8 ms·

"Congratulations, you have been elevated to manager to agents." That's not exactly really where I hoped my career would lead. It's like managing junior develop

• MangoToupe 11mo ago
  Also, agents have no capacity to learn.
  • jstummbillig 11mo ago
    Hold that thought.
  • bradfa 11mo ago
    They have a capacity to "learn", it's just WAY MORE INVOLVED than how humans learn. With a human, you give them feedback or advice and generally by the 2nd or 3rd time the same kind of thing happens they can figure it out and improve. With an LLM, you have to specifically setup a convoluted (and potentially financially and electrical power expensive) system in order to provide MANY MORE examples of how to improve via fine tuning or other training actions.
    • OtherShrezzing 11mo ago
      I think it’s reasonable to say that different approaches to learning is some kind of spectrum, but that contemporary fine tuning isn’t on that spectrum at all.
    • ethmarks 11mo ago
      Depending on your definition of "learn", you can also use something akin to ChatGPT's Memory feature. When you teach it something, just have it take notes on how to do that thing and include its notes in the system prompt for next time. Much cheaper than fine-tuning. But still obviously far less efficient and effective than human learning.
    • lowsong 11mo ago
      > With an LLM, you have to specifically setup a convoluted (and potentially financially and electrical power expensive) system in order to provide MANY MORE examples of how to improve via fine tuning or other training actions. The only way that an AI model can "learn" is during model creation, which is then fixed. Any "instructions" or other data or "correcting" you give the model is just part of the context window.
      • bradfa 11mo ago
        Fine tuning is additional training on specific things for an existing model. It happens after a model already exists in order to better suit the model to specific situations or types of interactions. It is not dealing with context during inference but actually modifying the weights within the model.
    • MangoToupe 11mo ago
      Retraining (or fine tuning) isn't the same thing at all and I think that's obvious
• Too 11mo ago
  I thought you were joking until I saw the video where this is an actual quote.
  • aDyslecticCrow 11mo ago
    There are two more quotes that made me giggle; > You can verify code quality as a glance, and ship absolute with confidence. > You can confidently trust and merge the code without hours of manual review. I couldn't possibly imagine that going wrong.
• throwawaysleep 11mo ago
  As an introvert, that's a pro, not a con. The burden of human interaction is removed from building.
  • ithkuil 11mo ago
    I'm an introvert and I love working with nice people. I just need some time by myself to recharge after all the social interactions.
    • warkdarrior 11mo ago
      As a team lead, working with people is so... cumbersome. They need time to recharge, lots of encouragement, and a nice place to work in. Give me a coding agent any time!
      • discreteevent 11mo ago
        As a PM working with team leads is so cumbersome...
        • ithkuil 11mo ago
          I wish I could automate PMs :-p
      • sanex 11mo ago
        They don't like working on the cumbersome tickets, writing tests, documentation. Talking to businesspeople.
  • AstroBen 11mo ago
    Being antisocial isn't an introvert thing. I'm incredibly introverted and still love having time interacting with people
    • anticensor 11mo ago
      They're asocial, not antisocial. Antisociality is a diagnosable disorder and is known for interpersonal behaviours that are actively against a healthy society. Asociality, on the other hand, just avoids social interactions, not actively harming the society.
• sorokod 11mo ago
  "junior developers" is a convenient label, it is incorrect but it will take a bit until we come up something that describes entities that: - can write code - tireless - have no aspirations - have no stylistic or architectural preferences - have massive, but at the same time not well defined, body of knowledge - have no intrinsic memories of past interactions. - change in unexpected ways when underlying models change - ... Edit: Drones? Drains?
  • auspiv 11mo ago
    I describe them in the claude training I'm doing for my company as: super smart, infinitely patient, overeager interns
    • kvirani 11mo ago
      Sometimes smart sometimes the opposite, though. Perhaps due to memory loss.
      • embedding-shape 11mo ago
        Not sure "smart" or "dumb" are even the right axis to be judging them by, seems like intrinsically human traits.
  • throwawaysleep 11mo ago
    Sounds like a junior developer? They can usually write code, but not that well. They have lots of energy and little to say about architecture and style. Don't have a well defined body of knowledge and have no experience. Individual juniors don't change, but the cast members of your junior cohort regularly do.
    • theshrike79 11mo ago
      The problem with AI Agents like Claude is that they write VERY good code and very fast. But they don't have a grasp for the project's architecture and will reinvent the wheel for feature X even when feature Y has it or there is an internal common library that does it. This is why you need to be the "manager of agents" and stay on top of their work. Sometimes it's just about hitting ESC and going "waitaminute, why'd you do that?" and sometimes it's about updating the project documentation (AGENTS.md, docs/) with extra information. Example: I have a project with a system that builds "rules" using a specific interpreter. Every LLM wants to "optimise" it by using a pattern that looks correct, but will in fact break immediately when there's more than one simultaneous user - and I have a unit test that catches it. I got bored by LLMs trying to optimise the bit wrong, so I added a specific instruction, with reasoning why it shouldn't be attempted and has been tried and failed multiple times. And now they stopped doing it =)
• tjmadsen 11mo ago
  OR - think about the junior developers being managers of agents, and you are still a manager of junior developers. This is not zero sum!
  • icedchai 11mo ago
    I am essentially in this exact role. The junior developers simply don't have the experience to evaluate the output of the agents. You wind up with a lot of slop in PRs. People can't justify why they did something. I've seen whole PRs closed, work redone, and opened anew because they were 70% garbage. Every other comment was asking "why is this here? it has nothing to do with the ticket." Sadly, this is not sustainable and I am not sure what I'm going to do.
• UltraSane 11mo ago
  I enjoy getting into a good flow state and pounding out clever and elegant code but watching a good LLM generate code according to my specs and refining it is also enjoyable. I've been burning through $250 of free Claude Code Web credits and having multiple workers running at the same time is fun.
• BeetleB 11mo ago
  > It's like managing junior developers, but without having nice people to work with. Nice? I thought all sycophant LLMs were exceedingly nice.
  • kalaksi 11mo ago
    For me, it feels so fake that I'd rather have it not try to be nice. I guess I've gotten a bit used to it and ignore it for most parts.
    • IshKebab 11mo ago
      Yeah it's saccharine. Reminds me quite a lot of Americans who work for tips (e.g. waiters) - disconcertingly friendly. Someone gave me a great tip though - at least for ChatGPT there's a setting where you can change its personality to "robot". I guess that affects the system prompt in some way but it basically fixes the issue.
• supportengineer 11mo ago
  I'm at one of those companies where we're forced to be in the office. NO ONE TALKS TO EACH OTHER unless absolutely necessary for work. We get on Zooms to talk. Even with the person 1 cubicle over.
  • dabockster 11mo ago
    > We get on Zooms to talk. Even with the person 1 cubicle over. Who normalized this?!!
    • Rohansi 11mo ago
      I know it happens when you're working with people who may be at home or another location.
      • IshKebab 11mo ago
        Yeah but not if you just want to talk to one person who's a few metres away. That's such bizarre behaviour I don't really believe it.
    • zmmmmm 11mo ago
      I actually do find there is a subset of meetings that are far more productive on Zoom. We can be voice chatting on one screen, share another screen and both be able to type, record notes, pull up side research without interrupting the conversation. It's a bit closer to co-working than a meeting but it hits a sweetspot for me.
  • cloverich 11mo ago
    > We get on Zooms to talk. Even with the person 1 cubicle over. But why? Required? Culture? Maybe it's the company?
  • jimbokun 11mo ago
    Why?
  • drcxd 11mo ago
• roadside_picnic 11mo ago
  I used to be really excited about "agents" when I thought people were trying to build actual agents like we've been working on in the CS field for decades now. It's clear now that "agents" in the context of "AI" is really about answering the question "How can we make users make 10x more calls to our models in a way that makes it feel like we're not just squeezing money out of them?" I've seen so many people that think setting some "agents" of on a minutes to hours long task of basically just driving up internal KPIs at LLM providers is cutting edge work. The problem is, I haven't seen any evidence at all that spending 10x the number of API calls on an agent results in anything closer to useful than last year when people where purely vibe coding all the time. At least then people would interactively learn about the slop they were building. It's astounding to watch a coworker walk though through a PR with hundreds of added new files and repeatedly mention "I'm not sure if these actually work, but it does look like there's something here". Now I'm sure I'll get some fantastic "no true Scotsman" replies about how my coworkers must not be skilled enough or how they need to follow xyz pattern, but the entire point of AI was to remove the need for specialize skills and make everyone 10x more productive. Not to mention that the shift in focus on "agents" is also useful in detracting from clearly diminishing returns on foundation models. I just hope there are enough people that still remember how to code (and think in some cases) to rebuild when this house of cards falls apart.
  • dragonwriter 11mo ago
    > but the entire point of AI was to remove the need for specialize skills and make everyone 10x more productive. At least for programming tools, for everything (well, the vast majority, at least) that is sold that way—since long before generative AI—it actually succeeds or fails based not on whether it eliminates need for specialized skills and makes everyone more productive, but whether it further rewards specialized skills, and makes the people who devote time to learning it more productive than if they devoted the same time to learning something else.
• naruhodo 11mo ago
  Pastor of Muppets
• fsmv 11mo ago
  You are being rescued. Do not resist.