Most enterprises have roadmaps stretching 3-5 years out. What if you could compress that to 1-2 years?

Brian Elliot is the Co-Founder and CEO of Blitzy, an enterprise-focused autonomous software development platform tackling one of technology's toughest problems: how do you modernize 20-100 million lines of legacy code when the developers who wrote it retired 15 years ago?

In this episode, Brian explores:

Why orchestrated AI agents can handle 80% of transformation work autonomously (and why humans still matter for the other 20%)
The realities of enterprise buying cycles and why embedded on-site teams accelerate change management
Why documentation and test coverage are the unsexy first steps that make everything else possible

About the Guest:
Brian Elliott is CEO and Co-founder of Blitzy. A serial entrepreneur, former Infantry Officer with the 1st Ranger Battalion, and West Point graduate in Systems Engineering with a Harvard MBA, Brian brings a unique blend of military precision, engineering expertise, and entrepreneurial vision to transforming enterprise software development.

As CEO, Brian leads Blitzy's mission to empower systematic AI adoption across enterprises, transforming traditional development lifecycles into AI-native workflows. Under his leadership, Blitzy has developed an agentic platform where thousands of specialized AI Agents cooperate at inference to autonomously deliver enterprise-scale code that is tested, validated, and compiled.

Focused on operational deployment at scale, Brian architected the company's proven Agentic SDLC Accelerator—a structured methodology that systematically guides engineering organizations from technical validation to full-scale enterprise adoption. This framework unlocks autonomous capabilities across the complete software development lifecycle.

Timestamps:
01:25 – Understanding Blitzy's AI Capabilities
03:25 – Challenges and Solutions in Enterprise Software
06:00 – The Genesis of Blitzy
07:30 – Insights from Nvidia and AI Development
11:00 – Implementing AI in Enterprise Systems
18:00 – Change Management and Customer Collaboration
20:30 – Understanding Enterprise Security Needs
25:10 – Improving Code Quality and Test Coverage
28:15 – Blitzy's Mission and Market Direction
30:10 – Challenges and Opportunities in Enterprise Software

Guest Highlight:
"Code is beautiful in that it's verifiable. We're following enterprise best practices—everything goes to a dev branch where a human can look at it, review it, go through a typical QA process. The first thing we're gonna do is document their code so they know what's going on, then add test cases, then develop software at scale that's highly verifiable."

Get Connected:

Hungry for more tech talk? Check out past episodes at ciopod.com:

Ep 62 - Running IT Like a Growth Engine
Ep 61 - What Manufacturing Can Teach You About Scaling Enterprise AI
Ep 60 - Why the Smartest CIOs Are Becoming Business Strategists

Learn more about Caspian Studios: caspianstudios.com

Our Sponsor:
This episode is brought to you by Blitzy, the Enterprise Autonomous Software Development Platform with Infinite Code Context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale codebases with millions of lines of code.

Enterprise Engineering leaders start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-compiles code for each task. Blitzy delivers 80%+ of the development work autonomously, while providing a guide for the final 20% of human development work required to complete the sprint.

Public companies are achieving a 5x engineering velocity increase when incorporating Blitzy as their Pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI-Native SDLC into their org.

Visit Blitzy.com and press book demo to learn how Blitzy transforms your SDLC from AI Assisted to AI Native.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.