Karat blog

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 […]

Money20/20 Europe Recap (2026): Can you assess how engineers use AI credits? Agentic excitement, governance and more.

[This article was originally published in 2020, but has been updated to reflect the evolution of interviewing and what Karat technical interviews measure in the human + AI era.] Going back to the early days of Karat, reviewing candidate feedback has been one of the most important ways we gauge the consistency, accuracy, and fairness […]

What building and running the first human-led, AI-enabled technical interview system actually looks like When we launched Karat NextGen late last year, we had a clear thesis: the way companies evaluate engineering talent hadn’t kept pace with how software is actually built. AI tools had changed the job, but interviews were still designed for a […]