Knowledge workers use it primarily to "augment" their work, answer questions with AI, get it to create documents, etc. But it's usually 1 individual to 1-2 conversation threads.
Meanwhile in software development were running fleets of agents. At work we have it setup where firing off one agent request will eventually lead to like 10-20 AI calls at different parts of the process.
I make this distinctions because it changes how each group thinks about AI. For software devs it just feels like "moving up the stack". Yeah you're not writing code anymore but there is still plenty of work to do and problems to solve within your "software factory". Contrast that with knowledge workers that feel like the AI is making all of their decisions for them.
I almost think of this as a factory worker versus an artisan. The software devs are "factory workers" where we used to be on the floor but now we're managing the machines that took over the work. There are still tons of interesting problems at that stage and you still feel like you have worth. Contrast that with a knowledge worker that's more of an artisan in this analogy. For them they aren't running a factory but instead watching a robot do the work they used to do while they sit idle and watch it.
[–] Scubabear68 1 day ago
[–] jacquesm 1 day ago
Using AI is like using adaptive cruise control: you're still in charge of where the vehicle will ultimately end up and if you decide to go take a nap you will wake up in the hospital or end up in the morgue.
It's true though that the 'time between interventions' is lengthening steadily.
[–] slg 1 day ago
The primary difference is that it's much easier for the AI to figure out itself if it's wrong on the programming side. Knowledge workers don't have automated testing for example.
The end result is the knowledge worker needs to be more heavily involved in the process and be more mindful of mistakes which makes it a worse experience for the user and generally less productive than it is for programmers.
[–] WillPostForFood 1 day ago
[–] Retric 1 day ago
For most professionals it’s just safer to avoid having output in your workflow. Keep using AI, but stop copying and pasting AI output.
[–] eluru 1 day ago
[–] EA-3167 1 day ago
[–] infamouscow 1 day ago
In practice, lawyers generally don't ever disbarred except if they lie to clients or steal from them.
[–] echelon 1 day ago
All of this will sort itself out and eventually bio, legal, software will all just work.
Don't hold onto any single assumption about the world. Things are going to be weird.
[–] dTal 1 day ago
[–] readthenotes1 1 day ago
If lawyers and article writers are in the knowledge realm. Then your thesis has plenty of counter-examples of people who just use AI to create stuff and don't correct it.
[–] Exoristos 1 day ago
[–] mywittyname 1 day ago
And I'm probably on the more amateurish end of AI development. As I learned these techniques from YouTube.
When you hear about the work Anthropic researchers are doing, they seem to be using hundreds or thousands of agents to solve problems.
[–] Wheen 1 day ago
There's a reason they're Anthropic researchers. The value proposition tanks when you actually have to foot the bill for the tokens you use.
Subagent flows can improve overall performance, but it generally also comes with disproportionately high token use. That gets worse with parallel subagents that are often doing the same things at the same time and cannot share a cache.
[–] mywittyname 1 day ago
So the median developer is probably using 5-20 agents at a time for a task. I'm not sure if that crosses the threshold of being a "fleet of agents".
[–] Wheen 1 day ago
[–] NichoPaolucci 1 day ago
[–] mistrial9 1 day ago
The "median developer" refers to the particularly skilled or fast-paced, not that there are continuous numbers of every practitioner using N-agents
[–] _aavaa_ 10 hours ago
[–] tehjoker 1 day ago
[–] bigstrat2003 1 day ago
[–] chicagobuss 1 day ago
[–] thatsabadlook 14 hours ago
[–] MisterTea 1 day ago
I don't actually use AI much at all simply because in my line of work the knowledge is industry specific and niche - an AI can't tell you how to fix a proprietary machine. I have used it a few times but to do dumb things like write some Excel script or some other piece of software I have no interest or need for learning.
[–] iugtmkbdfil834 1 day ago
[–] idontknowmann 1 day ago
It’s a phase.
[–] rootusrootus 1 day ago
Fortunately I'm in a shop that isn't being judged by feature output quantity, but is absolutely judged on whether or not our internal or external customers go out of service. We don't have pressure to pump output.
[–] archagon 1 day ago
[–] SR2Z 1 day ago
In the sense that "down the stack" is well-captured by existing language, AI is absolutely moving programmers up the stack. I can describe my goals using high-level abstractions, and the low-level implementation is somewhat constrained by that.
How well constrained it is depends on how well I described the problem and the quality of the model - much like how good human-written code is depends on how clearly the authors were thinking when they designed the structure.
[–] archagon 22 hours ago
[–] SR2Z 12 hours ago
[–] shepherdjerred 1 day ago
[–] freejazz 1 day ago
[–] bigstrat2003 1 day ago
[–] soco 1 day ago
[–] exe34 1 day ago
I know knowledge workers who throw what you give them into the slop machine and return the slop, but I don't need them, I can feed the slop machine myself. I still need those who have experience and taste that the machine hasn't got yet.
I think your general thesis about how AI is used of agents vs. the general chat interface is true, but not the rest.
Your knowledge worker example is where people fail when using AI, and it is usually very obvious.
Knowledge workers who know what they're doing recognized very quickly that AI often goes down very bad rabbit holes, often cites incorrect sources, makes up sources, or will use a random Facebook source or Reddit post as an authority on some topic. In legal circles you have to fight it to understand what venue(s) apply and to get it to stick to the right ones, in medical research it will sometimes pull in crackpot papers from left field and intermix them with well defined research.
People in the knowledge realm caught on very quickly that you have to use AI iteratively and constantly back check what you get and correct it. Let it run on its own and it will give you a legal theory based on some weird case in Kentucky that has no bearing to your issue with a court in Vermont.