Tech Leaders Using AI Are Thriving—Here’s Why

AI-powered tools like Copilot, Cursor, or SonarQube help teams write and review code faster. They catch mistakes, suggest improvements, and even generate boilerplate code.

What you might notice:

• Pull requests are getting approved faster.
• Developers are shipping more AI-assisted code.
• AI is catching small bugs before they reach production.

Where leadership is still needed:

• Developers may rely too much on AI, weakening problem-solving skills.
• AI suggests changes, but it does not understand project-specific best practices.
• AI does not verify that code meets business needs, you still need to review carefully.

AI-powered tools like Otter.ai, Fireflies, and Notion AI can summarize meetings, generate action items, and suggest follow-ups. This means fewer long meetings and more time for real work.

What you might notice:

• Standup summaries arrive automatically.
• Fewer status meetings as AI tracks progress.
• Documentation and follow-ups are generated instantly.

What leadership still requires:

• Some engineers struggle in silence—AI will not catch that.
• AI can track progress, but it cannot detect team misalignment.
• AI-generated notes do not replace meaningful team discussions.

AI can screen resumes, rank candidates, and suggest interview questions.

What you might notice:

• Resume filtering happens instantly.
• AI is ranking candidates before interviews.
• Hiring processes are moving faster than before.

Why leadership is still essential:

• AI cannot measure soft skills or team culture fit.
• AI may reinforce hiring biases if not properly managed.
• AI can assist with hiring, but mentorship still requires human leadership.

AI is handling routine engineering tasks like writing unit tests, generating documentation, and detecting security issues.

What you might notice:

• Boilerplate code is being written automatically.
• AI is suggesting test cases before engineers write them.
• Security vulnerabilities are flagged earlier in development.

What tech leads must do:

• Encourage deep learning of system architecture and debugging skills.
• Use AI for efficiency, but make sure the team still develops critical thinking.
• Ensure engineers work on meaningful problems, not just AI-assisted coding.

AI is making many daily tasks faster, from code reviews to project management. But it is not replacing the role of a tech lead—it is just changing how leadership works.

What you might notice:

• AI is assisting with project tracking, reducing manual work.
• Engineers are adopting AI-powered tools for debugging and coding.
• AI-generated insights are helping with technical decisions.

What leadership still requires:

• You must ensure AI aligns with long-term team and company goals.
• You need to focus on mentorship, as AI cannot develop your team’s leadership skills.
• Decision-making still requires human oversight—AI cannot set engineering strategy.

AI is already changing how tech leads work every day. To stay effective:

AI will not replace leadership—it will redefine it.

Cheers,
Gábor