7 ms·

Can you give an example to help us understand? I look at my ticket tracker and I see basically 100% of it that can be done by AI. Some with assistance because

by malyk 7mo ago

Can you give an example to help us understand? I look at my ticket tracker and I see basically 100% of it that can be done by AI. Some with assistance because business logic is more complex/not well factored than it should be, but most of the work that is done AI is perfectly capable of doing with a well defined prompt.

contagiousflow 7mo ago
Why do you have a backlog then? If a current AI can do 100% of it then just run it over the weekend and close everything
- fishpham 7mo ago
  As always, the limit is human bandwidth. But that's basically what AI-forward companies are doing now. I would be curious which tasks OP commenter has that couldn't be done by an agent (assuming they're a SWE)
  - Analemma_ 7mo ago
    This sounds bogus to me: if AI really could close 100% of your backlog with just a couple more humans in the loop, you’d hire a bunch of temps/contractors to do that, then declare the product done and lay off everybody. How come that isn’t happening?
    - fishpham 7mo ago
      Because there's an unlimited amount of work to do. This is the same reason you are not fired once completing a feature :-) The point of hiring a FTE is to continue to create work that provides business value. For your analogy, FTEs often do that by hiring temp, and you can think of the agent as the new temp in this case - the human drives an infinite amount of them
      - sarchertech 7mo ago
        Why hasn’t any of the software I use started shipping features at a breakneck speed then? The only thing any of them have added is barely working AI features. Why aren’t there 10x the number of games on steam? Why aren’t people releasing new integrated programming language/OS/dev environments? Why does our backlog look exactly the same as when I left for posterity leave 4 months ago?
        fishpham 7mo ago
        Questions posed in bad faith can only be answered by the author.
        sarchertech 7mo ago
        Someone asked why the backlog doesn’t get finished. You answered that it does but the backlog just refills. So I asked where is the backlog evidence that the original backlog was completed. I’m still waiting for the evidence. I still haven’t seen externally verifiable evidence that AI is a net productivity boost for the ability to ship software. That doesn’t mean that it isn’t. It does mean that it isn’t big enough to be obvious. I’m very closet watching every external metric I can find. Nothing yet. Just saw the steam metrics for January. Fewer titles than January last year.
      - catmanjan 7mo ago
        Sounds more like busy work rather than something that makes money
lbrito 7mo ago
Then why isn't it? Just offload it to the clankers and go enjoy a margarita at the beach or something.
- Gud 7mo ago
  There are plenty of people who are enjoying margarita by the beach while you, the laborer, are working for them.
  - lbrito 7mo ago
    Preach. That's always been the case though, AI just makes it slightly worse.
dwa3592 7mo ago
>>I look at my ticket tracker and I see basically 100% of it that can be done by AI. That's a sign that you have spurious problems under those tickets or you have a PM problem. Also, a job is a not a task- if your company has jobs which is a single task then those jobs would definitely be gone.
rockbruno 7mo ago
I think the "well defined prompt" is precisely what the person you responded to is alluring to. They are saying they don't get worried because AI doesn't get the job done without someone behind it that knows exactly what to prompt.
gordonhart 7mo ago
Here's an example ticket that I'll probably work on next week: Live stream validation results as they come in The body doesn't give much other than the high-level motivation from the person who filed the ticket. In order to implement this, you need to have a lot of context, some of which can be discovered by grepping through the code base and some of which can't: - What is the validation system and how does it work today? - What sort of UX do we want? What are the specific deficiencies in the current UX that we're trying to fix? - What prior art exists on the backend and frontend, and how much of that can/should be reused? - Are there any scaling or load considerations that need to be accounted for? I'll probably implement this as 2-3 PRs in a chain touching different parts of the codebase. GPT via Codex will write 80% of the code, and I'll cover the last 20% of polish. Throughout the process I'll prompt it in the right direction when it runs up against questions it can't answer, and check its assumptions about the right way to push this out. I'll make sure that the tests cover what we need them to and that the resultant UX feels good. I'll own the responsibility for covering load considerations and be on the line if anything falls over. Does it look like software engineering from 3 years ago? Absolutely not. But it's software engineering all the same even if I'm not writing most of the code anymore.
- Rodeoclash 7mo ago
  This right here is my view on the future as well. Will the AI write the entire feature in one go? No. Will the AI be involved in writing a large proportion of the code that will be carefully studied and adjusted by a human before being used? Absolutely yes. This cyborg process is exactly how we're using AI in our organisation as well. The human in the loop understands the full context of what the feature is and what we're trying to achieve.
- fragmede 7mo ago
  I mean, what is the validation system? Either it exists in code, and thus can be discovered if you point the AI at repo, or... what, it doesn't exist? For the UX, have it explore your existing repos and copy prior art from there and industry standards to come up with something workable. Web scale issues can be inferred by the rest of the codebase. If your terraform repo has one RDS server, vs a fleet of them, multi-region, then the AI, just as well as a human, can figure out if it needs Google Spanner level engineering or not. (probably not) Bigger picture though, what's the process of a human logs an under specified ticket and someone else picks it up and has no clue what to do with it? They're gonna go ask the person who logged the bug for their thoughts and some details beyond "hurr Durr something something validation". If we're at the point where AI is able to make a public blog post shaming the open source developer for not accepting a patch, throwing questions back to you in JIRA about the details of the streaming validation system is well within its capabilities, given the right set of tools.

by malyk 7mo ago

contagiousflow 7mo ago

Why do you have a backlog then? If a current AI can do 100% of it then just run it over the weekend and close everything

fishpham 7mo ago
As always, the limit is human bandwidth. But that's basically what AI-forward companies are doing now. I would be curious which tasks OP commenter has that couldn't be done by an agent (assuming they're a SWE)
- Analemma_ 7mo ago
  This sounds bogus to me: if AI really could close 100% of your backlog with just a couple more humans in the loop, you’d hire a bunch of temps/contractors to do that, then declare the product done and lay off everybody. How come that isn’t happening?
  - fishpham 7mo ago
    Because there's an unlimited amount of work to do. This is the same reason you are not fired once completing a feature :-) The point of hiring a FTE is to continue to create work that provides business value. For your analogy, FTEs often do that by hiring temp, and you can think of the agent as the new temp in this case - the human drives an infinite amount of them
    - sarchertech 7mo ago
      Why hasn’t any of the software I use started shipping features at a breakneck speed then? The only thing any of them have added is barely working AI features. Why aren’t there 10x the number of games on steam? Why aren’t people releasing new integrated programming language/OS/dev environments? Why does our backlog look exactly the same as when I left for posterity leave 4 months ago?
      - fishpham 7mo ago
        Questions posed in bad faith can only be answered by the author.
        sarchertech 7mo ago
        Someone asked why the backlog doesn’t get finished. You answered that it does but the backlog just refills. So I asked where is the backlog evidence that the original backlog was completed. I’m still waiting for the evidence. I still haven’t seen externally verifiable evidence that AI is a net productivity boost for the ability to ship software. That doesn’t mean that it isn’t. It does mean that it isn’t big enough to be obvious. I’m very closet watching every external metric I can find. Nothing yet. Just saw the steam metrics for January. Fewer titles than January last year.
    - catmanjan 7mo ago
      Sounds more like busy work rather than something that makes money

lbrito 7mo ago

Then why isn't it? Just offload it to the clankers and go enjoy a margarita at the beach or something.

Gud 7mo ago
There are plenty of people who are enjoying margarita by the beach while you, the laborer, are working for them.
- lbrito 7mo ago
  Preach. That's always been the case though, AI just makes it slightly worse.

dwa3592 7mo ago

>>I look at my ticket tracker and I see basically 100% of it that can be done by AI. That's a sign that you have spurious problems under those tickets or you have a PM problem. Also, a job is a not a task- if your company has jobs which is a single task then those jobs would definitely be gone.

rockbruno 7mo ago

I think the "well defined prompt" is precisely what the person you responded to is alluring to. They are saying they don't get worried because AI doesn't get the job done without someone behind it that knows exactly what to prompt.

gordonhart 7mo ago

Here's an example ticket that I'll probably work on next week: Live stream validation results as they come in The body doesn't give much other than the high-level motivation from the person who filed the ticket. In order to implement this, you need to have a lot of context, some of which can be discovered by grepping through the code base and some of which can't: - What is the validation system and how does it work today? - What sort of UX do we want? What are the specific deficiencies in the current UX that we're trying to fix? - What prior art exists on the backend and frontend, and how much of that can/should be reused? - Are there any scaling or load considerations that need to be accounted for? I'll probably implement this as 2-3 PRs in a chain touching different parts of the codebase. GPT via Codex will write 80% of the code, and I'll cover the last 20% of polish. Throughout the process I'll prompt it in the right direction when it runs up against questions it can't answer, and check its assumptions about the right way to push this out. I'll make sure that the tests cover what we need them to and that the resultant UX feels good. I'll own the responsibility for covering load considerations and be on the line if anything falls over. Does it look like software engineering from 3 years ago? Absolutely not. But it's software engineering all the same even if I'm not writing most of the code anymore.

Rodeoclash 7mo ago
This right here is my view on the future as well. Will the AI write the entire feature in one go? No. Will the AI be involved in writing a large proportion of the code that will be carefully studied and adjusted by a human before being used? Absolutely yes. This cyborg process is exactly how we're using AI in our organisation as well. The human in the loop understands the full context of what the feature is and what we're trying to achieve.
fragmede 7mo ago
I mean, what is the validation system? Either it exists in code, and thus can be discovered if you point the AI at repo, or... what, it doesn't exist? For the UX, have it explore your existing repos and copy prior art from there and industry standards to come up with something workable. Web scale issues can be inferred by the rest of the codebase. If your terraform repo has one RDS server, vs a fleet of them, multi-region, then the AI, just as well as a human, can figure out if it needs Google Spanner level engineering or not. (probably not) Bigger picture though, what's the process of a human logs an under specified ticket and someone else picks it up and has no clue what to do with it? They're gonna go ask the person who logged the bug for their thoughts and some details beyond "hurr Durr something something validation". If we're at the point where AI is able to make a public blog post shaming the open source developer for not accepting a patch, throwing questions back to you in JIRA about the details of the streaming validation system is well within its capabilities, given the right set of tools.