Insights / Topic
Agentic AI
Agentic AI for the enterprise: agent architecture, permissions, autonomy, human approval and observability. Start with Designing for Agents: When Software Starts to Act, or see the AI Architecture Review and AI Strategy Advisory.
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macOS Full Disk Access: An Enterprise Plan
Apple says macOS Full Disk Access will soon require very explicit user action. Here’s how CTOs should prepare fleets, agents and permissions before it lands.
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Multi Agent Systems done right: no rogue agents
Agents don’t go rogue; we let them. Bound them with scoped tools, plan-as-code, budgets and middleware, then prove it in simulation before prod.
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NVIDIA Open Agent Safety Platform: An Enterprise Checklist
NVIDIA’s new safety stack pairs OpenShell with Sentry. Here’s how I’d map it onto an enterprise agent architecture, where to enforce controls, and who owns what.
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Multi-Agent Control Checklist: Engineering Agent Systems Like Software
If AI is software, we can engineer it like software. Here’s a concrete checklist to make agentic systems predictable without killing flexibility.
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Reworking CI for AI Teams with Multi-Agent Systems
AI code generation made CI the new bottleneck. Here’s a concrete blueprint to restructure CI/CD so PRs stay fast without torching your compute budget.
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MCP for Enterprise Commerce Agents: A Practical Playbook
Amazon blocking Meta’s Muse is a reminder: respect the rails. Here’s how I design commerce agents that stay compliant and reliable in the real world.
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Enterprise AI Agents After Amazon vs Muse: Build Resiliently
Amazon blocking Meta’s Muse is a reminder: scraping won’t scale. Here’s a concrete architecture to keep commerce agents effective, compliant and observable.
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Designing for Agents: When Software Starts to Act
Agents move software from answers to actions. The design questions that matter now are about permissions, evidence of completion, recovery and the limits of delegation.
