2026.05: AI Infrastructure Beats Model-Chasing
This week, three signals cut through the noise.
The pattern? The real work isn't in the shiny capabilities. It's in the boring foundations that let you deploy them safely and systematically.
Let's break it down.
Signal:
Signal One: Ignore the Agent Hype. Fix the Security Holes.
Critical security gaps in AI agent frameworks (like Claudebot/Moltbot/OpenClaw) expose API keys and credentials to attackers, with malicious plugins seeing thousands of downloads. This creates supply-chain attack vectors that show up as breach costs and compliance failures. If you own infrastructure or AI operations, rotate all API keys immediately, move off default ports, and establish plugin governance—start with agents touching customer data or production systems.
Signal Two: Forget Better Prompts. Orchestrate the Workflow.
Anthropic released Cowork plugins that handle complete workflows like “feature request → spec → stakeholder doc” or “support ticket → triage → response → KB update” by encoding team preferences and integrating tools. This reduces context-switching friction that shows up as inconsistent output quality and slow time-to-draft. If you own product, operations, or support, start with 2–3 high-volume workflows, connect read-only tool access first, and automate the drafting step while keeping human review for edge cases.
Signal Three: Stop Chasing Models. Build the Infrastructure.
Businesses that build AI infrastructure—documented context, digital assets, processes, and standards—let any model handle 80–90% of lead generation, nurturing, and sales work autonomously, while those chasing new models stay stuck in research mode. This removes the “learning every new model” treadmill and unlocks model-agnostic leverage where your role shifts to designing reusable assets. If you own growth, content, or operations, map one revenue-critical workflow this week, document the assets AI needs to execute it, and automate the content-generation step while keeping human editing for brand.
Scale:
Scale One: Ignore the Agent Hype. Fix the Security Holes.
Start Here: Audit your most privileged agents first—those touching customer data, financial systems, or production infrastructure. Implement weekly credential rotation and restrict agents to read-only access until you verify plugin safety. Track credential exposure incidents and time-to-rotate for 30 days before expanding agent permissions.
Scale Two: Forget Better Prompts. Orchestrate the Workflow.
Start Here: Pick 2–3 high-volume workflows where output format is consistent (specs, briefs, responses) and quality standards are documented. Connect tools with read-only access first and keep human review for final outputs, edge cases, and customer-facing content. Track turnaround time, revision count, and stakeholder satisfaction for 4 weeks before removing human review steps.
Scale Three: Stop Chasing Models. Build the Infrastructure.
Start Here: Map one revenue-critical workflow (lead nurture, sales follow-up, content creation) and document the assets AI needs to execute it in your voice. Start with stable, high-volume content generation (emails, briefs, responses) and keep human editing for brand consistency and edge cases. Track output quality, time saved, and pipeline impact (open rate, reply rate, conversion) for 60 days before expanding to additional workflows.
Deep Dive:
This week’s deep dive focuses on Signal Three: AI Infrastructure Beats Model-Chasing.
If you’re tired of testing AI tools that never make it to production, here’s a practical framework for building AI infrastructure that works regardless of which model you use. It includes the four-layer infrastructure model (business context, digital assets, structured processes, and specialized skills), real examples from companies using this approach, and a step-by-step guide to documenting your first revenue-critical workflow.
Best for founders, ops leaders, and growth teams who need to shift from AI research to AI deployment.
Thanks for reading!
My hot take, pick one thing from the signals above and do something about it. Security audit. Workflow documentation. Infrastructure mapping. The work that matters isn’t sexy, but it’s the work that compounds.
See you next Friday!
