Agentic Web and the Rise of AI Agents

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December 15, 2025

The Web’s Next User Isn’t Human

For 30 years, the internet has been built around a single assumption:
a human is sitting at the screen.

They search.
They click.
They compare.
They decide.

That assumption is now breaking.

The next dominant “user” of the web will not scroll, skim, or browse. It will delegate.

AI agents—software systems that can reason, communicate, and act—are beginning to search, shop, book, negotiate, and execute tasks on behalf of people. And as they do, they are forcing a radical rewrite of the internet’s underlying architecture.

This is not a UI change.
It is not a productivity feature.
It is not another SaaS trend.

It is the beginning of a machine-first internet, where websites, apps, and marketplaces are designed primarily for machines that act, not humans who browse.

For startups, this shift will be as consequential as:

  • the rise of browsers in the 1990s
  • the mobile-first transition of the 2010s
  • the API economy that followed

And most founders are dangerously unprepared for it.


What Is the Agentic Web? (And Why It’s Not Just “AI on the Internet”)

The term agentic web describes an internet where AI agents are first-class participants.

Unlike chatbots or copilots, agents don’t just answer questions. They:

  • interpret goals
  • break them into steps
  • coordinate with tools and services
  • execute actions autonomously
  • report outcomes back to users

In an agentic web:

  • users express intent
  • agents perform work
  • websites expose capabilities, not pages

This is a fundamental shift from information retrieval to task execution.

The original web answered questions like:

“What flights exist between London and New York?”

The agentic web answers:

“Book the best trip that fits my preferences and constraints.”

That difference changes everything—from UX and APIs to monetization and regulation.


From Browsing to Delegation: How We Got Here

To understand why this shift is happening now, it helps to zoom out.

Web 1.0: Read

Static pages. Human readers. Manual discovery.

Web 2.0: Interact

Forms, feeds, marketplaces, ads. Still human-driven, but more dynamic.

Web 3.0 (Actual, Not Crypto): Act

Agents execute workflows across services, continuously and autonomously.

Large language models made this possible by solving one key problem:
natural language reasoning at scale.

But reasoning alone isn’t enough. To reshape the web, AI needs the ability to act.

That’s where agents—and new standards—enter the picture.


Why AI Agents Break the Existing Web

Today’s internet is optimized for humans in three ways:

  1. Visual interfaces (menus, buttons, filters)
  2. Manual workflows (forms, confirmations, checkouts)
  3. Fragmented APIs (each service speaks its own dialect)

AI agents struggle in this environment because:

  • they reason in natural language
  • they need consistent, machine-readable action descriptions
  • they can’t afford to “learn” every bespoke API from scratch

If agents are going to operate independently, the web’s plumbing must change.

That realization has triggered a standards landrush.


The New Infrastructure Layer: MCP, A2A, and the Agent Stack

The agentic web is not emerging randomly. It is being intentionally standardized.

Model Context Protocol (MCP): Teaching Agents What Systems Can Do

MCP is an open protocol designed to solve a simple but critical problem:

How does an AI agent discover what actions a system supports?

Instead of reading human-written API docs, an agent can:

  • ask an MCP server what capabilities exist
  • understand permissions and constraints
  • invoke actions safely and predictably

For startups, MCP reframes your product as a capability provider, not a UI.

If your service can:

  • book
  • cancel
  • search
  • compare
  • generate
  • refund
  • notify

Then MCP is how agents learn that.

Agent-to-Agent (A2A): When Agents Work Together

Single agents are powerful.
Networks of agents are transformative.

A2A protocols allow agents to:

  • advertise capabilities
  • delegate subtasks
  • negotiate responsibility
  • coordinate execution

A “travel agent” AI, for example, may rely on:

  • a flight-search agent
  • a hotel-pricing agent
  • a car-rental agent
  • a policy-compliance agent

This is the foundation for multi-agent economies, where software services collaborate dynamically.

Why Standards Matter (Ask Netscape)

History is clear:
Platforms don’t win because they’re best. They win because they’re standard.

Browsers won the web because HTML and HTTP became universal.
Mobile apps won because iOS and Android controlled distribution.

The agentic web will be no different.

The dominant agent protocols will:

  • determine traffic flows
  • decide integration costs
  • shape who captures value

Which is why major players are moving fast.


The Agentic AI Foundation: A Browser Wars Moment

The formation of an industry-backed foundation to steward open agent standards is a massive signal.

It means:

  • this is no longer speculative
  • governance is forming
  • adoption is accelerating

When competitors collaborate on infrastructure, it’s because the market is inevitable—and the fight is about position, not existence.

For startups, this is the brief window where:

  • rules are still fluid
  • early alignment compounds
  • late movers pay integration tax

NLWeb and the Death of Click-Based UX

Even with standards, there’s a problem:
Most websites are still designed for human eyes.

Enter natural-language web interfaces.

Instead of navigating menus and filters, users—or agents—can simply ask:

  • “What’s the best option for X?”
  • “Compare these choices under Y constraints.”
  • “Do this task now.”

This collapses:

  • search
  • filtering
  • comparison
  • decision

into a single intent expression.

The implications are profound:

  • UX becomes conversational
  • SEO becomes intent optimization
  • UI becomes optional

For startups, this raises an uncomfortable question:

What happens when users never see your homepage?


Agent-Powered Browsers: The New Gatekeepers

Browsers are being reimagined—not as windows, but as operators.

Modern agent-native browsers can:

  • track prices continuously
  • monitor availability
  • fetch and summarize documents
  • manage inboxes
  • execute purchases

They don’t wait for commands.
They act in the background.

This recreates the power dynamics of the 1990s, when browsers decided which sites mattered—except now, the “browser” makes decisions on your behalf.

If your startup depends on:

  • funnel optimization
  • attention capture
  • human persuasion

You are now competing with algorithms, not eyeballs.


Agentic Commerce: When the Buyer Is Software

Commerce is one of the first industries to feel the impact.

Why? Because buying is a task—perfect for delegation.

In an agentic commerce world:

  • discovery happens via agents
  • comparison is instantaneous
  • checkout is embedded
  • loyalty is algorithmic

The “funnel” collapses.

This creates existential questions for marketplaces, brands, and DTC startups:

  • How do agents choose vendors?
  • What signals matter?
  • Who controls ranking?

It also explains why incumbents are nervous—and why legal conflicts are emerging.


Why Advertising Must Evolve (or Die)

Today’s web is funded by human attention.

Search ads.
Social feeds.
Display networks.

But agents don’t scroll feeds.
They don’t get distracted.
They don’t feel FOMO.

They optimize.

In the agentic web, advertising becomes:

  • ranking incentives
  • preference weighting
  • machine-readable offers
  • trust and reliability signals

Marketers won’t pitch people.
They’ll pitch decision-making algorithms.

This doesn’t kill advertising—it rewires it.

And it opens enormous opportunities for startups building:

  • agent-aware ad platforms
  • intent marketplaces
  • trust scoring systems
  • outcome-based placements

The Scale Explosion: Why the Agentic Web Will Be Bigger Than the Human Web

Humans operate at human speed.

Agents do not.

An AI agent can:

  • read thousands of pages per second
  • monitor markets continuously
  • run parallel workflows
  • act 24/7

This means:

  • dramatically more web traffic
  • dramatically more API calls
  • dramatically more economic activity

Much of it invisible to humans.

The “visible web” may shrink—while the machine web explodes underneath it.


Security, Trust, and the New Attack Surface

Where agents act, risk follows.

Key challenges include:

  • unauthorized actions
  • hallucinated justifications
  • prompt injection attacks
  • data exfiltration
  • silent failures

This creates a massive new category:
agent trust and governance infrastructure.

Expect growth in startups offering:

  • permission frameworks
  • audit trails
  • sandboxed execution
  • human-in-the-loop systems
  • agent observability

In the agentic web, trust is the product.


From Pull to Push: The Most Underappreciated Shift

Perhaps the biggest change is subtle.

The traditional web is pull-based:

  • users initiate
  • systems respond

The agentic web becomes push-based:

  • agents anticipate needs
  • actions happen unprompted
  • humans supervise outcomes

Meetings get scheduled.
Research gets flagged.
Tasks get completed.

The web stops waiting—and starts acting.

This transforms software from a tool you use into a system that works for you.


What Founders Must Do Now (Not Later)

This shift will not reward passive observers.

1. Make Your Product Agent-Legible

  • Clear capability definitions
  • Structured data
  • Predictable behavior

2. Optimize for Algorithmic Choice

  • Transparent pricing
  • Reliable availability
  • Consistent outcomes

3. Prepare for Invisible Users

  • Your “traffic” may never render a page
  • Success metrics must evolve
  • UX ≠ UI

4. Treat Standards as Strategy

  • Early alignment compounds
  • Late adoption is expensive

The Final Question Every Startup Must Answer

Not:

“How do we get users to choose us?”

But:

“How does an agent decide we’re the best option?”

Because the next version of the internet won’t be built for humans who browse.

It will be built for machines that decide, act, and execute.

And the startups that win won’t just be used by people.

They’ll be trusted by machines.