The software industry has a hiring problem. We've spent decades optimizing for algorithmic wizards who can reverse binary trees in their sleep, while completely ignoring the skills that actually matter for building great software. Now, with AI agents writing code faster than any human, this misalignment isn't just inefficient, it's existential.
The concept of "weak engineers" exposes what many already knew: technical skill alone doesn't make someone effective. Engineers share stories of brilliant coders who couldn't communicate, couldn't think strategically, and couldn't deliver real value.
In the age of AI, these problems aren't just annoying anymore. They're existential.
What we got wrong about engineering
A "weak" engineer excels at technical tasks but struggles with broader skills needed for impactful software. They crush algorithmic interviews and memorize design patterns, but can't grasp trade-offs, communicate with stakeholders, or align work with business goals.
Our entire hiring process selects for this profile. We test candidates on problems they'll never solve while ignoring skills they'll use daily.
The AI twist: Now that coding agents generate boilerplate code, implement algorithms, and suggest system designs, pure technical skill matters less than ever. What matters is knowing what to build, why to build it, and how to guide AI tools toward the right solutions.
A "weak" engineer in the AI era blindly accepts AI outputs without questioning correctness, security, or business fit. They let GitHub Copilot write database schemas without considering scalability, or implement AI-suggested features without understanding trade-offs.
Critical thinking becomes essential
Critical thinking has long been undervalued compared to pure technical skills. In an AI-driven world, this becomes essential for survival.
Why AI makes this urgent: AI agents excel at executing well-defined tasks but struggle with ambiguity. When stakeholders say "make the app faster," AI can't figure out what that means. Strong engineers bridge this gap by translating vague requirements into clear instructions and ensuring solutions solve the right problems.
Consider building an AI-driven recommendation system. Your coding agent might generate algorithms that maximize click-through rates. A weak engineer implements them directly. A strong engineer asks: Do these algorithms respect user privacy? Will they scale cost-effectively? Do they align with our brand values?
Communication: your unfair advantage
Communication is critical for collaboration and business alignment, yet it's often ignored in favor of coding skills. The AI era makes this even more valuable.
Engineers increasingly act as bridges between AI capabilities and business strategy. They must craft precise instructions for AI tools, explain AI-generated solutions to non-technical stakeholders, and justify why they modified or rejected AI suggestions.
Strong engineers use communication as their competitive advantage in an increasingly automated world.
Hiring needs to evolve
Current hiring practices are broken. LeetCode problems that AI can solve in seconds tell us nothing about candidates' ability to work with AI tools or make strategic decisions.
AI-era hiring should include:
- Giving candidates AI-generated code to critique for performance, security, or business alignment
- Pair programming sessions with AI collaboration
- Testing system design skills with AI assistance
- Evaluating how candidates refine and improve AI outputs
The goal isn't eliminating technical assessment. It's testing technical judgment rather than technical memorization.
What strong engineers look like now
In the AI era, strong engineers are orchestrators, not just implementers. They guide AI tools toward business goals, translate ambiguity into clarity, evaluate trade-offs AI can't understand, and communicate across disciplines to align technical decisions with business strategy.
They're not necessarily the fastest coders. They're people who see the bigger picture and use AI to achieve it.
The path forward
The shift is already happening. Companies that adapt their hiring, training, and culture will attract engineers who thrive in AI-augmented workflows.
For individuals: Focus on developing judgment, communication, and strategic thinking. Learn to work with AI tools rather than competing against them.
For companies: Rethink what you value and test for. Hire for potential impact, not just technical performance.
For the industry: Build more diverse, thoughtful teams that deliver real value rather than just impressive algorithms.
The age of the "10x engineer" who cranks out code in isolation is ending. The future belongs to engineers who can think critically, communicate clearly, and orchestrate AI to solve meaningful problems.
Sources: Insights from Sean Goedecke's "Weak Engineers" and Hacker News discussion.
