Karat blog

90% of U.S. technology leaders are using AI to increase output without reducing engineering headcount, while 75% globally say a strong engineer is worth at least 3x their compensation SEATTLE, October 8, 2026 – AI is increasing the capacity of engineering organizations, but technology leaders are largely using those productivity gains to build more rather […]

Enterprise leaders can scale technical interviews by standardizing evaluation criteria, modernizing assessments for the AI era, expanding interview availability, and adding trained interviewer capacity. This not only allows enterprises to conduct more interviews, but it also creates a consistent, high-quality hiring signal across teams, roles, regions, and talent sources without stretching engineers thin. Scaling technical […]

To assess engineering skills in financial services, organizations should define the competencies needed for each role, develop interview content that measures both foundational engineering and AI skills, evaluate candidates in realistic environments, and standardize their interviews and scoring. By taking these steps, you’ll be able to reliably identify software engineers who can build secure products […]

Canadian banks should evaluate AI-ready contract engineers across four areas: engineering fundamentals, AI fluency, responsible AI judgment, and role-specific AI engineering skills. The strongest candidates can use AI productively, validate its output, protect sensitive data, identify security and model risks, and make sound decisions within a regulated banking environment. Banks should assess these capabilities through […]

In every issue of The Talent Signal newsletter, Karat Co-Founder and President Jeffrey Spector explores the trends reshaping technical hiring. From changing skill requirements to new hiring challenges, the series helps engineering leaders understand how the broader landscape is changing software engineering and what it means for building high-performing teams. One of the biggest themes […]

AI has impacted technical assessment formats in different ways. Code tests and take-home assessments now provide less reliable hiring signals. Because candidates can use AI to generate complete solutions, these asynchronous and output-based assessments offer less insight into a candidate’s true capabilities. Live interviews with a human hold up better, but they can’t measure how […]

Not long ago, hiring software engineers was largely about evaluating whether someone could write quality code on their own. Today, that assumption no longer reflects how engineering work actually gets done. Generative AI has become part of the modern software development workflow. Engineers use AI to accelerate implementation, explore unfamiliar codebases, generate tests, debug issues, […]

Financial services engineering leaders are tasked with modernizing legacy systems, shipping new digital products, and navigating an AI revolution – all while competing with big tech and fast-growing startups for increasingly scarce engineering talent. To better understand where FinServ engineering leaders are feeling the most pressure, Karat analyzed data from 303 CTOs, CIOs, VPs of […]

Google: What are Karat interview questions? Chances are, if you’ve taken a Karat interview, you’ve run a search like the example above. In fact, most candidates interviewing at any company will have scoured Leetcode, Reddit, Blind, Glassdoor, and other sites for clues on what questions they might be asked throughout the technical hiring process. At […]