The State of Technical Hiring in 2026
Technical interviewing has been in a state of contested transition for several years. The dominant model, LeetCode-style algorithmic problems administered in a timed, high-pressure live environment, has been criticized by practitioners and candidates alike for most of the past decade. And yet it has persisted at many organizations because it provides a consistent, scalable signal and because the largest companies in the industry have used it successfully at enormous volume.
What has changed in the past two to three years is that the criticism has sharpened into concrete alternatives, the evidence base has grown, and a significant number of organizations have moved to different approaches.
What Is Wrong With Algorithmic Screening
The core critique of LeetCode-style interviews is not that algorithm knowledge is irrelevant. It is that the format selects heavily for a narrow type of preparation at the expense of signal about actual job performance. Success on algorithmic screens is highly correlated with whether a candidate has spent time specifically drilling those problems. An engineer who has been working productively at a company for three years, solving real engineering problems, but who has not drilled LeetCode recently will often perform worse than a recent graduate who has spent six weeks on it. This inverts the signal.
Most engineering roles also do not require the ability to reverse a binary tree on demand. They require the ability to read existing code, write maintainable code, debug problems, make architectural decisions, and collaborate with other engineers. Algorithmic screens assess almost none of these capabilities directly.
The Take-Home vs. Live Coding Debate
Take-home assessments allow candidates to work in their own environment, without time pressure and without an observer. This reduces anxiety and allows candidates who are not natural performers under observation to show their actual work. The costs are also real: they require significant time investment from candidates, and candidates have started declining to complete substantial take-homes at companies where they feel the investment is disproportionate to the likelihood of moving forward.
Live coding exercises allow interviewers to observe how a candidate thinks, asks clarifying questions, handles ambiguity, and debugs problems in real time. The practical trend: many companies are moving toward a blended model. A shorter take-home that establishes a technical baseline, followed by a live session that discusses the take-home and adds an interactive element.
The Rise of Work Sample Assessments
Work sample assessments are structured tasks that replicate the actual work the role involves. For an engineering role that primarily involves debugging and extending existing codebases, the assessment involves doing exactly that. Work sample validity is consistently higher than algorithmic screening validity in predicting job performance. Companies that have built strong work sample assessment libraries report better candidate experience (candidates prefer tasks that feel relevant) and better signal for underrepresented candidates who may not have optimized for traditional interview formats.
AI-Assisted Assessments
AI tools have become a structural fact of software engineering work. Some companies allow and encourage AI tool use in assessments, reflecting actual working conditions. The evaluation then focuses on how the candidate uses AI: do they verify the output? Do they understand what it produces? Can they prompt effectively for a complex task? The direction the industry is moving is toward AI-permitted or AI-integrated assessments, because that reflects how work actually gets done.
What Companies Are Actually Moving Toward
Observable patterns: fewer pure algorithmic screens at early stages; shorter take-homes (two to four hours maximum) often paired with a discussion session; live coding exercises using the company's actual tech stack focused on debugging and extension rather than construction from scratch; system design interviews retained for senior roles but using real systems as prompts; and explicit accommodation processes for candidates who need adjusted interview formats.