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raw_anon_1111 10 hours ago

The average tenure of a developer for the longest was 2.5 years not to mention the developer changing teams, even before AI many developers didn’t know how the code they were brought in to maintain works.

> My English instructions do not leave any residual growth. I learn nothing to send back up the chain, and I know nothing of what's below. Why should I exist?

When you use Claude code, tell it to keep a markdown file updated with the what and the why. Instead of just “Do $y”, “Because of $x I need to do $y”. If it is updated in the markdown file, it will be recorded and sometime the agent will come up with code and mske changes that are correct. But use cases you didn’t think about. You can then even ask it “why did it do $x” that you weren’t expecting but oh yeah, it was right.

> Why should I exist?

That’s the wrong question, the correct question is “why is my employer paying me?”. Your employer is paying you to turn well defined requirements into working code to either make them money or to save them money if (the royal) you are a mid level ticket taker. If someone is working at that level, that’s what they are regardless of title.

No one cares if either you or the LLM decided to use a for loop or a while loop.

At higher levels you are responsible for taking your $n number of years of experience to turn more ambiguous, more impactful, larger scoped projects into working implementations that are done on time, on budget and meets requirements. Before LLMs, that meant a combination of my own coding, putting a team together and delegating and telling my director/CTO that this isn’t something we should be doing in house (ie a Salesforce or Workday integration) at all.

Now add to the mix between all those resources - a coding agent. In either case, I as anything above ticket taker, probably haven’t looked at a line of code first. I test for does it meet the functional and non functional requirements and then mostly look at the hot spots - concurrency issues, security issue, and are there any scalability issues that are obvious before I hammer it with real world like traffic - web request or transactions for an ETL job.

And before the pearl clutching starts, I started programming as a hobby in the 80s in assembly and spent the first decade and a half of my career doing C bit twiddling on multiple mainframes, PCs, and later Windows CE devices.

beej71 9 hours ago | parent [-]

>At higher levels you are responsible for taking your $n number of years of experience to turn more ambiguous, more impactful, larger scoped projects into working implementations that are done on time, on budget and meets requirements.

Is this not a job for LLMs, though?

raw_anon_1111 9 hours ago | parent [-]

LLMs are good at turning well defined requirements to code.

But even now it’s struggling on a project to understand the correlation between “It is creating Lambda code to do $x meaning it needs to change the corresponding IAM role in CloudFormation to give it permission it needs”

Spivak 8 hours ago | parent [-]

The LLMs are fantastic at writing terraform when you tell it what to do which is a huge timesaver, but good heavens is it terrible at actually knowing what pieces need to be wired up for anything but the simplest cases. Job security for now I guess?

raw_anon_1111 8 hours ago | parent [-]

I was able to one shot CDK, Terraform and CloudFormation on my last three projects respectively (different clients - different IAC). But I was really detailed about everything I needed and I fed ChatGPT the diagram.

I guess I could be more detailed in the prompt/md files about every time it changes lambda code, check the permissions in the corresponding IAC and check to see if a new VPC endpoint is needed.