For two years, the hard part of running an AI agent was getting it connected to anything. That problem is now mostly solved, and almost nobody in go-to-market has noticed what it means.

Two open standards did the work. The Model Context Protocol (MCP) connects agents to tools and data. The Agent2Agent protocol (A2A) connects agents to each other. Both are now governed by the Linux Foundation, both are backed by every major cloud and enterprise software vendor, and both crossed the line from experiment to infrastructure in the last twelve months.

The numbers behind the shift

MCP passed 10,000 public servers and 97 million monthly SDK downloads in its first year, and in December 2025 it was donated to the Linux Foundation's new Agentic AI Foundation. ChatGPT, Gemini, Microsoft Copilot, Cursor, and VS Code all speak it. An MCP server written once can be used by any agent that supports the protocol, which is now nearly all of them.

A2A followed a similar arc. It launched in April 2025 with just over 50 supporters. By its first anniversary, the Linux Foundation reported more than 150 organizations backing the standard, SDKs in five languages, and production integrations in Azure AI Foundry, Amazon Bedrock, LangGraph, and CrewAI. The named backers read like a vendor shortlist: AWS, Cisco, Google, IBM, Microsoft, Salesforce, SAP, ServiceNow.

Put the two together and the picture is simple. An agent can now reach any system in your stack through MCP, and it can hand work to any other agent through A2A. Agents stopped being features inside a product. They became nodes in a network.

What a network changes for GTM

Here is the uncomfortable part. Every GTM team we talk to is still evaluating agents one at a time. Which SDR agent writes better emails. Which research agent produces cleaner account briefs. Which forecasting agent is closest to the number.

Those are fair questions for a world of isolated tools. They are the wrong questions for a network. In a network, the quality of any single node matters less than what the nodes share.

Consider what actually happens when a prospecting agent built on one framework hands a qualified account to a research agent built on another, which then drafts an outreach sequence and asks a third agent to log the activity in the CRM. Three vendors, three memories, three ideas of what "qualified" means. The handoffs work mechanically because A2A standardized the envelope. The content inside the envelope is a different story.

• The prospecting agent scored the account against last quarter's ICP definition. The research agent is working from the one in a Notion page nobody updated.

• The outreach agent has no idea the champion at that account left six weeks ago, because the agent that learned it never shared it.

• The CRM-writing agent has the same write permissions as the rep who installed it, which is to say all of them.

Nothing in either protocol prevents any of this. MCP and A2A solve connection. They say nothing about coherence.

Standards solve plumbing, not judgment

This is not a criticism of the protocols. It is what they were designed to do. TCP/IP does not care whether the packet is a wire transfer or a phishing email. HTTP does not know if a page is true.

The same holds here. MCP tells an agent how to call Salesforce. It does not tell the agent which of the four "customer status" fields is the one your finance team trusts. A2A tells two agents how to negotiate a task. It does not tell them whose definition of pipeline stage wins when they disagree.

The governance picture is thinner still. Gravitee's 2026 survey of more than 900 executives found that 81% of teams have agents past the planning stage, but only 14% ship them with full security and IT approval, and 88% report confirmed or suspected agent-related incidents. Those numbers were collected before agents could hand each other work over a standard protocol. A network of agents with per-agent permissions and per-agent memory does not make the governance gap smaller. It multiplies the surface area.

The layer the protocols leave open

So what does a GTM team actually need once connection is free?

Three things, and they sit underneath the agents rather than inside any one of them.

Shared grounding. One typed, current model of your accounts, contacts, deals, ICP, and definitions that every agent reads from, regardless of who built the agent. When the champion leaves, every node knows. When the ICP changes, there is one place to change it.

Shared rules. Governance applied at the point where an agent acts, not inside each vendor's settings page. Per-agent permissions. Human approval on writes that matter. One audit trail across all of them.

A shared scoreboard. Attribution that ties agent activity back to what moved in the pipeline, so when you ask which of your nine agents earned their seat, the answer does not depend on nine different dashboards.

This is the gap we built wysdym to fill. It is the operating layer for agentic GTM: one MCP door to your stack through the Gateway, with Cortex holding the shared memory, Governance setting the rules on every action, and Observe reporting which agents are actually working. You bring the agents. Claude, OpenAI, LangGraph, custom builds, whatever your team already runs. The protocols make those agents able to connect. The operating layer makes them worth connecting.

The question to ask this quarter

The protocol wars are over, and openness won. That is good news. It means the choice of agent is no longer a lock-in decision, and your stack will keep getting more connected whether you plan for it or not.

The planning question has moved. It is no longer "which agent should we buy?" It is "what will every agent we buy share?" Teams that answer it get a network that compounds. Teams that skip it get a network that argues with itself.

If you are working through that question, we would like to compare notes. Talk to the founders at wysdym.ai, or see the full set of agentic AI numbers at gtmstats.wysdym.ai.