An Anthropic engineer says AI agents that can operate computers are advancing quickly and could disrupt nearly every internet-based job in the U.S., with software engineering roles potentially changing as early as 2026.

A senior engineer at Anthropic says a new class of artificial intelligence systems capable of operating computers like humans is developing fast enough to reshape nearly every internet-based job in the United States.

Boris Cherny, creator of Claude Code at Anthropic, made the remarks during an appearance on Lenny’s Podcast, hosted by Lenny Rachitsky. He argued that AI systems that can take direct action across workplace tools — rather than merely generate text — are improving at a pace that could significantly alter responsibilities for software engineers, product managers, designers and other knowledge workers.

“It’s going to expand to pretty much any kind of work that you can do on a computer,” Cherny said. “In the meantime, it’s going to be very disruptive. It’s going to be painful for a lot of people.”

Anthropic is widely known for its Claude chatbot, but Claude Code represents a strategic pivot toward what developers call “agentic AI.” Built on the company’s Claude models, Claude Code is designed as a coding agent capable of running terminal commands, editing files, navigating repositories, analyzing documents and executing multi-step tasks across applications.

The company released an updated version of its model suite, Opus 4.6, in early February, further enhancing Claude Code’s capabilities.

Unlike traditional chatbots that respond to prompts with text or images, AI agents can interact with digital systems directly. They can open software, manipulate files, generate reports, message collaborators, and deploy code — effectively functioning as a junior digital operator inside enterprise workflows.

Anthropic has said Claude Code has not yet reached the skill level of an experienced human engineer. However, Cherny described it as a breakthrough in accessibility, bringing agent-based AI into practical use for a broader audience.

“It’s the thing that I think brings agentic AI to people that haven’t really used it before,” he said. “People are starting to just get a sense of it for the first time.”

Productivity Gains and Role Redefinition

Cherny said his own team has already integrated AI tools deeply into its workflow and that productivity per engineer has increased sharply since Claude Code’s launch. While Anthropic has commercial incentives to promote its tools — the company sells access to enterprise customers — similar productivity claims have surfaced across the technology sector.

The core shift is from AI as a passive assistant to AI as an active executor. In software development, this could reduce the need for engineers to manually write and refactor large volumes of code. Instead, engineers may move toward defining architecture, validating outputs, designing systems, and supervising AI-generated work.

Cherny previously suggested on Y Combinator’s “Lightcone” podcast that the traditional job title “software engineer” could begin to “go away” in 2026. The implication is not necessarily that programming will vanish, but that its nature will change. Coding may become more about intent specification and system oversight than syntax-level craftsmanship.

The impact extends beyond engineering. Product managers could use agents to analyze user data and generate feature roadmaps. Designers might deploy AI to produce prototypes and conduct automated usability testing. Operations teams could rely on agents to reconcile data, generate compliance reports, and manage routine workflows.

If agents can navigate productivity suites, code repositories, customer support dashboards, and analytics platforms, the automation envelope expands across most internet-connected professions.

Tomorrow is Not Certain

The broader economic consequences remain uncertain. Cherny acknowledged that society has yet to determine how to manage the transition.

“As a society, this is a conversation we have to figure out together,” he said. “Anyone can just build software anytime.”

The prospect that “anyone” could generate functional software products through natural language prompts challenges long-standing labor market structures. Barriers to entry in software development may fall, enabling more entrepreneurs and small teams to launch products. At the same time, companies may reduce headcount if AI systems absorb a growing share of routine tasks.

Historically, automation has displaced certain roles while creating new categories of work. The difference with agentic AI is that it targets cognitive, digital, and creative tasks traditionally associated with white-collar employment. That could compress mid-level roles while increasing demand for high-level oversight, AI system governance, and interdisciplinary coordination.

Regulatory frameworks may also come under scrutiny. Enterprises deploying autonomous agents will need safeguards around data privacy, cybersecurity, audit trails, and accountability. Questions about liability — particularly if an AI agent executes flawed instructions or introduces security vulnerabilities — remain unresolved.

Technology firms are likely to adopt agentic systems rapidly to maintain efficiency and competitive advantage. Early adopters may see cost savings and faster product iteration cycles, pushing rivals to follow suit.

However, large-scale deployment will depend on reliability. AI agents that make mistakes in production environments — especially in financial, healthcare, or infrastructure systems — could expose companies to significant risk. Trust, therefore, becomes as important as capability.

Anthropic competes in a crowded field of AI developers racing to build more autonomous systems. The pace of model improvement, combined with falling compute costs and expanding enterprise integrations, suggests that experimentation with AI agents will intensify over the next year.

Preparing for the Transition

Cherny’s advice to workers is pragmatic: experiment with AI tools and understand how they function. Familiarity with agentic systems — including their limitations and failure modes — may become a foundational skill across industries.

Rather than eliminating work outright, agentic AI is likely to redefine it. The shift could mirror earlier technological inflection points in which tools first augment workers before altering organizational structures altogether.

India’s decision to delay high-level talks underscores how Washington’s abrupt shift to a 15% global tariff has reset the negotiating baseline and forced both sides back to strategic recalibration.

India has postponed a planned visit by its top trade negotiators to Washington, D.C., after President Donald Trump moved swiftly to impose a 15% global import tariff following a landmark court ruling on his earlier trade measures.

According to a person familiar with the development who spoke to CNBC, the visit “will be rescheduled at a mutually convenient date,” as both sides assess the implications of the latest U.S. action. The reassessment comes after the Supreme Court of the United States struck down several of Trump’s previous tariffs as illegal. Within hours, the administration invoked Section 122 of the Trade Act of 1974 to first impose a 10% global import duty, later increasing it to 15%.

The abrupt escalation has effectively altered the framework under which India and the U.S. were negotiating an interim trade agreement.

A Deal in Motion, Now in Flux

India’s chief negotiator, Darpan Jain, and his team had been scheduled to begin a three-day round of in-person meetings this week with the office of the U.S. Trade Representative, led by Ambassador Jamieson Greer. Those talks were widely viewed as a precursor to finalizing the legal text of the interim agreement.

Earlier this month, the two sides agreed in principle to reduce India’s reciprocal tariff exposure from 25% to 18%, with provisions allowing for adjustments. A joint statement issued on Feb. 6 stated: “In the event of any changes to the agreed-upon tariffs of either country, the United States and India agree that the other country may modify its commitments.”

With the U.S. applying a 15% global tariff across the board, the negotiated 18% figure loses much of its relative benefit. Ajay Srivastava, founder of the Global Trade Research Initiative and a former Indian trade negotiator, noted that India, like other trading partners, appears set to face the 15% levy in addition to most-favored-nation (MFN) rates, typically around 2–3%.

In practical terms, this narrows the preferential margin India had secured and raises questions about whether the interim arrangement still delivers sufficient economic advantage.

“The 18% tariff negotiations were based on a certain premise of some benefits which is now gone. Now, both sides have to rethink their strategy,” Srivastava said, adding that Washington may have “more pressing issues” following the court ruling and its aftermath.

For India, the delay suggests a desire to avoid locking in commitments under conditions that are rapidly evolving. New Delhi must assess how the 15% global tariff interacts with sector-specific duties and how it affects key export categories such as pharmaceuticals, textiles, auto components, and information technology services-linked goods.

From Washington’s perspective, invoking Section 122 provides a legally distinct basis for imposing tariffs after the Supreme Court curtailed earlier emergency-based measures. Section 122 allows temporary tariffs to address balance-of-payments concerns or currency issues, but its use on a broad global scale introduces fresh legal and diplomatic complexities.

U.S. Trade Representative Jamieson Greer announced on Friday that his office will launch multiple new investigations under Section 301 of the Trade Act of 1974, covering most major U.S. trading partners.

Others Too: The Implications Are Far-Reaching

The reset in U.S. tariff policy does not affect India in isolation. The flat 15% global duty alters competitive dynamics across emerging markets and advanced economies alike. Countries that had been negotiating tailored reductions now find themselves facing a standardized baseline.

Greer sought to reassure trading partners and markets that the ruling would not derail ongoing trade agreements.

“The administration is confident that all trade deals negotiated by President Trump will stay in effect,” he said. “Our partners have been responsive and engaged in good-faith negotiations and agreements despite the pending litigation.”

For India, the postponement of talks may serve several objectives:

• Re-evaluating whether to seek deeper tariff concessions in light of the new baseline.
• Assessing domestic industry impact before formalizing commitments.
• Monitoring potential legal or political challenges within the U.S. to the new tariff structure.

Commerce Minister Piyush Goyal had indicated on Friday that the interim agreement was likely to be signed in March and implemented in April. That timeline now appears uncertain.

India and the United States have expanded trade ties significantly in recent years, with bilateral goods and services trade crossing record levels. Washington has sought greater market access for agricultural products and manufactured goods, while India has prioritized tariff relief and improved access for its exports.

The global tariff increase reshapes bargaining power. A uniform 15% duty may reduce Washington’s need to negotiate country-specific concessions quickly, while India must weigh whether waiting could yield more clarity or better terms.

However, the decision to reschedule, rather than cancel, the talks suggests that both governments remain committed to the broader objective of an interim agreement. But the immediate priority appears to be strategic clarity.