Hiring Software Engineers in the Agentic Era
The way software engineers build software has changed dramatically over the past two years. AI coding assistants, autonomous agents, and increasingly capable development tools are now part of many engineering teams' daily workflows. As a result, the skills that make someone an effective engineer are evolving—and technical hiring needs to evolve with them.
Many interview processes, however, still measure skills that are becoming less representative of real work.
The Problem with Traditional Interviews
Whiteboard interviews, LeetCode exercises, and lengthy take-home assignments were designed to evaluate problem solving and technical knowledge. While they can reveal aspects of a candidate's ability, they often test performance in environments that look nothing like modern software development.
Today's engineers rarely solve complex problems from memory without documentation, collaboration, or tools. Instead, they work alongside AI assistants, search documentation, iterate quickly, and review generated code critically.
An engineer who excels at memorizing algorithms isn't necessarily the engineer who can ship reliable software with AI in the loop.
Likewise, take-home projects frequently measure who has the most free time rather than who collaborates most effectively or makes the best engineering decisions.
What Great Engineers Do Differently Today
The strongest engineers are no longer simply fast coders. They're effective orchestrators.
They know how to:
- Break ambiguous problems into manageable tasks.
- Use AI to accelerate implementation without sacrificing quality.
- Verify AI-generated code instead of accepting it blindly.
- Debug incorrect suggestions efficiently.
- Ask better questions that lead to better solutions.
- Balance speed with maintainability and security.
These are fundamentally different skills from solving algorithm puzzles under time pressure.
The emergence of agentic workflows means engineers increasingly direct AI systems rather than writing every line themselves. Success depends on judgment, communication, verification, and technical reasoning—not just syntax recall.
How to Interview for Agentic Work
Instead of asking candidates to pretend AI doesn't exist, hiring managers should evaluate how they use it.
Modern technical interviews can simulate real engineering tasks where candidates collaborate with an AI assistant to solve meaningful problems. This provides insight into abilities that traditional interviews often miss:
- How effectively they prompt and guide AI.
- When they challenge incorrect outputs.
- How they validate generated code.
- Whether they recognize edge cases and potential failures.
- How they make architectural tradeoffs.
- How efficiently they reach high-quality solutions.
These exercises more closely resemble the work engineers perform every day.
Rather than measuring who memorized the most algorithms, they measure who can deliver the best outcomes.
The Future of Technical Hiring
AI isn't replacing software engineers—but it is changing what makes them productive.
The best hiring processes won't ignore AI, nor will they simply ask candidates whether they've used tools like GitHub Copilot or Claude. Instead, they'll assess how candidates collaborate with intelligent systems to solve real engineering problems.
Organizations that modernize their hiring will likely identify stronger candidates while creating interview experiences that better reflect day-to-day work.
As engineering continues to evolve, interviews should evolve alongside it.
If you're looking for a better way to evaluate engineers in the agentic era, Tisuren helps companies run realistic, agentic technical interviews that measure how effectively candidates work with AI agents to solve software engineering problems. Rather than relying on whiteboards or algorithm puzzles alone, businesses gain insight into the skills that increasingly matter in modern engineering teams.
Tisuren is an AI-native technical interview that measures engineering judgment, not AI output. Book a demo →