The era where developers must write every line of code themselves is ending. AI agents are transforming web development.
Kawin Suangkaew
The era where developers must write every line of code themselves is ending. AI agents are transforming web development from automatic debugging to building entire applications
In early 2026, the Next.js team noticed an interesting pattern in developer workflows. When developers see an error in the browser, they copy the error details, paste them into an AI editor, and ask the agent to fix it. The critical problem is that agents can't see the browser. Runtime errors, client-side warnings, and rendered components are all invisible to them.
When a user says "fix the error," the agent doesn't know what error they mean because the error happens in the browser, not in the source code that the agent can read.
"We needed to make Next.js itself visible to agents" - Next.js Team
The Next.js team built an in-browser chat agent called Vector, similar to smart devtools. It allowed developers to select elements on the page, see their source code, and prompt for changes. Vector had Next.js best practices baked in to help agents avoid hallucination.
Although Vector was useful, it overlapped with general coding agents like Cursor and Claude Code, which most developers were already using for all their projects—not just Next.js. The UI selection made it easy to point at exactly what you wanted to change, but it wasn't something people needed every day. The team decided to sunset Vector but took what made it useful and built it into Next.js itself.
Model Context Protocol (MCP) changed the game for Next.js. It provided a way to expose internal data such as errors, routes, and rendered segments so agents could see them. But exposing data alone wasn't enough. Agents also needed to discover running dev servers and communicate with them.
This led to creating next-devtools-mcp, which enables agents to:
Simultaneously, the AI agent builder market is growing rapidly. Gumloop, a startup that raised $50 million from Benchmark, is challenging organizations to enable every employee to create AI agents without technical knowledge.
Gumloop claims that enterprise clients like Shopify, Ramp, Gusto, Samsara, Instacart, and Opendoor can deploy reliable AI agents that autonomously handle complex, multistep tasks, all without ever needing an engineer.
"Enterprise automation is a massive pot of gold. I think it's the biggest category in enterprise AI" - Everett Randle, General Partner, Benchmark
Not just web development—AI agents are transforming every industry. Rox AI, a startup developing autonomous AI agents to boost sales productivity, recently raised new funding valuing the company at $1.2 billion.
Rox positions itself as an "intelligent revenue operating system" that plugs into existing software—from Salesforce to Zendesk—and deploys hundreds of AI agents to:
From Next.js's experience, there are important lessons for developers:
Next.js is making adoption easier. You can already run npx @next/codemod to generate an up-to-date docs index for your project, and they're expanding their eval suite to cover more Next.js 16 APIs.
Longer term, the goal is to build this into next dev so agents get the right context automatically without any setup.
When you treat agents as first-class users and meet them where they are, debugging becomes a tight feedback loop between code, runtime, and AI