From Code to Collaboration: The Rise of Autonomous Software

Table of Contents

• 🤔What is MCP?

• 🤔🤔What is A2A?

• Why This Matters

• 📖Further Reading & Resources

• My Disruptive Take

• Learn about MIDWESTCON 2025

• The Disruption Now Podcast

For 70 years, we treated software like a kitchen recipe.
We told the computer: “Add salt. Now stir. Set timer.” Every step was programmed, every instruction manual.

Now?
We’re handing AI the pantry and saying, “You figure it out.”

This week, Google launched a new protocol called Agent-to-Agent (A2A)—and it connects with something I’ve been diving into: Model Context Protocol (MCP). These two protocols are the foundation for a new age of software—autonomous, adaptive, and collaborative.

Let’s break it down in real terms.

🤔What is MCP?

Model Context Protocol is like a universal adapter for AI. It helps AI systems connect to tools, apps, and data sources—without needing a new integration every time.

Think of it like this:

MCP is the USB-C for AI—one plug that works everywhere.
Your AI assistant no longer needs a different connection for Google Calendar, your database, and your CRM. It just asks for what it needs—and MCP handles the rest.

Or imagine MCP as a restaurant waiter:
• The AI places an order for data or an action.
• The waiter (MCP) speaks the kitchen’s language.
• The kitchen (app or service) prepares and sends the order back.

For startup teams, this means faster deployment of AI features. You can build once and connect anywhere. Less code. Less friction. More power.

🤔🤔What is A2A?

If MCP helps an AI talk to tools, Agent-to-Agent protocol (A2A) helps AIs talk to each other.

A2A is a universal communication system for AI agents. It lets them:
• Discover each other
• Share tasks
• Pass information
• Coordinate in real time

Picture this:

You’ve got an AI agent for scheduling. Another for data. Another for customer support.
Before A2A, they operated in silos.
With A2A, they collaborate—like coworkers with Slack access.

Now your scheduling agent can ping the data agent:
“Can you pull the latest numbers before I book this meeting?”

And it just happens—no human coordination required.

A2A turns isolated bots into a team of autonomous collaborators.

Why This Matters

Together, MCP and A2A unlock the next chapter of tech:
Autonomous Software.

Software that doesn’t need instructions.
Software that reasons, adapts, and works together to get things done.

This changes everything about how we build digital systems:
• No more rigid workflows.
• No more fragile integrations.
• No more single-function bots.

Instead, you get smart, flexible AI agents that:
• Access tools using MCP
• Collaborate via A2A
• Build real-time workflows on the fly

We’re shifting from “code-based systems” to intelligence-based networks

📖Further Reading & Resources

To learn more about MCP and A2A (in accessible language), check out these articles and posts:
• Anthropic—Introducing the Model Context Protocol: Anthropic's official announcement of MCP (Nov 2024) explains the motivation behind MCP. It’s a brief read on how MCP “provides a universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol,” enabling AI to access the data it needs more easily. This is great for understanding the problem MCP solves.

• TechTarget News – MCP fever spreads in cloud-native world: A news piece by Beth Pariseau (April 2025) reporting on the rapid adoption of MCP in the industry. It highlights that MCP, introduced by Anthropic in November, has quickly gained “buzz” with hundreds of integrations from various vendors and even support from OpenAI and Microsoft. This article underscores why MCP is considered a big deal (momentum and broad support) and how it’s becoming a standard for AI tool integration.

• Google Developers Blog – Announcing the Agent2Agent (A2A) Protocol: Google’s official blog post (April 2025) introducing A2A. It details how A2A works and its core purpose: allowing AI agents to “communicate with each other, securely exchange information, and coordinate actions” across different applications. It also mentions that A2A was developed with over 50 partners on board and how it complements Anthropic’s MCP. This is a more technical source, but straight from the horse’s mouth – useful for a deeper dive and the enterprise vision behind A2A.

• Medium – Google Introduces Agent-to-Agent Protocol (A2A) to Break Down AI Silos: An easy-to-read overview (April 2025) that summarizes A2A in everyday terms. The author calls A2A a “universal ‘friend request’ protocol for AI agents”  and explains how it standardizes collaboration between agents regardless of the platform. It draws an analogy to early Android’s ecosystem to convey how A2A, backed by 50+ companies, is poised to create a new interoperable AI ecosystem. This piece is helpful in quickly grasping why A2A is exciting without wading into too much technical detail.

My Disruptive Take

This isn’t just another tech update.
This is the beginning of autonomous software.

We’re no longer writing code for every decision.
We’re building systems that make decisions on their own.

But here’s the deal:
The potential is enormous—and so are the risks.

Opportunities:
• Founders can launch AI-driven products faster than ever.
• Teams can automate complex processes without stitching together a dozen tools.
• Businesses can mix and match the best agents from different vendors.

Challenges:
• Security: How do we trust agents making decisions in real time?
• Debugging: What happens when one agent breaks the chain?
• Governance: Who’s responsible when AI agents start talking without human oversight?

This is a whole new game.
And we need new rules, new mindsets, and new infrastructure to keep up.

Whether you’re a startup founder, civic leader, or data nerd, one thing’s clear:

If you’re not thinking about autonomous software now, you’ll be disrupted by it later.

Learn about MIDWESTCON 2025

The Disruption Now Podcast

Keep Disrupting My Friends,

Rob, CEO of Disruption Now & Chief Curator of MidwestCon

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