In this episode of "Full Tech Ahead," host Amanda Razani interviews Max Reele, VP of Delivery at Rise8. They discuss outcome-driven software delivery in high-compliance sectors, specifically focusing on defense tech and gov tech. 

Reele outlines that while AI and agentic assistance allow engineering teams to deliver a much higher quantity of code, the ultimate focus must remain heavily on quality and mission outcomes. 

Drawing from his 20 years of government experience, he warns against common tech project failure modes, such as the "Big Bang" release theory—attempting a hard cutover to completely replace a massive legacy system all at once. 

To combat this and prevent deepening organizational silos, Rise8 advocates for rigorous corporate upskilling, working backward from strict mission metrics, and conducting biweekly demos of working software. 

Furthermore, Reele champions "Extreme Programming" and engineering pairing to safely ground AI agents and prevent codebase hallucinations.

Key Quotes

"At Rise8, we're defense tech and gov tech focused... we build mission unique software for any mission... specifically in high compliance industries."

"Whether it was all hands on keyboard developing the code, or whether it was assisted with Agentic development, the outcome still needs to be the outcome."

"Everybody can become builders with agentic assistance in your development effort, but not everybody's really great builders. And it takes the seasoned software engineers to understand how to interact with the AI agents."

"Please just stay focused on the mission you're trying to improve and let the business operations follow."

Takeaways

Implement "Extreme Programming" with AI: AI agents are flooding codebases with volume, but they can hallucinate or even falsify data to artificially pass test cases. Organizations must pair seasoned, senior engineers with junior developers to continuously audit, test, and safely prompt AI agents, keeping code reliable.

Reject the "Big Bang" Release Trap: Attempting a sudden, full-scale replacement of a massive legacy operating system of record causes immense friction, timeline overruns, and project cancellations. Instead, break modernization efforts down into small, digestible bites and integrate users gradually throughout the journey.

Enforce Biweekly Software Demos: The ease of localized AI tooling risks driving engineers into deeper silos. To force collaboration and structural alignment, teams must pull their features, security hygiene, and technical debt together into a coherent, working software demo presented to primary stakeholders every two weeks.

Encourage Engineering Enablement: Business leaders must shift their mindsets regarding workforce upskilling. When an engineer raises their hand to ask for deeper training on how to handle AI agents safely in mundane functions, it should be viewed as a professional strength, not an operational flaw.

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