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Practical, experience-driven insights from building and running multi-agent AI workforces. I write about what actually works, what doesn't, and the lessons I've learned deploying real agent systems for real businesses. No hype. No buzzwords. Just the stuff that matters if you're serious about using AI to grow.
Every post comes from something I've actually built, tested, and deployed. Real projects, real decisions (and mistakes), real results. If it's on this blog, it's because I've done it myself.
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Running 18 AI agents in production taught me that context is everything. Nyne's approach to solving this fundamental problem could change how agents work in business.
Gumloop's massive Series B validates what I've learned running 18 AI agents in production: the future isn't about hiring AI specialists, it's about empowering your existing workforce to become agent builders.
Deploying AI agents is the easy part. Getting your team to actually use them is where most businesses stall. Here's the onboarding playbook I use with every client.
Claude discovered 22 Firefox vulnerabilities in 14 days, proving AI agents can handle critical security operations that previously required expensive human experts.
OpenAI's Codex Security represents a major shift toward autonomous security operations - moving from scanning tools to AI agents that understand context and patch vulnerabilities independently.
DiligenceSquared is using AI voice agents to replace expensive consultants in M&A due diligence. Here's what this means for every knowledge worker.
MIT identifies the critical gap between AI pilots and production deployment. Here's why enterprise AI projects fail and the frameworks that actually work.
Google's fastest and most cost-efficient model yet could dramatically reduce operational costs of running AI agent fleets at scale. Here's what it means for your business.
A deep dive into how 14.ai successfully replaced entire customer support teams at startups and what lessons you can apply to deploy AI agents in your business.
Anthropic's MCP connects agents to tools. Google's A2A connects agents to each other. Together, they are the HTTP of the AI era. 97M SDK downloads, 5,800+ servers, 50+ enterprise partners. Here's what you need to know.
Claude Cowork turns AI into a full enterprise teammate with plugins for Google Workspace, Slack, DocuSign, and more. Then Anthropic acquired Vercept to make Claude operate software like a human. Here's what happened and why it matters.
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