AI tools are actually improving at a rate faster than most junior engineers I have worked with, and about 30% of junior engineers I have worked with never really “graduated” to a level that I would trust them to do anything independently, even after 5 years in the job. Those engineers “find their niche” doing something other than engineering with their engineering job titles, and that’s great, but don’t ever trust them to build you a bridge or whatever it is they seem to have been hired to do.
Now, as for AI, it’s currently as good or “better” than about 40% of brand-new fresh from the BS program software engineers I have worked with. A year ago that number probably would have been 20%. So far it’s improving relatively quickly. The question is: will it plateau, or will it improve exponentially?
Many things in tech seem to have an exponential improvement phase, followed by a plateau. CPU clock speed is a good example of that. Storage density/cost is one that doesn’t seem to have hit a plateau yet. Software quality/power is much harder to gauge, but it definitely is still growing more powerful / capable even as it struggles with bloat and vulnerabilities.
The question I have is: will AI continue to write “human compatible” software, or is it going to start writing code that only AI understands, but people rely on anyway? After all, the code that humans write is incomprehensible to 90%+ of the humans that use it.
I’m seeing exactly the opposite. It used to be the junior engineers understood they had a lot to learn. However with AI they confidently try entirely wrong changes. They don’t understand how to tell when the ai goes down the wrong path, don’t know how to fix it, and it takes me longer to fix.
So far ai overall creates more mess faster.
Don’t get me wrong, it can be a useful tool you have to think of it like autocomplete or internet search. Just like those tools it provides results but the human needs judgement and needs to figure out how to apply the appropriate results.
My company wants metrics on how much time we’re saving with ai, but
I have to spend more time helping the junior guys out of the holes dug by ai, making it net negative
it’s just another tool. There’s not really a defined task or set time. If you had to answer how much time autocomplete saved you, could you provide any sort of meaningful answer?
I’ve always had problems with junior engineers (self included) going down bad paths, since before there was Google search - let alone AI.
So far ai overall creates more mess faster.
Maybe it is moving faster, maybe they do bother the senior engineers less often than they used to, but for throw-away proof of concept and similar stuff, the juniors+AI are getting better than the juniors without senior support used to be… Is that a good direction? No. When the seniors are over-tasked with “Priority 1” deadlines (nothing new) does this mean the juniors can get a little further on their own and some of them learn from their own mistakes? I think so.
Where I started, it was actually the case that the PhD senior engineers needed help from me fresh out of school - maybe that was a rare circumstance, but the shop was trying to use cutting edge stuff that I knew more about than the seniors. Basically, everything in 1991 was cutting edge and it made the difference between getting something that worked or having nothing if you didn’t use it. My mentor was expert in another field, so we were complimentary that way.
My company (now) wants metrics on a lot of things, but they also understand how meaningless those metrics can be.
I have to spend more time helping the junior guys out of the holes dug by ai, making it net negative
Shame. There was a time that people dug out of their own messes, I think you learn more, faster that way. Still, I agree - since 2005 I have spend a lot of time taking piles of Matlab, Fortran, Python that have been developed over years to reach critical mass - add anything else to them and they’ll go BOOM - and translating those into commercially salable / maintainable / extensible Qt/C++ apps, and I don’t think I ever had one “mentee” through that process who was learning how to follow in my footsteps, the organizations were always just interested in having one thing they could sell, not really a team that could build more like it in the future.
it’s just another tool.
Yep.
If you had to answer how much time autocomplete saved you, could you provide any sort of meaningful answer?
Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?___
Shame. There was a time that people dug out of their own messes, I think you learn more, faster
Yes, that’s how we became senior guys. But when you have deadlines that you’re both on the hook for and they’re just floundering, you can only give them so much opportunity. I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base
Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?
We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home
I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base
I guess I’m lucky, before here I always had 100% control of the code I was responsible for. Here (last 12 years) we have a big team, but nobody merges to master/main without a review and screwups in the section of the repository I am primarily responsible for have been rare.
We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home
I have been getting actively recruited - six figures+ - for multiple openings right here in town (not a huge market here, either…) this may be the time…
Now, as for AI, it’s currently as good or “better” than about 40% of brand-new fresh from the BS program software engineers I have worked with. A year ago that number probably would have been 20%. So far it’s improving relatively quickly. The question is: will it plateau, or will it improve exponentially?
AI tools are actually improving at a rate faster than most junior engineers I have worked with, and about 30% of junior engineers I have worked with never really “graduated” to a level that I would trust them to do anything independently, even after 5 years in the job. Those engineers “find their niche” doing something other than engineering with their engineering job titles, and that’s great, but don’t ever trust them to build you a bridge or whatever it is they seem to have been hired to do.
Now, as for AI, it’s currently as good or “better” than about 40% of brand-new fresh from the BS program software engineers I have worked with. A year ago that number probably would have been 20%. So far it’s improving relatively quickly. The question is: will it plateau, or will it improve exponentially?
Many things in tech seem to have an exponential improvement phase, followed by a plateau. CPU clock speed is a good example of that. Storage density/cost is one that doesn’t seem to have hit a plateau yet. Software quality/power is much harder to gauge, but it definitely is still growing more powerful / capable even as it struggles with bloat and vulnerabilities.
The question I have is: will AI continue to write “human compatible” software, or is it going to start writing code that only AI understands, but people rely on anyway? After all, the code that humans write is incomprehensible to 90%+ of the humans that use it.
I’m seeing exactly the opposite. It used to be the junior engineers understood they had a lot to learn. However with AI they confidently try entirely wrong changes. They don’t understand how to tell when the ai goes down the wrong path, don’t know how to fix it, and it takes me longer to fix.
So far ai overall creates more mess faster.
Don’t get me wrong, it can be a useful tool you have to think of it like autocomplete or internet search. Just like those tools it provides results but the human needs judgement and needs to figure out how to apply the appropriate results.
My company wants metrics on how much time we’re saving with ai, but
I’ve always had problems with junior engineers (self included) going down bad paths, since before there was Google search - let alone AI.
Maybe it is moving faster, maybe they do bother the senior engineers less often than they used to, but for throw-away proof of concept and similar stuff, the juniors+AI are getting better than the juniors without senior support used to be… Is that a good direction? No. When the seniors are over-tasked with “Priority 1” deadlines (nothing new) does this mean the juniors can get a little further on their own and some of them learn from their own mistakes? I think so.
Where I started, it was actually the case that the PhD senior engineers needed help from me fresh out of school - maybe that was a rare circumstance, but the shop was trying to use cutting edge stuff that I knew more about than the seniors. Basically, everything in 1991 was cutting edge and it made the difference between getting something that worked or having nothing if you didn’t use it. My mentor was expert in another field, so we were complimentary that way.
My company (now) wants metrics on a lot of things, but they also understand how meaningless those metrics can be.
https://clip.cafe/monsters-inc-2001/all-right-mr-bile-it/
Shame. There was a time that people dug out of their own messes, I think you learn more, faster that way. Still, I agree - since 2005 I have spend a lot of time taking piles of Matlab, Fortran, Python that have been developed over years to reach critical mass - add anything else to them and they’ll go BOOM - and translating those into commercially salable / maintainable / extensible Qt/C++ apps, and I don’t think I ever had one “mentee” through that process who was learning how to follow in my footsteps, the organizations were always just interested in having one thing they could sell, not really a team that could build more like it in the future.
Yep.
Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?___
Yes, that’s how we became senior guys. But when you have deadlines that you’re both on the hook for and they’re just floundering, you can only give them so much opportunity. I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base
We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home
I guess I’m lucky, before here I always had 100% control of the code I was responsible for. Here (last 12 years) we have a big team, but nobody merges to master/main without a review and screwups in the section of the repository I am primarily responsible for have been rare.
I have been getting actively recruited - six figures+ - for multiple openings right here in town (not a huge market here, either…) this may be the time…
LOL sure
I’m not talking about the ones that get hired in your 'leet shop, I’m talking about the whole damn crop that’s just graduated.