Google Cloud Next ’26 was a major turning point for enterprise AI.
Google officially launched the Gemini Enterprise Agent Platform, A2A v1.2 reached production deployments across 150+ organisations, and MCP has rapidly become the standard interface layer between AI agents and enterprise tools.
The industry is quietly converging around a multi-layer agentic stack:
• MCP → tool integration
• A2A → agent communication
• WebMCP → structured web interaction
• AP2 → agentic payments and commerce
In my latest deep dive, I break down:
Gemini Enterprise architecture
MCP vs A2A (clearly explained)
Enterprise orchestration layers
Security vulnerabilities already discovered in production
Agent governance and non-human identity
TPU 8 infrastructure economics
Real-world deployment data from Gartner and McKinsey
One of the biggest lessons from the research:
Scaling agents successfully is less about model intelligence and more about workflow redesign, observability, governance, and orchestration.
We’re moving from “AI assistants” to enterprise operating systems for autonomous workflows.
Read full breakdown here
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