Brian Chappell

Built from the operator’s seat - I came to AI after more than 20 years in internet marketing, search, and digital strategy. For the last two years, I have been rebuilding that experience into practical agentic systems I own and operate. This is not about adding an AI chat box to a business or getting walled into Claude or OpenAIs garden. It is about changing how work gets researched, delegated, checked, and shipped and being free to move around. I use my own businesses as the test environment, so these systems have to survive real deadlines, imperfect data, changing platforms, and failure.

Systems, not prompts - I built my AI operating layer around NanoClaw, connecting specialized agents to chat, scheduled tasks, structured memory, isolated workspaces, cross-channel handoffs, and human approval. From that foundation, I built BlogClaw to learn from WordPress revisions, GCE to coordinate research, drafting, images, QA, and Google Drive delivery. These are not isolated prompt experiments. They are repeatable workflows with roles, tools, permissions, outputs, and recovery paths.

Measure, learn, and keep control - I also built AdaptConvert and AdaptAgent for agent-assisted conversion and content enablement + experiments. I also created GLLMV, Great LLM Visibility, to measure how brands appear across ChatGPT Search, Google AI results, Gemini, and Perplexity using fixed questions and evidence-backed captures.

The same approach extends into commerce, WordPress and Shopify operations, Google Ads, social publishing, SEO research, and content production, its all now semi-automated with HITL checkpoints. My goal is not to remove people from the loop. It is to give independent operators and existing teams leverage they can understand, control, and improve.