In my work, letters to referring doctors are proof of evidence that I did something for the patient. Speech-to-text tools now turn my medical consult into words (and let me look at the actual person, which is nice). The other doctor won’t bother that it’s automatically written as long as it’s accurate. The problem for my profession will arise when a little agent swarm calculates the risks for one policy over the other, asks for a scan and prescribes medication. This will be soon I think, although the data to train those specialized swarms is still protected by law.
I wholeheartedly agree but how can someone only come to this conclusion after years? It is so obvious that writing and reading were for centuries bound in a social contract between reader and writer. Post-modernism if anything reinforced that notion by rebelling against it.
I assure you anyone in the business of administrating stuff through paperwork (government contracting!) is well aware of the complete obliteration of the basic assumption that ‘someone wrote this so it is at least worth a cursory glance’.
For all its other problems this is my main issue with LLM’s. Writing let people communicate across vast distance and time. Given no metadata, today one must initially assume all writing to be noise.
I was a little cranky when I replied. What I meant was that this flood of LLM-noise already started around GPT-4.5 for many people. I was surprised to read about this now. But it’s good to have a discussion about it at large, anyway.
>Another example: if you’re working on a project by yourself, why spend time creating tickets and filling them out? I suppose theoretically someone could read them to get a sense of what you’re doing, but in that case you’ve failed to communicate the project via normal channels: telling people in Slack or in meetings, writing a proposal document, and so on. The tickets are primarily valuable as evidence: proof1 that you haven’t just been screwing around playing video games.
What about us feeble mortals that don't remember everything they have written down? Honestly, when I work alone my tickets are often just the title and maybe a sentence in the body.
I feel like the "evidence" framework here is being abused. Why am I not allowed to have "evidence" of past ideas? In that case even an LLM written issue is evidence.
Here's my bet: with the new unlocked efficiencies, developers will no longer just work on a very small part of a system. Instead they'd be entrusted with entire business units individually or in a small group.
In those cases, the feedback loop is more direct and not necessarily relying on toy proxies like LOC or documents. My point is that it would be like grading a VP of product on how many lines their document has. That'd be stupid because VP's are seen as more mature and have longer term incentives. I don't think it should be any different for employees.
TL;DR employees will become small business owners-ish with AI.
This is just a hypothesis, but I'm willing to be proven wrong.
Diffusion of responsibility is the main aspect and the other factor is complexity. While AI might scale at will via the number of agents used, humans cannot.
Have you developed a platform which was business critical to the 100.000+ headcount global company that has 24/7 uptime before and after AI kicked in?
After all the amount of decisions to be made accumulate the larger the product or unit you are working on. After all, an AI is a approximation and even automating decisions away means knowing what to automate.
In this high impact and stress situation most people hide. No one wants to be held accountable. No one. That's why you have scapegoats.
Build a SaaS app with 10.000+ customers yourself. This doesn't exist on autopilot. And the moment you see humans fit for whole business units - why stop there? Where does this arbitrary border come from? This doesn't make sense, because why shouldn't AI be able to overtake this function as well?
Complex applications and decisions to be made - they also increase exponentially. And to be honest, this isn't just a matter of AI, but IQ, too. Average people want to execute a well crafted plan - only few craft them on their own or they are basic ones in comparison to huge apps.
In my work, letters to referring doctors are proof of evidence that I did something for the patient. Speech-to-text tools now turn my medical consult into words (and let me look at the actual person, which is nice). The other doctor won’t bother that it’s automatically written as long as it’s accurate. The problem for my profession will arise when a little agent swarm calculates the risks for one policy over the other, asks for a scan and prescribes medication. This will be soon I think, although the data to train those specialized swarms is still protected by law.
I wholeheartedly agree but how can someone only come to this conclusion after years? It is so obvious that writing and reading were for centuries bound in a social contract between reader and writer. Post-modernism if anything reinforced that notion by rebelling against it.
I assure you anyone in the business of administrating stuff through paperwork (government contracting!) is well aware of the complete obliteration of the basic assumption that ‘someone wrote this so it is at least worth a cursory glance’.
For all its other problems this is my main issue with LLM’s. Writing let people communicate across vast distance and time. Given no metadata, today one must initially assume all writing to be noise.
>the complete obliteration of the basic assumption that ‘someone wrote this so it is at least worth a cursory glance’.
The OP is not disputing that a lot of writing already had less than zero value to the reader, even decades ago. So that is not their conclusion.
They are really only saying that problem suddenly got MUCH worse.
You said it perfectly - “All writing now is noise”
I was a little cranky when I replied. What I meant was that this flood of LLM-noise already started around GPT-4.5 for many people. I was surprised to read about this now. But it’s good to have a discussion about it at large, anyway.
>Another example: if you’re working on a project by yourself, why spend time creating tickets and filling them out? I suppose theoretically someone could read them to get a sense of what you’re doing, but in that case you’ve failed to communicate the project via normal channels: telling people in Slack or in meetings, writing a proposal document, and so on. The tickets are primarily valuable as evidence: proof1 that you haven’t just been screwing around playing video games.
What about us feeble mortals that don't remember everything they have written down? Honestly, when I work alone my tickets are often just the title and maybe a sentence in the body.
I feel like the "evidence" framework here is being abused. Why am I not allowed to have "evidence" of past ideas? In that case even an LLM written issue is evidence.
Here's my bet: with the new unlocked efficiencies, developers will no longer just work on a very small part of a system. Instead they'd be entrusted with entire business units individually or in a small group.
In those cases, the feedback loop is more direct and not necessarily relying on toy proxies like LOC or documents. My point is that it would be like grading a VP of product on how many lines their document has. That'd be stupid because VP's are seen as more mature and have longer term incentives. I don't think it should be any different for employees.
TL;DR employees will become small business owners-ish with AI.
This is just a hypothesis, but I'm willing to be proven wrong.
I disagree.
Diffusion of responsibility is the main aspect and the other factor is complexity. While AI might scale at will via the number of agents used, humans cannot.
Have you developed a platform which was business critical to the 100.000+ headcount global company that has 24/7 uptime before and after AI kicked in?
After all the amount of decisions to be made accumulate the larger the product or unit you are working on. After all, an AI is a approximation and even automating decisions away means knowing what to automate.
In this high impact and stress situation most people hide. No one wants to be held accountable. No one. That's why you have scapegoats.
Build a SaaS app with 10.000+ customers yourself. This doesn't exist on autopilot. And the moment you see humans fit for whole business units - why stop there? Where does this arbitrary border come from? This doesn't make sense, because why shouldn't AI be able to overtake this function as well?
Complex applications and decisions to be made - they also increase exponentially. And to be honest, this isn't just a matter of AI, but IQ, too. Average people want to execute a well crafted plan - only few craft them on their own or they are basic ones in comparison to huge apps.