How should software engineers adapt to AI-driven layoffs? With major tech companies laying off mid-level engineers due to AI efficiency gains, what strategies are engineers using to stay competitive? I'm interested in both immediate adaptations from those affected and how upcoming CS graduates are preparing for an AI-augmented industry. What does the engineering career look like in the future ? |
I expect to lean heavily on softer skills like "being able to collaborate with product owners help them figure out what they actually want to build", or "able to usefully simplify concepts in a way that helps non-developers make decisions."
I find it very confusing that everyone took the AI narrative at face value, and the AI "replacement" as fait accompli. Did it happen at all? At best, AI is intern level right now.
https://github.com/paradite/ai-replace-swe
Short answer: Leverage AI, become more productive with AI and make sure you can output more value than just AI itself. Also move up the value chain to product management, team management.
I’m actually _more_ worried about team managers than line engineers when it comes to AI impact.
It's less about personal development, but more on performance management.
https://www.wsj.com/lifestyle/careers/you-blamed-dei-for-hur...
Someone said that people would start blaming AI.
It’s not AI. There are too many people chasing too few jobs and the BigTech companies aside from Google are focusing on profitable segments.
The IPO market is dead and which caused the entire VC Ponzi scheme to collapse.
As far as upcoming CS graduates? They are screwed. Why would most companies want to hire new grads when there are proven experienced people looking for jobs?
1. Coordinated layoffs flood the market with talent forcing wages down overall and creating a chilling effect for existing employees. Believe it or not, layoffs are actually having the reverse effect from what some might think. They don’t make people want to leave, they make people scared to leave.
2. Wall Street loves layoffs.
3. Money is more expensive now.
4. Layoffs have a performative aspect for the incoming administration that all tech execs are so desperately trying to publicly please.
5. The narrative that “tech employees are lazy mooches” that’s been pushed by tech execs in alternative media has become mainstream. Places like the AllIn podcast and anything that Musk posts on Twitter have been pushing this narrative for a while and people have bought it. Since people think this now, it gives tech execs much more leeway in cutting employees “because they were underperforming” rather than “because we don’t have enough money” or “because Wallstreet wants us to.”
Ask any manager at big tech companies. They’ve been WANTING to hire for like 2 years now, but hiring freezes because of budget constraints have left them without the wanted headcount. Pretty strange that managers almost universally have been wanting to hire, but been told “no we don’t have the budget,” but then layoffs come through and it’s “because ai is handling all the work!”
I don't see companies keeping large engineering head counts when they can get working software in minutes from specs.
So, I suggest you become better in writing software specs.
Writing specs is safe for the foreseeable future because:
1. There is still no ai architecture that is comparable to human brain other than rot memory.
2. There is no enough data to train a model from such architecture if and when it's invented.
Salesforce (and other app builders) are buying those shovels (AI) to lower costs to build applications
I'm not sure that's really hedging your bets, since there are a bunch of potential futures where you might lose your job and those stocks lose value.
Though I’ll be surprised if they’re still hiring two years from now.