Building an AI Operating System for SMBs with Wil Lavender

Episode SummaryHow AI becomes a real operating system for small and mid-sized businesses. Wil Lavender shares his path from post-2008 finance roles and nearly 15 years in bank back-office technology to becoming employee number one at Agent700. He and Brian talk about why most SaaS tools force companies into a one-size-fits-all mold, and how AI can help businesses build custom solutions at lower cost. They also dig into tool lock-in, cost arbitrage, and why “digital employees” need feedback loops to improve. Wil closes with a practical example of turning policy binders into usable company-wide knowledge that actually influences decisions.Key TakeawaysA shift from front office finance to back office technology can unlock a career focused on enabling outcomes through problem-solving.AI-driven custom software can reduce dependence on expensive SaaS tools that were built for mass appeal, not one business.Sovereignty matters because the “best” model changes fast, and staying flexible protects both performance and cost.Costs are part of the AI equation, and being able to switch tools can become a real cost optimization lever over time.Treating AI like digital employees reframes failures as inputs, because feedback and iteration are what make systems reliable.Architecture and outcome clarity still matter, because AI can generate code while humans define what good looks like and why.Global knowledge unlocks more than chatbots, because shared policies and context can shape decisions across teams instead of sitting in silos.TimelineEarly00:00:00 Wil’s path from finance interests into investment banking and prop trading after 200800:01:00 Discovering the appeal of back office problem-solving and technology enablement00:02:00 Nearly 15 years building teams and solutions across banking support functions00:03:00 Taking time off, consulting, then joining a startup as employee number oneMiddle00:03:00 What Agent700 is building, an AI-driven operating system with agentic capabilities00:05:00 Why SaaS tools like CRMs can feel overbuilt and still miss what a business truly needs00:06:00 Sovereignty and autonomy across AI providers, plus the rapid shifts in model leadership00:07:00 Cost considerations, experimentation versus repeatable “brick laying,” and optimizationLate00:09:00 Why AI-built software still benefits from expertise in debugging and architecture00:10:00 Managing AI like digital employees, feedback loops, and working backward from outcomes00:16:00 A practical use case, turning policy binders into global knowledge that guides decisions00:20:00 Hiring cycles, the storming-to-performing curve, and why AI is driving hiring demand00:22:00 What Wil is excited about in 2026 and how to reach himLinks and ResourcesLinkedIn: https://www.linkedin.com/in/wil-lavender-36a636259/Company: https://www.agent700.ai/