[baq]

Workflows exist to solve problems. If there are problems which need solving that are solved better/faster/cheaper by AI agents than with strict rule-based algorithmic systems, they’ll be used because it makes economic sense. Reliability requirements are different for every problem, cases where verification is easy and cheap and multiple attempts are allowed are perfect for not 100% reliable agents.

[zkmon]

it's fine if you want AI to help you in defining the workflow/rules. But you don't use AI to define rules on the fly. That's the whole point. It is like having AI to write code at runtime based on the request. I don't think that's how you use AI in software.

[mewpmewp2]

In many cases I do have AI writing code runtime for my tasks. E.g. if I'm doing analysis of something, or some data, I can ask AI to gather the data (it writes code for scraping or uses pre existing scraping/web search tools), then it uses python or typescript to analyze the data. After which it will use e.g. React in the web app to render the Charts, Tables in customized, personalized format.

For instance, I might be looking for a product or something, it will use web search to gather all possible products, then evaluate all the products against my desired criteria, use some sort of scoring mechanism to order the products for me and then write an UI to display the products with their pros and cons specified, with products ranked using an algorithm.

Or I might ask it to find all permutations of flight destinations in March, I want somewhere sunny and use weighted scoring algorithm to rank the destinations by price, flight travel duration etc.. Then it writes code to use flights API, to get all permutations and does the ranking.

I used to have to go to things like airport websites, momondo, skyscanner, I don't have to do those things manually anymore, thanks to AI agents. I can just let it work and churn out destinations, travel plans according to a scoring criteria.

Worst mistakes it can make is, that is missed a really good deal, but this is something I could even more easily miss myself, or worst case it makes a mistake and parses the price/dates wrong, which I will find out when trying to book it, so I waste a bit of time, but similar and worse mistakes I do on my own as well. So overall I drastically reduce my search time for the perfect travel, and also time spent on my own mistakes or misunderstandings. And it will be able to go through permutations far faster and more reliably with infinite patience compared to myself.

[zkmon]

None of what you said qualifies as coding at run time. I think you missed at. At run time, code is executed, not designed or defined.

[mewpmewp2]

Okay I tell AI to do X, it writes a script and executes it to perform X, how is that not defining code runtime?

AI agents like Claude Code or Codex constantly use the technique of writing temporary scripts and executing them inline.

[zkmon]

If your system receives 1000 requests per second, does it keep writing code while processing every request, on per request basis? I hope you understand what run time means.

[mewpmewp2]

Define runtime then.

> If your system receives 1000 requests per second, does it keep writing code while processing every request, on per request basis? I hope you understand what run time means.

With enough scale it could, however it really depends on the use case, right? If we are considering Claude Code for instance, it probably receives more than 1000+ requests per second and in many of those cases it is probably writing code or writing tool calls etc.

Or take Perplexity for example. If you ask it to calculate a large number, it will use Python to do that.

If I ask Perplexity to simulate investment for 100 years, 4% return, putting aside $50 each month, it will use Python to write code, calculate that and then when I ask it to give me a chart it will also use python to create the image.