AI & Tools
How AI Is Changing Tech Jobs
The honest answer is somewhere between the two extremes you'll see online -- "AI changes nothing" and "AI replaces everyone" -- here's a more grounded look.
What's Genuinely Changing
- Less time spent writing repetitive boilerplate code, more time reviewing, architecting, and debugging
- New roles emerging specifically around AI application development (prompt engineering, RAG systems, AI product features)
- Rising expectations that developers can evaluate AI-generated code critically, not just produce code from scratch
- Faster prototyping cycles, changing how quickly ideas can be validated before committing real engineering time
What's Staying the Same
- Understanding a real business problem well enough to design the right solution -- still a fundamentally human judgment call
- System design and architecture decisions that weigh genuine, context-specific tradeoffs
- Debugging complex, novel issues that don't match common patterns an AI model has seen before
- Communication, collaboration, and mentoring -- still core to almost every real engineering role
How to Position Yourself Well
Rather than treating AI tools as a threat to avoid or a magic shortcut to lean on entirely, the strongest position is becoming genuinely skilled at using them well -- knowing when they save real time, when to distrust their output, and how to review AI-generated code as critically as you'd review a colleague's pull request. That combination (strong fundamentals plus effective AI tool use) is increasingly what differentiates a strong candidate, more than either alone.
Frequently Asked Questions
Worth staying informed and adaptable, but most current evidence points toward role transformation (what the job involves shifting) rather than wholesale elimination for most engineering roles -- similar to how past major tooling shifts changed jobs without eliminating them. Continuing to build genuinely strong fundamentals remains the best insurance either way.
Yes -- AI Engineer, Prompt Engineer, and ML Platform Engineer roles have all grown significantly, and many existing roles (backend, full stack) increasingly list AI-tool fluency as a preferred or required skill in job descriptions.