From one piece Nicole Forsgren: Leading high-performing engineering teams in the age of AI - The Pragmatic Summit 18 beliefs, in the piece's order there
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right now, that whole front end has been like kind of smooshed because many times we can just like prototype really really rapidly and kind of solidify some of what we're thinking in terms of like ideas and coding. So I fully expect that part of the outer loop is just going to be collapsed as well, right?
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For that to be true, agents need to be able to see and understand the system. And agents need to be able to improve the things that need fixed. For that to be true, humans need to be able to see and understand the system and then take action to fix it. Uh and for that to be true, we got to see the system.
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korrents.com
Working too hard is not burnout, it is tiredness; burnout needs your values to be out of alignment with the work.Their words
It's working too hard, right? But that actually isn't burnout. That's just like getting tired. Another piece that's super critical to burnout is not having your values aligned.
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And so, um I'm seeing across at least a handful of companies that explicit exec sponsorship makes a huge difference in not just using them, but trying new things and feeling safe to fail within, you know, kind of guardrails.
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korrents.com
You cannot mandate a tool developers dislike — they will quietly spin up the one they wanted.Their words
I'm going to sound old when I say this, but like I one time had a company tell me, "Oh, well, they have to use that CI/CD system." I'm like 20 bucks, they're just spinning up Jenkins. And they were, right?
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I I will say I tend to start with adoption. I am not a fan of an adoption metric. I don't like it, but also devs are like a gloriously cranky bunch.
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Some teams can, and but when they do it, they're doing it very, very intentionally. They don't say they're sacrificing quality. They say they're making a risk-based decision.
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Oh, I agree. You know, one is being able to clearly articulate the problem or the thesis or the idea. Without trying, I don't get there.
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We may have a handful of genies, but that's different from having a handful of friends, right? In part because the energy's different, the conversations are different. Also, they just agree with us constantly.
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Uh well, tech is easy, people are hard. And so, you know, sometimes getting the flow really is about understanding what I'm doing, having very clear direction and goals and and knowing what my what my work is doing.
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Well, now I'm getting feedback so quickly that I'm having to sometimes rebuild my mental model dozens of times in like a 30-minute period.
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And humans max out at about like 3 to 4 hours a day. Like really really hard deep work, right? Um which always makes me laugh when executives are like, "We need 8 hours of intense work."
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korrents.com
Delivery will keep being slow until companies apply AI to the human, business-process half of it, not just to coding.Their words
a lot of companies haven't started until now thinking about how we could apply AI to the very human, very business process part of it. And so, that will keep slowing us down until we find a way to to address it, right?
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korrents.com
The processes organisations build to make work uniform are usually the same processes that slow the work down.Their words
Or like all of the the things that we have structured process around to try to make things more uniform are often the things that slow us down.
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korrents.com
Release management is human group sense-making, and it does not scale to the volume of change AI now produces.Their words
so many times that process has been managed by humans because you're selecting the right candidate build and you're verifying it and you're thinking, you know, you're figuring out cherry picks and then you like rebundle and then you send it out and that doesn't scale if you have one or two or a handful of people trying to make group decisions and do group sense making.
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And not only that, but like humans were already a bit of a bottleneck in the review process. Now it can be worse because things that we fairly straightforward changes that some companies had automation around reviewing, they've removed that reviewing because if AI is involved and they're worried about the verifiability or the reliability of the code.
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korrents.com
AI did not create the bottlenecks in software delivery; it threw gas on processes everybody already knew were weak.Their words
There were a handful of people probably managing a security review process or a launch process or a deployment process or, you know, sometimes reviews were a little slow and they got backed up. Well, now we just threw gas on the fire and so all of that is a problem.
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And so, like in the immediate term, yeah, we were getting more out, but now our systems, whether technology systems or human systems or processes, are really kind of getting overwhelmed.