In a recent interview that's sparking widespread discussion, Boris Cherny, the creator of Claude Code at Anthropic, offered a candid assessment of how AI agents are poised to reshape the workforce. While his comments echo familiar themes about AI's rapid progress, they stand out for their blunt acknowledgment of the challenges ahead, particularly for roles heavily reliant on computers.
Cherny's insights, shared on podcasts like Lenny's Podcast and Y Combinator's Lightcone, highlight a pivotal shift: AI isn't just augmenting tasks — it's fundamentally altering job structures, potentially rendering titles like "software engineer" obsolete as early as 2026.
The Core of Cherny's Message: AI Agents and Job Transformation
Cherny emphasizes that advancements in AI agents — systems capable of autonomously handling complex tasks across digital tools — will extend beyond coding to "pretty much any kind of work that you can do on a computer." He describes this evolution as "very disruptive" and anticipates it will be "painful for a lot of people," as roles in software engineering, product management, design, and other knowledge-based fields adapt to AI's capabilities.
Drawing from his experience at Anthropic, where Claude Code has boosted team productivity by enabling non-engineers to code and engineers to tackle higher-level problems, Cherny predicts "insane" developments in 2026.
A key term Cherny uses is "computer-based job," which encapsulates roles involving intensive computer use, from coding to data analysis and content creation. He notes that while exceptions exist — like psychotherapy, which relies on human empathy — most office work falls into this category.
As AI agents improve in reliability and versatility, they could handle routine tasks, allowing humans to shift toward oversight, strategy, and creative problem-solving.
Cherny illustrates this with his own team: "On the Claude Code team, everyone codes. Our product manager codes, our engineering manager codes, our designer codes, our finance guy codes."
Reactions and Broader Implications
The interview has ignited conversations across tech communities. On X, users like Aaron Levie, CEO of Box, agree that while tasks automate, new roles emerge at higher abstractions, emphasizing the need for humans to manage systems and address bottlenecks.
Entrepreneur Zach Giglio highlights the shift from entry-level tasks to elevated skills, urging leaders to invest in training rather than replacement. Developer Haider echoes Cherny's view that coding is "practically solved," predicting a move toward builders or product managers who guide AI rather than write every line of code.
These reactions underscore a consensus: the pain comes not from AI itself but from unpreparedness. Cherny likens the transition to historical shifts like the printing press, which disrupted scribes but expanded knowledge dissemination. However, the speed of AI's advancement—fueled by models like Claude's latest Opus 4.6 — amplifies the urgency.
Coping Strategies in the AI Era
To navigate this, Cherny advises workers to embrace AI tools actively: "Don't be scared of them." Experimenting with agents like Claude Code can reveal their strengths and limitations, turning potential threats into allies.
A practical strategy emerges from his insights: amplify the non-computer-based elements of your role — those human-centric aspects like relationship-building, ethical decision-making, and innovative thinking that AI can't replicate yet. For instance, software engineers might evolve into "builders" who define problems and review AI outputs, focusing on user needs over syntax.
This approach aligns with broader advice from experts. As Mohammad Abdullah notes on X, the competitive edge will lie in clear thinking and problem definition, not just coding speed. Companies should prioritize upskilling, fostering cultures where AI elevates rather than eliminates roles.
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Looking Ahead: A Balanced Perspective
While Cherny's warnings may sound alarmist, they serve as a call to action in an era of unprecedented technological acceleration. By 2026, as AI agents become ubiquitous, the workforce could see profound changes — but also opportunities for more fulfilling work. The key is adaptation: understanding AI's role in computer-based jobs and bolstering irreplaceable human skills. As discussions continue, one thing is clear — ignoring this wave isn't an option.
