State of Tech Hiring 2026

While 54% of developers depend on AI for productivity, technical hiring assessments haven’t declined – they’ve exploded. CoderPad’s platform data reveals:

• 48% growth in global technical assessments (since mid-2023)
• 90% growth in U.S. technical hiring (in the same time period)
• Large enterprises (with 10K+ employees) leading growth

The companies with the most AI resources and most sophisticated tools are hiring MORE engineers – not fewer. The question shifts from “Will we need developers?” to “Can we hire them fast enough?”

Our data reveals that AI isn’t killing developer jobs; it is accelerating the need for technical talent who can leverage it effectively.

We asked developers which skills are most important today versus what they think they’ll be most important in three years. In our results, a clear pattern revealed that debugging and fine-tuning and systems design will grow in importance, and writing new code will decline.

How will this shape how we evaluate the skills and competencies of developers? The shift from “can you code?” to “can you architect, debug, and optimize?” fundamentally changes what we should assess in technical hiring. Companies still relying on algorithm-heavy, write-from-scratch coding tests are measuring the skills from yesterday, not tomorrow.

The issue of agent-generated solutions is driving significant changes in how companies evaluate technical talent.

Here’s what’s changing:

• Companies are shifting away from algorithmic puzzles toward multi-file, real-world scenarios that mirror actual engineering work
• AI-enabled assessments are growing – candidates can use AI tools, but evaluators see their prompt history and decision-making processes
• The focus on realistic coding projects test judgment, not just syntax

Over the past two years, the conversations around AI in technical assessments have evolved from “Should we allow AI in interviews” to “How do we assess AI-augmented engineering skills?”

One of the most critical questions in technical hiring is also the most challenging: which assessments actually predict on-the-job success? Our data reveals significant alignment between developers and recruiters on what works.

Of our recruiters surveyed, 69% use the resume review to assess technical talent, but only 16% think it predicts performance. While resumes may serve as a necessary filter at the start of the candidate’s journey, survey respondents agree that they’re not the best signal of job-relevant skills.

We asked recruiters about the types of technical assessments they’re conducting, and what they include.

Despite industry-wide criticism of algorithmic interviews as poor predictors of job performance, 43% of teams are still relying on these results. Meanwhile, system design and real-world scenarios are gaining ground but haven’t yet displaced algorithms as the dominant assessment format.

38% of the recruiters we surveyed are adopting real-world scenario simulations, which signals some progress toward assessing what matters. These exercises typically include:

• Multi-file codebases (not single-function puzzles)
• Realistic debugging challenges
• Working with existing code (not greenfield only)
• Integration with actual frameworks and tools
• Problems that mirror day-to-day work

When combined with the 30% using pair-programming and 38% testing system design, there’s a meaningful shift toward assessments that more accurately reflect actual engineering work.

AI has become foundational, and leading companies have moved beyond asking whether candidates can use AI. Instead, they’re measuring how effectively candidates can use it. This requires a shared framework for defining AI proficiency.

For example, consider these four dimensions of AI proficiency:

1. Prompting Skill: Can they guide AI to produce high-quality, relevant results?
2. Workflow Integration: Do they use AI as a smart assistant in their daily tasks to improve efficiencies?
3. Judgment & Verification: Can they evaluate, edit, and fact-check AI output?
4. Creativity & Adaptability: Do they find new, practical ways to apply AI tools?

Companies like MNTN, Meta, and Yahoo are now explicitly testing for these dimensions in their hiring processes, allowing candidates to use AI tools during their technical assessments so they can observe actual AI proficiency.

Forward-thinking companies focused on hiring for AI proficiency are seeing real gains in their time to productivity and overall performance:

• MNTN: Engineers hired through AI-enabled interviews are making meaningful contributions in 1-2 days, rather than weeks
• Meta: Engineers who have proficiency with AI tools ramp up “dramatically faster” and become productive in days, rather than months
• Yahoo!: Hires who are proficient in AI navigate large codebases more quickly, accelerating the time-to-ship for new features

Hiring for AI proficiency isn’t just about filling seats – it’s correlated with faster ramp times and earlier impact. Companies who can identify, close, and onboard the right talent can gain a competitive advantage.

Evaluating soft skills continues to be a pain point in technical assessments.

We asked recruiters: what is your main challenge when evaluating soft skill?

Recruiters agree that measuring intangible qualities is difficult to assess and measure in an interview.

Developers who responded to our survey were mostly content in their current roles, supporting the theory that the “Great Stay” will continue into this year.

For the past 5 years, our surveys have reflected declines in the number of developers considering leaving their current positions. This year’s number – 39% represents a five-year low.

Developers who are exploring new opportunities are prioritizing career advancement and compensation. However, remote work is also playing a major role.

How does this compare to our results from last year?

• Career advancement remains #1 or #2 (was 44% in 2025, now 39%)
• Compensation was consistently top factor
• Remote work flexibility emerged as major post-pandemic driver

Understanding key retention factors helps organizations keep their best talent in a competitive job market. Developers cite quality of life, culture, stability, and security as their top three reasons for staying with their current companies.

Interestingly, culture dominates retention metrics among our survey respondents. In fact, the top two factors were consistent with the results we saw in 2025, at 43% and 37% respectively. Job stability entered the top three for 2026, perhaps due to the volatility of the job market.

You’ve seen the headlines about tech companies reducing entry-level hiring. However, the full picture is more complex.

Here’s what our data shows:

• 28% of hiring leaders cite early-career pipeline building as a priority – it’s a top 3 goal
• Technical assessments for junior roles remain active
• Multiple organizations are expanding – not cutting – new grad programs

Overall, the market is shifting, not shrinking.

According to the World Economic Forum’s Future of Jobs 2025 report:

• AI will create 11M new jobs, while displacing 9M jobs (2025-2030)
• AI Engineer is the fastest-growing job across 15 countries, including the U.S.
• More than 20% of today’s U.S. workforce holds job titles that didn’t exist in 2000 – many are tech-adjacent roles

The reality is that entry-level roles now require different skills, and companies now seek grads who combine programming with AI proficiency.

In 2026, developers are focused on expanding technical capabilities, particularly in these areas:

Machine learning / AI is the clear priority for developers for 2026. While 37% of developers reported that they already learned AI skills in the past 12 months, there’s still room to grow.

This isn’t random skills acquisition – it’s the market speaking. Companies are actively hiring for AI/ML roles (35%), system design is rising in importance, and early-career developers are building the foundation (programming languages), while acquiring AI skills that will define the next few years of software engineering.

Budget increases translate into real hiring activity. This investment is also evident through CoderPad platform data. We’ve seen:

• 43% growth in average usage per customer since 2023
• 90% increase in usage in the U.S.
• Enterprise companies with 10K+ employees leading growth

Companies aren’t just saying they’ll hire more engineers – they’re actively assessing more candidates. Additionally, large companies are investing heavily in technical infrastructure.

The growth in assessments suggests that companies are being even more selective, not less. They want to hire the right technical talent for the AI era.

Backend and full-stack engineers remain the most sought-after roles, with AI-oriented positions seeing significant demand.

However, recruiters and hiring teams acknowledge the challenges in hiring for 2026. The toughest roles to fill in 2026 are fairly universal, with AI/ML specialists and full-stack developers taking the top spots.

AI/ML roles were the most challenging to fill in 2025 (with 22% of recruiters weighing in on this role). The talent shortage for these roles may be worsening, not improving.

Despite improvements in AI adoption and tooling, recruiters report that core challenges persist.

How does this compare to 2025?

• 2025: Finding qualified candidates (48%), Identifying potential (28%), Evaluating soft skills (26%)
• 2026: Finding qualified remains #1 (29%), but volume management (25%) and closing (18%) rise in prominence

While finding qualified candidates remains the top challenge this year, volume management has emerged as a close second. This is likely due to the explosion of AI-facilitated job applications, which has spiked volume across organizations.

Recruiters also reported significant progress in AI knowledge and training among their teams.

The AI training gap has improved significantly year over year (22%). However, this lags the broader market. According to the BCG AT at Work Report 2025, 72% of professionals are regular users of AI at work, but just 36% feel they are properly trained. That gap between usage and training signals a challenge and opportunity. Professionals are learning on the job, but companies that provide structured enablement could more effectively attract and retain talent.

Two-thirds of recruiters are using AI tools every day – they’ve become embedded in daily workflows.

The recruiting tech stack is multi-faceted, with AI playing a role in multiple stages. The ATS/CRM is central to the function, along with technical assessments. Beyond those, teams are building their stacks based on specific objectives and hiring goals.