Product and design are the new bottlenecks(jampa.dev) |
Product and design are the new bottlenecks(jampa.dev) |
This is just a blatant lie lmao, this is the core tenant that all these AI takes rely on and it is just flat out not true.
as elon musk said, the next phase is 100% AI run companies, any sort of a human in a loop, even if in a minimal role, will collapse the productivity
Do most engineers find this to be true? For me the balance switched within a few years of being a senior (nearly a decade ago). Writing code is easy, negotiating over what code to write takes time.
But I have worked in some areas that its not like that. What we are building is decided pretty quick, but the implementation takes a month of two.
my days are spent in meetings discussion how to implement things or why do it certain ways - when most of that time spend asking inevitably turns into "when can this be ready?"....well if you didnt have me stuck discussing it for the last 6 months it would've been ready yesterday like you wanted.
And by the way, one thing is missing from the OP graph: i now spend maybe 50% less time writing my own code, and 100% more time fixing my juniors PRs and fixing production issues after my reviews miss issues...
Interestingly though, the experimentation process itself seems very under-optimized, and so it is frequently the bottleneck.
Product and design were always the bottleneck. Engineering speed was never the issue, it was the politics and indecision in product that always slowed engineering teams down. I can't count how many prep meetings product had before they presented to their boss what the new font and color looks like. They basically had a team of PMs just running around creating busy work and making decision based on pure whim and personal feeling, without actually looking at any data. And God forbid they ever talk to customers. Ew, who cares about what they have to say.
Engineers like to claim everyone else is their problem, when in fact, it's often the case that engineers are their own problem.
Bottlenecks happen everywhere.
Depends. It definitely can be. When you get those people who want to spend weeks going back and forth over whether the button should be red or slightly darker red, as if they can somehow figure out the right answer from gut feeling alone, not realizing that in that time they could have tried both and learned from it, all while delivering other things of value on top, engineering has no hope of becoming the bottleneck.
That being said, I've recently made a few light weight apps for myself with Claude and I've easily spent 4x the time hand tuning the UI compared to implementing business logic / core features. Super fun tbh
That's pretty much always been true for greenfield that doesn't require large swaths of boilerplate (e.g. integrations)
It starts with "I know/can handle issues from infra to design" to regroupings of focus, often DevOps / code / design. But companies also might split focus by user concerns, like the "Admin console team" vs. "End user team". That depends on the product and the complexity of the specialist concerns.
I think across the board there is going to be a blurring of management and engineering. We see the value of "product engineers" now but they are starting to eat some of PM's lunch. On the other side, "technical PMs" are more valuable, as they come at things from the other side. The driver for this change is that both are using a shared context to bridge the gap from "business concerns + product requirements" to code.
One 16" pizza can be a lunch for 2, maybe 3 people. Which, by the way, is a very good size for a team.
New idea: 1-2 pizza companies
> Product engineers assume traditional PM roles, including owning the roadmap, engaging with users, analyzing data, framing opportunities, and determining what to build. However, they do not replace a PM. The PM still provides context but is no longer the main driver of implementation.
How is this different from a "lead"?
I'm a frontend specialist developer currently taking some time off to reskill - and trying to decide exactly which direction to go. My thinking was that I would need to lean into design and product - leverage my technical knowledge in building interfaces to be able to inform the product side. Knowing what is easy or hard to build hopefully would speed up the product side.
I am not exactly a big guy but even I can easily eat two slices of pizza and I am talking about real slices of the Costco pizza which I love for its value for money. I can't imagine how you could feed a team of eight with a single pizza.
If we believe the AI-influenced system will be faster, more prolific and more experimental (cheaper experiments), then it seems human attention and the rate at which humans can change (individually, processes, tools, teams, etc) becomes the bottleneck.
In that system, the designer and PM functions become more important in addressing that bottleneck - in producing solutions to best overcome those bottlenecks?
Continuous learning systems aren't there yet, though we have the proto-learning systems with things like agents and skills. What does it look like when we have AI systems building systems for other AI systems?
Say what?
Technology has plenty of room to keep marching forward, but the next substantive improvement here will see it no longer be AI. It will become AGI.
If you replace this assumption with “we’re going to see the same magnitude improvement in the next six months that we saw in the last six months” then the post is already outdated. You can’t hire new people fast enough to effectuate this strategy before you’ll have to change course.
Instead, I’d propose allowing a bit more anarchy in your teams, letting people know that it’s OK to take the initiative, even if it means stepping on each others toes. Management should be clear that critical risks need to be mitigated (eg no security vulns, no prod outages) and be strict about those (to the point where you can say ‘yolo pushing a prod outage will affect your bonus and be added to your HR record’), but otherwise let people—anyone—code.
Good. Fullstack roles are like giving away free options contracts away to businesses when they were only buying some stock. Sure, you don't work twice as much as fullstack and shouldn't get twice the pay, but the flexibility should have a price.
When fullstack engineers are making just as much as front-end/backend only engineers, they are giving the options away for free. Engineers simply didn't stand up for themselves to assert their worth in these positions, which led companies to prioritize hiring them over specialists. Any decrease in fullstack positions will help our compensation.
Yup, so far the LLMs just haven't been as great at product and design as us. But they'll get there.
Sometimes there’s valid reasons for addressing technical debt and reworking things to be better in the future… and other times people are just rewriting working code because reasons™.
Encountering the latter can be quite demotivating, especially when it turns to nitpicking over small stuff or keeping releases back for no good reason. Personally, I try to lean away from that and more into the “if it works, it works” camp (as long as you don’t ignore referential integrity and don’t mess up foundational logic).