Abundant Intelligence at the Midwest AI Summit
In this special episode, host Daniel Whitenack shares highlights from three keynote sessions at the second annual Midwest AI Summit. Heidi Porter outlines the structural components required to build durable AI workflows with guardrails and evals, Kevin Solorio explains how to build AI with frontline workers to secure adoption, and Chris Shinkle and Andrew Dunlap from SEP present a Lean-inspired decision framework for calibrating AI autonomy in software development teams.
- In an industrial hose manufacturing plant, engineers separated defect detection from text generation: computer vision and graph databases detect the flaws, while the language model only drafts explanations subject to deterministic guardrails. Read →
- Enterprise AI pilots usually stall between prototype and production because teams force large language models to perform steps that deterministic software should handle. Read →
- Deploying an AI agent onto enterprise cloud infrastructure does not make it production-ready. Without structured evaluation benchmarks, Kevin Solorio argues that any deployed system remains an unverified proof of concept. Read →
- Chris Shinkle warns against chasing the dark factory fantasy, where autonomous agents write, test, review, and deploy code without human engineers touching the keyboard. Read →
- Software teams do not need a fully automated dark factory to benefit from AI; Lean manufacturing demonstrates that core principles hold true across environments while practices must shift based on constraints. Read →