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

Noam Segal and Lenny Rachitsky's second annual Tech Worker Sentiment Survey reveals a striking bifurcation in the tech workforce: 50% feel energized and amplified by AI, while the other half feels redefined, destabilized, or diminished. Burnout is surging (up 11 points in a year) and optimism is declining, even as 97% believe AI makes them 'better' (often meaning faster, not higher quality, leading to 'cognitive rot'). The #1 fear isn't job loss to AI, but being squeezed to do more for the same pay. Nobody would recommend their job to someone entering the industry today, with designers and researchers being the most negative. Managers are identified as the single biggest lever for employee well-being, yet most are rated ineffective. The industry is described as 'chaotic,' with advice for employees to go deep on AI, manage the 'squeeze,' and invest in manager relationships, while leaders are urged to invest in managers, manage expectations, and support early talent and struggling roles.

July 12, 2026 5 min read

Why the tech workforce is quietly splitting in two | Annual AI sentiment survey (Noam Segal) — source: https://www.youtube.com/watch?v=_cmpIveXnvE

Noam Segal and Lenny Rachitsky conducted their second annual Tech Worker Sentiment Survey, a quantitative study of 6,000 tech professionals across various roles. The results reveal a tech workforce profoundly impacted by AI, experiencing unprecedented levels of burnout and uncertainty, alongside pockets of intense excitement.

The Bifurcation of the Tech Workforce

The core finding is that AI has split the tech workforce almost exactly in half regarding professional identity. Only 3% reported no shift in their identity due to AI. The remaining are divided:

50% Amplified: Feel capable of doing more and better, energized, and excited.
27% Redefined: Acknowledge their role is fundamentally changing but lack clarity or specific positive/negative emotions.
14% Destabilized: Experience ground-shaking uncertainty, high anxiety, and pessimistic views.
5% Diminished: Feel AI has taken something away from their role, likely permanently. This impact of AI on identity is three times greater than factors like manager effectiveness or founder happiness.

Four Emotional Archetypes

Based on a deeper analysis of reported emotions, four archetypes emerged:

Energized (41%): View product development as fun again, feel like builders with new powers, and are very excited about their careers.
Conflicted (35%): Experience both unprecedented fun in building and the highest uncertainty in their careers, questioning where things are headed.
Disoriented (12%): Feel their role is constantly shifting, akin to “farmers on the cusp of the industrial revolution” with no clear path.
Resentful (12%): Feel pressured, checked out, and forced to use AI, lamenting job losses even with AI adoption.

Surging Burnout and Declining Optimism

Burnout is a critical concern, increasing significantly:

Significant burnout: Jumped from 44.7% in 2025 to 54.7% in 2026.
Optimism: Declined from 54.8% in 2025 to 48.7% in 2026. This suggests that while tech workers are shipping faster than ever, the relentless pace and increased workload are leading to greater exhaustion. A “glimmer of hope” is that enjoyment of work remains high for many, as AI enables them to manifest new ideas and explore different aspects of their professional identity.

Layoff Worries and Career Recommendations

Layoff Worry: 72% are worried about being laid off, with 41.2% moderately worried, contributing to ambivalence.
Career Recommendation NPS: The “Net Promoter Score” for recommending one’s role to someone entering the industry is shockingly negative across the board. Not even founders, typically the happiest group, would recommend their roles. Designers and researchers are the least likely to recommend their careers, struggling with feeling diminished and anxious. This is attributed to the “ladder metaphor,” where AI is seen as pulling rungs from beneath junior workers.

AI: Faster, Not Better, and the #1 Fear

While 97.2% believe AI makes them “better” at their job, this often translates to “doing more faster, but not better quality.” A concerning effect is “cognitive rot,” where over-reliance on AI leads to a deterioration of critical thinking and judgment. The #1 fear in tech is not job loss to AI (which ranks second to last), but the expectation to do more for the same pay and an unsustainable pace of work and technological change. This contributes to “smiling exhaustion” – feeling excited about AI’s capabilities but brutalized by the relentless tempo.

The Emotional Landscape and Role-Specific Impacts

The overall emotional landscape is ambivalent, with top emotions being curiosity and excitement, but also significant feelings of overwhelm, conflict, tiredness, unease, and anxiety. The sentiment analysis of descriptions of the tech industry showed an even split: 37% positive, 37% negative, 26% neutral.

Most Negative: Designers and researchers consistently report the highest levels of destabilization, diminished feelings, anxiety, and layoff worry. They are also the least likely to recommend their role. The industry is encouraged to invest in these roles, emphasizing the need for taste, craft, and quality that AI currently lacks.
Happiest: Founders and individuals in smaller companies (1-10 people) show the highest optimism and lowest burnout and layoff worry. Burnout consistently increases linearly with company size.

Managers: The Single Biggest Lever

Manager effectiveness is a massive predictor of employee well-being:

Impact: Highly effective managers lead to approximately 65% higher job enjoyment and dramatically lower burnout.
The Problem: Only 25% of the sample rated their managers as highly effective, while 36% rated them ineffective. Managers are crucial in protecting employees from the “squeeze” and managing workload expectations.
Worst-Rated Managers: Cluster in data analytics and design, possibly due to their own struggles within those roles.

Advice for Employees and Leaders

For Employees:

Go Deep, Not Broad: Focus on mastering specific AI applications relevant to your core tasks, rather than trying to generalize everything.
Watch the Squeeze: Be aware of increased scope without proportional compensation; communicate with managers to recalibrate work and expectations.
Invest in Your Manager Relationship: Strong communication and managing up can significantly improve well-being.
Consider Smaller Companies/Founding: These environments generally correlate with higher job satisfaction and lower burnout.
Seek Mentorship: Especially for early-career individuals, strong mentorship is vital for navigating a shifting landscape.

For Leaders:

Invest in Managers: Provide training and support, as effective managers are critical for retention, enjoyment, and mitigating burnout.
Manage the Squeeze: Set sustainable expectations, balancing productivity goals with employee well-being.
Support Early-Career Talent: Ensure entry-level paths exist and that junior employees, often AI-native, have opportunities to advance.
Pay Attention to Struggling Roles: Provide targeted support and investment for functions like design and research.
Acknowledge Varied AI Impacts: Recognize that AI affects individuals differently, fostering empathy and tailored support.

Closing Thought: The tech industry is experiencing an unprecedented shift. While the technology is powerful, the focus must remain on the people navigating these changes, understanding their diverse emotional experiences, and fostering environments where they can thrive.