Summary
Craig Hewitt, who operates a seven-figure software company in roughly 10 hours per week, presents a 10-step framework he calls the “AI Native Sequence” for building reliable AI workflows, agents, and internal tools inside real businesses. The central argument: only one of the ten steps involves AI itself — building the system, at step four — while the other nine are the human-side work that most teams skip, which is why most AI projects succeed in demos and fail in production.
The sequence begins with identifying a genuine pain point (not a solution hunting for a problem), mapping the current workflow in granular detail before touching any tool, and collecting real-world training data — past examples, edge cases, source documents. Steps five through ten cover iterative testing until the system can’t be broken, wiring into live data sources (Notion, Gmail, Slack on input; Twitter, Substack, LinkedIn on output), structured handoff to broader teams, and ongoing monitoring with defined success metrics.
Hewitt uses his own content marketing pipeline as a running concrete example throughout — showing how he wired AI-assisted ideation and writing into a system fed by actual Slack messages, Notion transcripts, podcast recordings, and years of historical posts — rather than presenting the framework in abstract terms. The video is aimed at founders and business leaders who want to move past demos and into AI that delivers measurable operational results.
📺 Source: Craig Hewitt · Published June 24, 2026
🏷️ Format: Opinion Editorial
