5 OpenClaw Agents Run My Home, Finances, and Code. Five specialized OpenClaw agents run a family’s homeschooling, finances, scheduling, development, and ops—deployed on separate Mac Minis and linked to an Obsidian second brain. It’s a concrete, composable example of multi-agent deployment and long-context memory in the wild, showing how to split responsibilities, isolate state, and stitch personal infrastructure—Principle 09 in practice.

Atlassian embeds agents into Jira and embraces MCP for third-party integrations. Atlassian installs AI agents inside Jira and opens Rovo to third-party agents via MCP, launching an open beta. Turning an issue tracker into an agent host and adopting MCP changes how you design integrations, contract tool schemas, and think about permission boundaries inside enterprise workflows.

Perplexity launches Perplexity Computer, “a general-purpose digital worker” that can route work across 19 AI models, available initially for Max subscribers. Perplexity ships a digital worker that routes tasks across 19 models to match strengths and cost profiles. Multi-model routing as a platform pattern forces outcome engineers to design competency-based routing, observability, and fallbacks when models disagree.

Vast Data expands AI Operating System with global control plane, zero-trust agent framework and deeper NVIDIA integration. Vast Data adds a global control plane and a zero-trust agent framework for hybrid multicloud AI deployments. A control plane + zero-trust model is the operational foundation you need to scale agent fleets securely and to enforce provenance, access policies, and lifecycle controls across environments.

I Made MCP 94% Cheaper (And It Only Took One Command). Converting MCP tool catalogs to lightweight CLIs cuts token costs by ~94% via lazy schema loading and deferred discovery at runtime. That cost/latency trick is an immediate, implementable optimization for anyone building tool-driven agents or wide MCP catalogs—practical context-engineering and system-level cost control.