Agent 365, Vertex, Gemini: The Rise of Governed Multi-Agent AI

What happened

Over the past two weeks (early–mid November 2025) major cloud vendors released agent-focused features that move AI from isolated bots toward managed, multi-agent ecosystems. Microsoft launched Agent 365 (~2025-11-18 UTC) to “manage existing AI bots within organizations,” offering a registry, real‐time oversight and centralized controls (early access). Google Cloud updated Vertex AI’s Agent Builder (~2025-11-07 UTC) with an Agent Development Kit (ADK), prebuilt plugins (including a self‐heal plugin), Go language support, a single‐command deployment CLI and new observability/security tools. Google also expanded the Gemini API (~2025-11-07 UTC) to support JSON Schema across Gemini 2.5 models and integrations with libraries like Pydantic and Zod for more consistent agent-to-agent messaging.

Why this matters

Platform & governance shift — enterprises can build larger, more autonomous agent fleets while adding governance and interoperability.

• Governance: Agent 365 and Vertex security features (Model Armor, Security Command Center) put monitoring, access control and prompt‐injection detection front and center — signaling management is expected, not optional.
• Interoperability: JSON Schema support and schema libraries reduce brittle handoffs and make chained, multi‐agent workflows more reliable.
• Autonomy and resilience: Self‐heal plugins and observability dashboards aim to let agents operate with less human intervention while tracking tokens, latency, errors and tool calls.
• Accessibility: ADKs, prebuilt plugins and new language support (Go) lower engineering barriers, enabling smaller teams to deploy complex agentic systems.

Risks noted in the article include agent sprawl (Microsoft projects “hundreds or thousands” of agents), nascent security/detection mechanisms (prompt injection, hallucinations), coordination/correctness challenges and performance unpredictability from increased autonomy.

Sources

• Wired — coverage of Microsoft Agent 365: Microsoft AI Agent 365
• TechRadar — Google Cloud Vertex AI Agent Builder updates: Google Cloud makes its AI Agent Builder smarter
• Android Central — Gemini API structured outputs and multi‐agent workflows: Google makes Gemini API easier for multi‐agent workflows

• Programming languages supported in Vertex AI Agent Builder ADK — 3 languages, adds Go alongside Python and Java to broaden developer access and integration paths.
• Deployment pipeline commands for Vertex AI ADK — 1 command, reduces deployment friction by enabling agent rollout via a single CLI step.
• Schema libraries supported by Gemini API for structured outputs — 3 libraries, standardizes multi-agent messaging via JSON Schema with OpenAI 3.0, Pydantic, and Zod.

• Security & trust gaps: Prompt injection, hallucinations, and tool misuse remain significant despite new defenses (Google’s Model Armor, Security Command Center; Microsoft Agent 365 oversight launched ~2025-11-18 UTC), risking data exposure, fraud, and unreliable automation for enterprises and regulated sectors. Opportunity: Vendors and CISOs can differentiate by deploying centralized registries, injection detection, and end-to-end auditing to win compliance-sensitive workloads.

• Agent sprawl & maintenance burden: As organizations move toward “hundreds or thousands” of agents, versioning, dependencies, access, and cost attribution become complex, threatening operational stability and budgets. Opportunity: Centralized agent registries (Agent 365), observability dashboards (Vertex AI), and FinOps-style governance create platform and services revenue for CIOs/CTOs and MSPs.

• Known unknown: Multi-agent reliability and compliance outcomes: Metrics for agent-to-agent coordination (success rates, end-to-end latency), cross-vendor schema adoption beyond Google’s Gemini JSON Schema, and paths to meet finance/healthcare oversight remain unclear. Opportunity: Standards bodies, cloud providers, and early adopters that publish benchmarks, schema conventions, and audit frameworks can shape policy and secure enterprise adoption.

Supporters will call this fortnight the moment agent ecosystems finally grew up: Microsoft’s Agent 365 puts a registry and real-time oversight at the center, Vertex AI adds self-heal plugins, dashboards, and Model Armor, and Gemini’s JSON Schema support turns inter-agent chatter from brittle guesswork into contract-driven handshakes. Skeptics will counter that we’ve swapped novelty for nuance: autonomy that “self-heals” can also self-propagate faults, security tooling remains nascent against prompt injection, and “hundreds or thousands” of agents risks costly sprawl. If autonomy is the goal, why is every headline about control? The article flags real uncertainty—coordination conflicts without rigorous schemas, unpredictable performance, and the burden of auditing sprawling dependencies—suggesting governance isn’t a nice-to-have; it’s the fragile spine of the whole vision.

Here’s the twist the facts support: the road to more autonomous agents is being paved not by freedom but by constraints—schemas, registries, and security perimeters are the breakthrough features. That flips the next phase from AI-as-brain to AI-as-institution: engineers, traders, and architects will be judged less on clever prompts and more on measurable coordination metrics, adoption of shared schemas, and readiness for audits in regulated domains. Watch whether structured outputs spread beyond the current stack, whether governance frameworks mature, and whether early access control planes like Agent 365 become the default layer for enterprise automation. Autonomy will scale only as fast as accountability does.