AI is great enabler for stuff that you don't want to be good at, it cut a ton of chore type jobs out of my workflow, but for stuff you do want to get better and care for, it's both joy killer, and if you're not careful you will only learn how to prompt, not how the stuff works.
I love code as a craft. I love spending time designing the perfect abstraction. I love seeing it come together in the implementation stage. I love the troubleshooting process and the understanding that comes when you finally engage with the root cause of the issue. I love all of this so much that I ship little, all my time is spent in process.
I also love code as a tool. I love working tirelessly towards describing a goal and then watching it come to completion. I love knowing my projects consume terabytes of data and spit out useful results. I love seeing my assumptions on the outcome proved right or wrong.
Now I can do the latter without the former, and it leaves me deeply conflicted. A large part of me is more excited than I've ever been. Another part of me is quite sad, and this is unfortunately the part where my ego lives. For now, I keep it in check by asking the LLM to describe the pros/cons of alternative architectures. That way I stay learning about the products I create.
So it all wishes and prayers? no wonder software quality is down.
I ultimately think learning how other people structure programs is an enriching task and not one that should cause you to dig in and discredit differently-shaped approaches.
Learning from others is great. But there should be actually something to learn. When someone says
so long as you're not writing the code or specifying exactly how it should work.
A software is the recipe for some process. The code is the formal version where everything is exhaustively specified. Not thinking about the code means you’ve stopped thinking about the software somewhere and no longer can say if it’s ok or not.
Axiom: A software is the recipe for some process. The code is the formal version where everything is exhaustively specified.
P: Not thinking about the code
Q: means you’ve stopped thinking about the software somewhere and no longer can say if it’s ok or not.
Modern computing is an exercise in trusting abstractions and then zooming into the abstractions and figuring out what went wrong when something breaks. Just because I wrote a web route doesn't mean I've audited the code behind the web framework, the event loop, the HTTP implementation, the TCP implementation and so forth. By your argument then I've already stopped thinking about my software and can't tell you if it's okay or not.
I'm sympathetic to both the perspective of sadness from the loss of hand coding and the perspective of joy from working at a higher level of abstraction, despite its costs in understanding. It actually seems very simple to me to hold both perspectives within me.
Once that’s done, there’s a matter of accountability where you can report the issue to the people responsible for that. Then because they know their own code they can repeat what you did and try to find where things went wrong.
That chain of accountability is the main issue there. We still have tower of abstraction, but no one knows about their layers. Accountability is lost and with it the trust is gone.
I never care about code, whether you wrote the majority of it or it’s just a glue that hold several library. What I care about is that the semantics of that module that I interact or build upon can be trusted, and when something wrong is an accident and not a daily event.
Even when you’re writing an application and not a library or a platform, you’re not free to write whatever. Your users depends on you, and themselves may have clients that depends on them. Being cavalier about what you write is just recklessness and in any other (real in some countries) type of engineering, it would be labelled as malpractice.
Right this is the main difference between our viewpoints. I don't work on completely open systems. A lot of my life I've worked on closed platforms, cloud runtimes, a mix of work that's been in my control and out of my control. I've filed my share of AWS tickets but ultimately most of them ended up not fixed by AWS. I've made peace with not having accountability for layers of the stack and am comfortable assuming that there are bugs on the foundation that I have to work around.
> Being cavalier about what you write is just recklessness and in any other (real in some countries) type of engineering, it would be labelled as malpractice.
An old critique of software engineers that I've always found flimsy and find that Hillel Wayne addresses well: https://hillelwayne.com/post/are-we-really-engineers/
Software is built on wishes and prayers. Programmers don't ship pixels to be installed in monitors, nor do we (mostly) work with compiler internals. We write a detailed set of instructions and hope that a bunch of systems we don't necessarily comprehend follow them well enough to get the intended results. It works because some folks got together and wrote down their wishes and prayers so good that others were able to understand and follow them later.
I've done a lot of functional coding in the past (in academia, in Haskell as a hobby, and Scala for a unicorn where I was an early hire.) This probably affects how I think. But I find it quite natural to organize my code this way. After all the fundamental data structures and the hierarchies relating them are what often determine core properties of your programs such as being CPU, Memory, or IO bound.
I also work as a pretty senior engineer and my tasks before agents were usually about leading a team to implement something. I would often do the v0 implementation to make sure we met customer requirements and then take a step back and help the team scale the service up. These days the team is a lot smaller and maybe just another engineer; the agents make up the rest.
so ... this conversation isn't really about you then, is it.
For example recently I did tiny little hobby project, taking metrics of ESPHome/homeassistant MQTT and pushing it into prometheus. Coded the main parts, told LLM to do the boring part of setting up test suite, guided it thru making tests, it worked fine, tested it, then told LLM to do another boring task, taking all the datatypes it support and unit conversions (which is hundreds).
I got to do all the fun design stuff, but had code review assistant that also did all the boring tasks.
It's like making animation but you only have to make keyframes and initial coloring, with AI filling the blanks, just cutting out the tedium
so it's just like making really crappy animation?
I’ve been coding over four decades and it is clear to me that most programmers don’t know how the stuff works, and not just script kiddies but some PhDs I worked with.
For those who want to know how it works, LLMs are massive enablers. I’ve written so many debugging and inspection tools with an LLM; had a model explain the assembly language produced; had rubber duck conversations with it. I’m having such fun tbh.
You are aware that the LLM (or anything/anyone) explaining stuff to you is just going to atrophy if you don't use it, so maybe you weren't actually learning but just scratching a curiosity itch.
On the road to wire heading.
I think the benefit is that now I get to choose what I want to focus my limited attention on; from a much broader range of subjects; with expert knowledge on tap. For sure, some of it was just scratching an itch. I didn’t waste much time getting to that point before I could go down another interesting rabbit hole. It’s just much more fun!
You're saying that I must not be good in writing tests, irregardless on how I feel about test writing.