I note that AI is getting better at writing code, and tech companies are laying off engineers as a result. I also recognize that understanding the problem, making sound architectural decisions, anticipating failures, balancing trade‑offs, and building maintainable systems are skills that go beyond code generation. While AI can help us move faster, speed alone doesn't guarantee good software.
AI can help us move faster, but speed alone doesn't guarantee good software.
I decided that engineers should prioritize development of higher‑order thinking skills rather than focusing on raw coding output.
This decision stems from observing a wave of engineer layoffs tied to AI‑driven code generation; AI can already write syntactically correct code quickly, so the differentiator becomes the ability to design, reason, and maintain complex systems.
After years in software engineering, I've learned that a person's real expertise goes far beyond what's written on their resume.
It's in the problems they've solved, the decisions they've made, the trade‑offs they've considered, and the lessons they've learned along the way.
The challenge is building an AI that represents us accurately, respects our privacy, and knows when to let a human take over.
These observations expand my earlier view that professional networks should surface deeper expertise, emphasizing that any AI‑mediated system must balance accurate representation, privacy safeguards, and appropriate human hand‑off.
Good engineering isn't about writing more code. It's about making the right trade‑offs.
The best solution isn't the most sophisticated one; it's reliable, maintainable, performs well, and solves the actual problem.
Knowing what to build, why to build it, and how to build it well remains the real skill.
What if our professional networks could help us discover not just who people are, but also what they know and how they think?
Imagine AI agents helping us find the right people, exchange knowledge, and build more meaningful connections.
- Trust in AI representation of expertise is a key concern.
These open questions will guide future design decisions for AI‑augmented professional networks.
- Privacy safeguards for knowledge‑profile data are essential.
- The human element must be retained alongside AI‑mediated introductions.
- Incentives are needed for users to let AI act on their behalf.