to produce internal reports, etc.

I don't have much experience in robotics but I've heard that machine vision models have absolutely been changing the industry. And I imagine they are also using AI to write a lot of software too. But not my area, just what I've heard / been reading.