What are the four archetypes of tech workers identified in the survey?

The four archetypes are: Energized (41%, fun, exploration, new powers), Conflicted (35%, enjoying building but uncertain about career future), Disoriented (12%, role shifting, unclear path), and Resentful (12%, pressured, checked out, forced to use AI).

Is burnout increasing in the tech industry?

Yes, significant burnout (higher than moderate) has increased from 44.7% in 2025 to 54.7% in 2026. At the same time, optimism about career futures has fallen from 54.8% to 48.7%.

Are tech workers worried about layoffs due to AI?

72% of the surveyed sample are worried to some extent about being laid off, with 41.2% feeling moderately worried. However, the fear of losing jobs to AI ranks second to last among top concerns, overshadowed by the expectation to do more for the same pay and unsustainable work pace.

How does AI affect productivity and quality of work in tech?

97.2% of people believe AI makes them better at their job. However, when probed deeper, many report doing 'much more, faster, but not better,' and express concern about 'cognitive rot,' where reliance on AI diminishes their thinking and judgment.

What is 'smiling exhaustion' in the context of tech workers?

Coined by Nikil Singal, 'smiling exhaustion' describes tech workers feeling reborn, shipping, and building incredible things with AI, experiencing an exciting time, but simultaneously facing a brutal, relentless pace with no off switch, leading to exhaustion they smile through.

Which tech roles are feeling the most negative impact from AI?

Designers and researchers consistently show the most negative sentiment. They lead in feeling destabilized or diminished, reporting higher levels of tiredness, overwhelm, anxiety, and are least likely to recommend their role to others entering the industry.

Who are the happiest people in tech right now?

Founders and employees at smaller companies are consistently the happiest. Founders show 71% optimism, lowest burnout, lowest layoff worry, and highest AI excitement, though even they are not highly likely to recommend their role.

What role does a manager play in employee well-being in tech?

Manager effectiveness is a massive factor: highly effective managers correlate with 65% higher job enjoyment and dramatically lower burnout. However, only about 25% of managers are rated highly effective, highlighting a significant issue in the industry.

What is AI guilt, and which roles experience it most?

AI guilt is a phenomenon where early-career professionals feel that leveraging AI is akin to 'cheating.' This guilt tends to decrease with seniority. Product marketing and data analytics roles experience the most AI guilt.

What are key recommendations for tech employees navigating the AI era?

Employees should focus on going deep on specific AI uses rather than trying to be a generalist, watch out for overwork for the same pay, prioritize a strong relationship with their manager, consider smaller companies or founding their own, and seek mentorship.

Key Moments

Why the tech workforce is quietly splitting in two | Annual AI sentiment survey (Noam Segal)

Lenny's Podcast

People & Blogs5 min read97 min video

Jul 12, 2026|652 views|29|8

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Key Moments

TL;DR

Half of tech workers feel amplified by AI, while the other half feel destabilized or diminished, leading to a stark split in the tech workforce and a surge in burnout.

Key Insights

Burnout has increased significantly, with 54.7% of tech workers experiencing significant burnout in 2026, up from 44.7% in 2025.

50% of tech workers feel amplified by AI, while 27% feel their role is being redefined, 14% feel destabilized, and 5% feel diminished.

Only 3% of people reported that AI has not shifted their professional identity.

Across all roles, founders reported the highest optimism (71%) and enjoyment, along with the lowest burnout and layoff worry.

Despite AI making workers feel 'better' at their jobs (97.2%), this often translates to doing more faster, not better quality, and nearly half admitted their 'brain is rotting' due to cognitive decline.

The expectation to do more for the same pay, coupled with an unsustainable pace of work and technological change, is the dominant fear, ranking higher than job loss to AI.

The tech workforce is split in two by AI

The second annual Tech Worker Sentiment Survey reveals a stark division within the tech industry, largely driven by AI. Half of the workforce feels amplified and energized by AI, capable of doing more and better work. However, the other half feels destabilized, diminished, or uncertain about their roles as AI evolves. This bifurcation profoundly impacts career optimism, burnout, and job satisfaction, more so than any other job characteristic like role, company size, or level. The data indicates AI's outsized impact, affecting identity and job sentiment three times more than previous major factors like manager effectiveness or founder status.

AI's impact on professional identity

AI has demonstrably shifted how tech workers perceive themselves professionally, with only 3% reporting no change to their identity. The largest group, 50%, feels "amplified" by AI, experiencing positive emotions and a sense of enhanced capability. Conversely, the remaining 50% are split into three groups: 27% feel their roles are being "redefined" with unclear consequences, 14% feel "destabilized" with high anxiety, and 5% feel "diminished," believing AI has taken something irreplaceable away. This division strongly correlates with overall job sentiment, leading to a decline in career optimism and a rise in burnout and layoff worries as one moves from amplified to diminished.

Burnout surges as optimism declines

Despite the promise of increased efficiency, burnout in the tech industry has surged. Significant burnout, defined as higher than moderate levels, rose from 44.7% in 2025 to 54.7% in 2026. Simultaneously, optimism about career futures has fallen from 54.8% to 48.7% in the same period. This counterintuitive trend suggests that increased output and faster work, while potentially fun, are not reducing workload or leading to greater well-being. Instead, the pressure to do more with the same pay, coupled with the rapid pace of technological change and the constant need to learn new AI tools, is contributing to exhaustion and diminishing positive outlooks.

The surprising dominance of 'doing more for less'

The survey identified a primary fear among tech workers: not being replaced by AI, but the expectation to "do more for the same pay." This, along with an "unsustainable pace" of both work and technological evolution, emerged as the top concerns. Workers are feeling squeezed, burdened by increased expectations without commensurate compensation or relief. The rapid advancements in AI, while unlocking new capabilities, are being channeled into increased output demands rather than improved work-life balance or reduced pressure. This constant drive for higher velocity and continuous learning creates an "evil downward spiral," leaving employees feeling overworked and incapable of meaningful progress.

'Cognitive rot' and the quality paradox of AI

While 97.2% of workers believe AI makes them better at their jobs, this "better" often means faster, not higher quality. AI has lowered the floor for output, enabling workers to produce more PRs, documents, or prototypes. However, a concerning effect is "cognitive rot," where reliance on AI leads to a decline in critical thinking and judgment. Workers report their "brain is rotting" and their work feels worse, accepting AI's initial output without deeper scrutiny. This phenomenon, coupled with skill atrophy fears, highlights a critical challenge: AI's benefits are yielding increased productivity at the cost of individual mental sharpness and work quality.

The stark reality of recommending tech careers

Alarmingly, the survey found that no group, including founders, would actively recommend their role in tech to others. Net Promoter Scores (NPS) for recommending one's role were negative across product, engineering, design, research, and sales. Designers and researchers are the least likely to recommend their fields, reporting the highest levels of destabilization and diminution from AI. This suggests that while workers may enjoy their current tasks, their outlook on the future and the sustainability of their roles is deeply pessimistic, indicating a potential crisis in attracting future talent to the tech industry. This sentiment is more pronounced for junior roles, where the 'rungs of the ladder' are perceived as disappearing.

Founders and small companies remain the 'happiest'

Founders and employees in smaller companies consistently report higher job satisfaction, optimism, and lower burnout compared to those in larger enterprises. Founders, despite facing immense challenges, exhibit the highest optimism (71%) and excitement about AI. However, even founders are not universally recommending their path. Conversely, as company size increases, so do burnout rates, layoff worries, and a diminished likelihood to recommend the role. This suggests that the autonomy and agency afforded by smaller organizations or founder roles may offer a buffer against the broader anxieties pervading the tech sector.

The enduring impact of effective management

Manager effectiveness remains a critical factor influencing employee well-being, with highly effective managers correlating to significantly higher job enjoyment (65% increase) and drastically lower burnout. Despite this, only about 25% of tech workers rate their managers as highly effective, while 36% consider them ineffective. This disconnect is exacerbated by trends like the "great flattening" and the increased span of control for managers, who are crucial in protecting employees from overwhelming workloads. The survey also noted that managers in data analytics and design are among the worst-rated, potentially reflecting their own struggles within the current tech climate and impacting their teams negatively.

Mentioned in This Episode

●Software & Apps

●Companies

●Organizations

●Concepts

●People Referenced

Navigating the AI Era in Tech: Employee & Leader Actions

Practical takeaways from this episode

Do This

For employees: Go deep on specific tasks and jobs that AI is useful for, instead of trying to be a generalist.

For employees: Protect and invest in your relationship with your manager, as their effectiveness significantly impacts your well-being.

For employees: Consider working for a smaller company or starting your own venture if seeking more agency and less burnout.

For employees: Seek out strong mentorship, especially if early in your career, to navigate disappearing opportunities and develop skills.

For employees: Leverage AI actively and without guilt, as it's a powerful tool that will only continue to improve.

For leaders: Invest heavily in manager training and development; it's a key lever for retention and employee well-being.

For leaders: Manage the 'squeeze' of increased expectations and unsustainable pace to prevent employee burnout.

For leaders: Create clear advancement paths for entry-level talent to avoid 'cognitive rot' and foster AI-native skills.

For leaders: Pay attention to the negative sentiment in roles like design and research, as these functions are crucial for product quality and innovation.

For leaders: Recognize that AI impacts people differently, lifting some while destabilizing others, and tailor support accordingly.

Avoid This

For employees: Don't spread yourself too thin trying to be an 'AI generalist' doing everything; focus on depth.

For employees: Don't ignore the signs of being 'squeezed' (overwork for the same pay); address it with your manager.

For employees: Don't let your cognitive abilities atrophy by blindly accepting AI outputs; apply judgment and critical thinking.

For employees: Don't shy away from using AI due to 'guilt'; it's a tool to be leveraged for professional growth.

For leaders: Don't neglect manager development, as ineffective managers contribute significantly to burnout and low morale.

For leaders: Don't impose unsustainable work paces without adjusting expectations or resources for employees.

For leaders: Don't allow the 'bottom rung of the ladder to rot' by ignoring the needs and career paths of early-career employees.

For leaders: Don't assume all employees experience AI's impact uniformly; recognize and address the varied emotional responses.

Common Questions

The survey found a significant bifurcation in the tech workforce, with half of employees feeling amplified and excited by AI, while the other half feel destabilized, diminished, or ambivalent about their professional identities and careers. This split significantly impacts other measures like optimism and burnout.

Topics

Mental Health & Psychology AI & Machine Learning Job Satisfaction Career & Skills Tech Industry Trends Cognitive Workload AI Sentiment Employee Burnout Career Optimism Layoff Anxiety Manager Effectiveness

Mentioned in this video

Companies

Airbnb

Tech company where Lenny and Noam worked together a decade ago.

OpenAI

Company mentioned as a user of Work OS for enterprise features.

Anthropic

Company mentioned as a user of Work OS for enterprise features.

Vercel

Company mentioned as a user of Work OS for enterprise features.

Intercom

One of the companies where Noam Segal served as a research leader.

Twitter

One of the companies where Noam Segal served as a research leader.

Wealthfront

One of the companies where Noam Segal served as a research leader.

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Why the tech workforce is quietly splitting in two | Annual AI sentiment survey (Noam Segal)

Want to know something specific about what's covered?

Key Insights

The tech workforce is split in two by AI

AI's impact on professional identity

Burnout surges as optimism declines

The surprising dominance of 'doing more for less'

'Cognitive rot' and the quality paradox of AI

The stark reality of recommending tech careers

Founders and small companies remain the 'happiest'

The enduring impact of effective management

Mentioned in This Episode

Navigating the AI Era in Tech: Employee & Leader Actions

Do This

Avoid This

Common Questions

Topics

Mentioned in this video

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