Session details: David Priev presents the AI Machinist on September 14 at 1:15 P.M. in IMTS08 Room W192-B.
- Fragmented workflows: CNC programming, inspection, and manufacturability analysis remain manual and dependent on scarce expertise, while CAM, CMM, and DFM operate in silos.
- System scope: The AI Machinist generates machining strategies and tool paths in CAM software, creates CMM inspection programs, and evaluates manufacturability upfront.
- Knowledge scaling: The system continuously improves from every interaction, capturing and scaling expert knowledge across teams.
- Manufacturing direction: A unified, AI-driven production floor reduces programming time, improves consistency, and unlocks a path to autonomous manufacturing.
Published August 27, 2026
Fragmented production work
CNC programming, inspection, and manufacturability analysis are fragmented, manual, and dependent on scarce expertise. CAM, CMM, and DFM workflows operate in silos, slowing production and limiting scalability. For manufacturers trying to move faster without adding risk, that separation remains the constraint.
The session is scheduled for September 14 at 1:15 P.M. in IMTS08 Room W192-B.
A system across the workflow
David Priev, CEO of LimitlessCNC, introduces the AI Machinist as an intelligent system that works across the entire production workflow. It generates machining strategies and tool paths in CAM software, creates CMM inspection programs, and evaluates manufacturability upfront.
Just as important, the AI Machinist continuously improves from every interaction, capturing and scaling expert knowledge across teams. That points to a shift from isolated automation steps toward a production environment where programming, inspection, and manufacturability analysis inform one another.
Presenter background
David Priev is the CEO and co-founder of LimitlessCNC. He is a mechanical engineer with many years of experience in complex production sites.
Why it matters
Leading manufacturers are moving toward a unified, AI-driven production floor. The stated payoff is practical: the AI-driven production floor reduces programming time, improves consistency, and unlocks a path to autonomous manufacturing. The open question is not whether the workflow is fragmented; it is how quickly teams can connect it without losing control of process knowledge.
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