09/04/2026
“It’s really a needle in a mountain of needles and you just want to find one.”
For most manufacturers, the hard part of AI isn’t the model — it’s the knowledge locked in the heads of veteran engineers. In this special Automate 2026 episode of Manufacturing Matters, TECH B2B Marketing’s Jimmy Carroll sits down with ReshapeX’s co-founder and CEO Juan Aparicio and Novanta’s Ajay Sharma (ATI Industrial Automation) for a candid case study of how the two companies turned decades of tribal knowledge into a working AI agent.
Novanta’s ATI tool changers can be configured millions of ways — the team pegs a single product line at roughly 7 million combinations — and pinpointing the one right configuration used to take days of back-and-forth with application engineers. Sharma and Aparicio walk through how they codified that expertise into an “agentic application engineer” that returns the right answer in minutes, why they set out to be the 5% of enterprise AI projects that succeed rather than the 95% that fail, and the build-versus-buy calculus that led Novanta to partner with ReshapeX.
The conversation digs into the unglamorous work behind a reliable agent: gamified, week-over-week testing with real customer queries, a human-in-the-loop feedback loop that moves the system from probabilistic to deterministic, a knowledge graph that reasons on relationships instead of semantics to reach 99.99% precision, and continuous evals to guard against model drift. They close with a playbook for other manufacturers — define the real problem, secure executive cover, get your solution fit right, and treat it like a high-risk project — plus why codifying knowledge before it walks out the door may be the most important thing an established company can do.
Link to the full episode in the comments.