lartin_muther

I moved from biz ops to full stack engineering in 2018. "Learn to code" they said. I did.

Earlier this year I got laid off for not having 10 years of experience or a ML graduate degree. I've applied to hundreds of jobs over the last several months and can count my follow-up interviews on one hand. You can say "you're probably just a bad developer." It's ok. I know I'm not.

I feel frustrated and disillusioned. Looking into becoming an electrician, which should keep me afloat until they roll out the electrician robots in a few years. If you're in a similar boat, best of luck to you.

1. Things besides “more code” need to happen for a good tech product to be built and released (ideation, quality assurance)

2. The market’s tunnel vision around generative AI tools (more code! more art!) creates an ecosystem-wide effect whereby emphasis and usage of tools for other things is boxed out. People have certainly built a ton of great AI tools for design, documentation, and dev tools — things that suggest bug fixes/refactors as you write, summarize dense onboarding docs, and create test data that looks like production data, for example — and it doesn’t mean companies will use them

3. Focusing on fixing the simple yet time-consuming problem of “more code! where is my more code?!!?” will balloon the responsibilities of these other areas, whose demands can grow exponentially (because complexity can, especially in software products)

4. Companies have thus left themselves with a perfect storm: (a) buckets of new code, (b) smaller “leaner” teams after layoffs (so less density of institutional knowledge), and (c) a drought of investment in tools that actually help with the most difficult parts of releasing good software products

5. They will find (if they haven’t already) that they quickly need to hire people back, this time with AI-related skills that thanks to AI’s newness basically no one has