Rethinking Technical Hiring
for the AI Era
Insights on engineering evaluation, AI-assisted development, and building hiring processes that actually work in 2026.
Latest Posts
The Interview-to-Offer Pipeline: Where Companies Lose Top Engineers
Over half of candidate drop-off happens after the first interview. Here is where engineering pipelines leak top candidates, and how to fix each stage.
Read postarrow_forwardHow to Evaluate Engineers Who Use AI: The Complete Framework
A practical framework for evaluating engineers who use AI: seven steps, the behaviors to watch for, and why process-based scoring beats grading the code.
Read postarrow_forwardWhat Is AI Hiring Intelligence? The Complete Guide to Evaluating Engineers in the AI Era
AI Hiring Intelligence is evidence-based evaluation of how engineers think and work with AI. What the term means, why the old signals broke, and how to build the process.
Read postarrow_forwardInterview Scorecard Templates for AI-Era Hiring
Most scorecard templates still grade syntax and puzzle-solving. Here is what an AI-era interview scorecard should measure, plus a full rubric you can copy.
Read postarrow_forwardData-Driven Hiring: What to Measure and Why
Most hiring dashboards measure how fast and cheap you hire, not how well. Here is what data-driven hiring should actually measure, and why.
Read postarrow_forwardHow AI Changes What Good Code Looks Like
AI made clean, working code cheap to produce. Here is how the definition of good code shifts from the artifact to the system, and how to evaluate it.
Read postarrow_forwardWhy Your $150K Senior Hire Depends on a Gut Feeling
Every CTO I interviewed admitted senior hires come down to gut feeling. Here is why that happened, what it costs, and how to replace it with evidence.
Read postarrow_forwardMulti-Model AI in Technical Assessment: Why It Matters
Single-model AI in a technical interview measures tool familiarity and carries one model's bias. Here is why multi-model matters for both the candidate and the score.
Read postarrow_forwardEval-X vs Codility: Why Syntax Testing Fails in the AI Era
Eval-X vs Codility compared: algorithmic syntax testing plus AI-detection proctoring vs AI-native evaluation that scores how engineers think and work with AI.
Read postarrow_forwardHow to Build a Technical Hiring Process from Scratch in 2026
A step-by-step guide to building a technical hiring process from scratch in 2026: six structured stages, scorecards, and AI-native assessment that still work.
Read postarrow_forwardHow to Reduce Bias in Technical Hiring with AI
AI can amplify hiring bias or reduce it, and the difference is what you point it at. Here is how to use AI to make technical hiring fairer, not just faster.
Read postarrow_forwardEval-X vs CodeSignal: AI-Native Assessment vs Auto-Grading
Eval-X vs CodeSignal compared: auto-grading and AI detection vs AI-native evaluation that scores how engineers actually think and work with AI.
Read postarrow_forwardLive Coding vs Take-Home vs AI-Native: Comparing Assessment Approaches
Live coding, take-home, and AI-native assessments compared on signal, cheating resistance, and experience. Which interview format wins in 2026.
Read postarrow_forwardAI Cheating vs AI Collaboration: Where's the Line?
AI cheating hides the candidate's thinking; AI collaboration shows it. Here is the exact line between the two in technical interviews, and how to tell them apart.
Read postarrow_forwardWhat CTOs Get Wrong About Technical Hiring
I ran 1,000+ technical interviews and scaled an org from 15 to 120. Here are the seven mistakes CTOs make in technical hiring, and how to fix each one.
Read postarrow_forwardThe False Positive Problem in Technical Hiring
A false positive in hiring is a bad hire who aced the interview. Here is why AI has multiplied them in technical hiring, and how to catch them before the offer.
Read postarrow_forwardHow to Assess AI Collaboration Skills in Technical Interviews
A practical 5-step guide to assessing how engineers work with AI in technical interviews. Score the behaviors that predict performance, not the final code.
Read postarrow_forwardStructured vs Unstructured Technical Interviews: What the Data Shows
Structured interviews are roughly twice as predictive of job performance as unstructured ones. Here is what the meta-analytic data shows, and why structure alone is not enough in the AI era.
Read postarrow_forwardMeasuring Engineering Judgment, Not Just Coding Speed
Coding speed was a proxy for engineering ability. AI broke it. Here is what engineering judgment actually is and how to measure it directly in 2026.
Read postarrow_forwardDoes HackerRank Actually Detect Cheating? What's Changed in 2026
HackerRank's proctoring catches some cheating signals and misses others. Here's what its detection layer actually flags in 2026, what it can't see, and why detection is structurally losing to AI.
Read postarrow_forwardThe Real Cost of a Bad Engineering Hire in 2026
A bad senior engineering hire costs $150K-$300K. But the real damage is invisible: technical debt, team erosion, and months of lost velocity. Here's the full breakdown.
Read postarrow_forwardWhy LeetCode Doesn't Work in the AI Era
LeetCode-style interviews test skills that AI makes irrelevant. Here's why algorithm puzzles fail as hiring signals in 2026, what they actually measure, and what to evaluate instead.
Read postarrow_forwardAgentic Assessments Test What Engineers Build. We Evaluate How They Think.
CodeSignal launched agentic coding assessments. Meta is rolling out AI-assisted interviews. The industry agrees AI belongs in the interview. The question is: what do you actually measure once it's there?
Read postarrow_forwardThe AI Interview Arms Race: Why Detection Will Always Lose
38% of technical interviews triggered cheating flags in a recent analysis. The detection approach is losing. Here is why - and what to do instead.
Read postarrow_forwardThe Multi-Dimensional Framework for Evaluating AI-Era Engineers
A single interview score compresses everything you need to know into a number. Here's how to evaluate engineers across 6 dimensions that actually predict on-the-job performance when AI is in the loop.
Read postarrow_forwardWhy Technical Interviews Are Broken in the AI Era
After 1,000+ technical interviews, the signals that used to predict engineering success have stopped working. Here's what changed and what to do about it.
Read postarrow_forwardEval-X vs HackerRank: Detecting Cheating vs. Evaluating Collaboration
HackerRank answers a compliance question. Eval-X answers an evaluation question. A fair, sourced look at the difference, and which one your next senior hire actually needs.
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