I’m Mitch, making AI a first-class participant in how we ship software.
2026 – present
The AI-Era SDLC
My current chapter is a three-person tiger team, chartered by senior leadership, with a deceptively large question: how does agentic AI reshape the software development lifecycle, and what do we build so the answer becomes practice instead of a slide? In practice that’s a harness, a context substrate, and the workflows that connect them, now serving a cohort of around 45 engineers and feeding the enterprise AI strategy.
Two convictions drive most of it. The first is that an agent is a model plus a harness (the guides, hooks, skills, tests, reviews, and judges around the model), and the harness is where the real engineering lives. Hooks always execute; instructions only get interpreted, so anything that has to hold gets enforced deterministically rather than left to a model’s discretion. The second is that context, not the model, is the load-bearing layer of agentic delivery. Karpathy’s writing on LLM wikis matched what I keep seeing in practice: AI output improves dramatically the moment an agent can reach the “pet knowledge” a team usually keeps in human heads.
And the throughline underneath all of it is a refusal to run on vibes. “AI made me 3x faster” is an anecdote, not a measurement. The interesting work is turning that into something falsifiable: replacing how it felt with evidence you could be proven wrong about.
2019 – 2026
From APIs to Enterprise Platforms
2019 – 2021 · John Deere Financial
I started at John Deere Financial during an early attempt to make APIs safely available to dealer software. The ambition resembled what a product such as Azure API Management provides: a common gateway for governing and exposing APIs instead of another one-off integration. I helped architect the platform’s first external-facing API for dealer access to sales-lead data, with role-based authorization and audit logging designed in from the beginning. That early platform later matured into the JDF API Gateway used for both internal and external APIs.
2021 – 2023 · ISG Digital
I then moved closer to the technology on John Deere machinery within the Intelligent Solutions Group’s digital organization. On License Management, I worked behind the customer experience for purchasing digital capabilities on equipment—for example, enabling a combine to use See & Spray. A secure data-ingestion prototype I built during a hackathon showed that license data could be made useful to internal teams without giving up isolation or access controls, and helped make the case for a dedicated enterprise Data Engineering team.
2023 – 2025 · Enterprise Cloud Foundations
The next chapter moved from individual products to infrastructure used across the enterprise. The Landing Zone team began within Infrastructure and Operations in Global IT, serving engineering teams across John Deere, before moving into the broader enterprise platform organization. I led a network consolidation across about 2,000 VPCs that removed seven figures of annual cloud spend, orchestrated a DNS migration that remediated 140,000+ security vulnerabilities at 100% uptime through the cutover, automated certificate renewal, and turned account and VPC deletion from a manual, hour-long procedure into an event-driven workflow measured in seconds.
2025 – 2026 · Developer Experience
Within that enterprise platform organization, I moved to the Developer Experience product responsible for the path from pull request to production. I worked on governance, automation, and incident response across more than 50,000 repositories, including an event-driven separation-of-duties platform that cut audit preparation by roughly three-quarters, shared delivery workflows, and diagnostics that reduced production investigation from hours to minutes.
The throughline across those chapters is the same instinct that now shapes my AI work: make the hard, important thing also the easy, default thing. Secure access that does not need to be reinvented. Compliance that does not depend on an engineer remembering it. Renewals that do not need a human in the loop. Onboarding that goes from hours to minutes.
I’m not interested in pulling humans out of the loop. The target is complementarity: higher confidence, higher quality, lower cognitive load on the person doing the work.
That was true when the output was a pipeline nobody had to think about. It’s just as true now that the output is an agent.
Credentials
- B.S. Software Engineering, Iowa State University (Cum Laude, 2020). Cyber security minor.
- AWS Certified DevOps Engineer – Professional · May 2026
- AWS Certified Advanced Networking – Specialty · Aug 2025
- AWS Certified SysOps Administrator – Associate · Feb 2025
- AWS Certified Solutions Architect – Associate · Mar 2024
- AWS Certified Cloud Practitioner – Foundational · Nov 2021
Skills
Colophon
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