The Deep View: Conversations

Coding agents can drastically accelerate how fast developers build, but defaulting to the most powerful models gets expensive fast. But what if your coding assistant could route to less expensive models when they don't need high-end frontier intelligence?
In this episode of The Deep View Conversations, we sit down with Kyle Daigle, GitHub’s chief operating officer, at GitHub Universe in San Francisco to explore how the company's new Copilot Fusion can route between models and reduce token costs.
Daigle explains how Fusion can start with a less expensive model, move to a more capable one when needed, and bring in a second model to check the first model’s work. He says GitHub’s teams and early enterprise customers are seeing 50% to 60% lower costs on complex work, with savings reaching 77% for certain workloads. But most importantly, it's getting results that match using high-end models while doing it about 40% faster. 
Other topics covered:
• Why people outside traditional developer roles are building their own software
• How GitHub’s marketing and design teams use Copilot to create tools for their own work
• How Fusion’s Cascade and Critique approaches coordinate models within a task
• Choosing between Fusion Standard, High, and Max based on the work you need done
• GitHub’s plans to route some tasks to local models running on your computer
• How Copilot Projects brings repositories, files, and agents together in one workflow
If you’re building with AI coding agents, leading a development team, or managing your company’s AI budget, this conversation offers a way to control costs while keeping the capabilities 
Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ 
And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

The AI agents helping employees work faster also open up new risks for a company's most sensitive data. So how do businesses keep up with the opportunities and the risks?
In this episode of The Deep View Conversations, we sit down with Cristian Rodriguez, CrowdStrike's field CTO for the Americas. We talked to Rodriguez at CrowdStrike's Fal.Con 2026 event to explore what one of the world's largest cybersecurity companies is learning about how AI is rapidly changing the cybersecurity landscape.
 
Rodriguez explains why defenders need to respond at machine speed, what the OpenAI and Hugging Face incident reveals about goal-seeking agents, and why even useful AI tools need visibility, boundaries, and accountability. Rodriguez argues that data governance remains a central challenge: companies need to understand what their agents can access, where information moves and who is responsible for each action.
Topics covered:
• Helping healthcare, government and other understaffed organizations respond to faster attacks 
• Whether automation and tool consolidation can strengthen security within existing budgets 
• SafeMind, red and blue cybersecurity models, and the role of the AI harness 
• Bring-your-own-model options and where CrowdStrike's models run 
• Moving from reactive incident response toward proactive security with human oversight 
• How Rodriguez uses Slackbot to organize his day and follow through on commitments 
If you're leading an organization, putting agents to work, or trying to understand how AI changes the security and safety landscape, this conversation connects the new capabilities with the controls and judgment needed to manage them.
Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ 
And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

Your next big AI win may come from someone your leadership team would never think to pick.
In this episode of The Deep View Conversations, we sit down with Todd Earwood, CEO of Betra Works and an AI investor at HalfCourt Ventures, to explore what it takes to deploy AI for useful work inside organizations.
 
Drawing on his work with 1,200 leaders and executives, Todd explains why the people closest to the work often see AI opportunities that executives miss. He shares how a university athletics sales rep used AI to uncover new ticket buyers, how a warehouse employee helped a manufacturer rethink a 22-year-old spreadsheet, and why a skeptical, experienced employee became an unexpected AI champion.
We also discuss Todd's book, Adapt & Adopt, and his approach to teaching people how to identify useful AI tasks, evaluate opportunities, and build momentum from individual wins to broader adoption.
Other topics covered:
• Three paths to putting AI to work in a business
• Why employee frustrations can reveal valuable AI opportunities
• The gap between personal AI use and workplace adoption
• What Todd learned from investing in more than 100 AI companies
• Building a tech career outside San Francisco and New York
• Why meeting recorders and voice dictation can make an immediate difference
• Using Claude to protect your calendar and priorities
If you're leading a team, trying to make AI useful in your own job, or deciding where to start, this conversation offers practical ways to connect AI's capabilities with the work people do every day.
Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ 
And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com
TIMELINE
0:00 Introduction
2:27 From AI investing to real-world adoption
7:19 Three paths to making AI useful
10:16 Adapt & Adopt: learning how to think
16:34 Unexpected AI wins in sales and manufacturing
21:14 Finding AI opportunities in the work you hate
23:45 Why your AI champions may surprise you
27:02 Investing in AI before the boom
33:49 Building a tech career beyond the coastal hubs
40:44 Meeting recorders, Wispr Flow and everyday AI
45:24 Using AI to protect your time
48:58 Closing advice: slow down when life gets hard

AI is making it easier for employees to work beyond their specialties and that has big implications for the future organizations of all sizes. 
In this episode of The Deep View Conversations, we sit down with Bill Barton, chief operating officer at Rokt and the former leader of the Alexa team at Amazon. Rokt has gotten called out by some of the biggest tech companies in the world for its innovative use of AI inside the company. 
In fact, several of them have had Rokt come and talk to their teams about how they do it. So we wanted to have Bill on the show to share those insights with a larger audience.
Barton shares how Rokt is using an internal AI fleet across software development, finance, legal, security and other functions. He explains how AI is helping blur the boundaries between roles, why the company has moved from more than a dozen job ladders to four, and what it takes to turn experimentation into everyday practice.
Other topics covered include:
• Why Bill returned to Rokt after trying retirement
• How AI is expanding the reach of generalists
• Enabling shared AI experimentation companywide
• Why fewer, more flexible systems can help teams move faster
• How Barton thinks about productivity gains and hiring
• What Google search reveals about frictionless AI
• Why more powerful tools can make it harder to step away from work
Bill also shares his six timeless attributes that can help anyone succeed in the AI era: relentlessness, resilience, rigorousness, inquisitiveness, optimism and humility.
For leaders rethinking their teams and professionals navigating changing roles, this conversation connects the possibilities of AI with the habits and judgment needed to make them useful.
Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ 
And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com

Companies want to own the intelligence that makes their business valuable. So what will that mean for the AI models they use, and the systems they build around them?
In this episode of The Deep View Conversations, we sit down with Justin Boitano, VP of enterprise AI at Nvidia, to explore why NVIDIA is investing in open models and how enterprises are turning them into specialized intelligence.
 
Boitano talks about why NVIDIA makes Nemotron's datasets, training techniques and model weights openly available, how proprietary business knowledge can become a competitive advantage, and why lower token costs can unlock much greater demand for AI.
The conversation also examines why the agent harness that manages tools, memory and execution can matter as much as the model itself. Boitano shares how Nvidia worked with CrowdStrike on AI models for cybersecurity, why AI incidents need the equivalent of an aviation flight recorder, and how OpenShell moves agent controls into the infrastructure layer.
Other topics covered:
• Why NVIDIA is building open models alongside its chip business
• What Nemotron needs to compete with China's open models
• Owning institutional knowledge, protecting data and controlling AI costs
• How model development helps NVIDIA improve hardware efficiency
• Why harness engineering is becoming a new frontier for AI
• Moving cybersecurity from finding bugs to verifying and fixing them
• Transparency and learning from AI incidents
• OpenShell, sandboxing and enforceable limits on agent access
• How Justin uses Hermes as an AI chief of staff
• Jensen Huang's approach to priorities and team alignment
If you're deciding how to build enterprise AI, where your company's competitive advantage comes from, or how to give agents useful access without giving them unlimited control, this conversation offers a perspective from Nvidia's work across the ecosystem.
Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: https://tdv.transistor.fm/ 
And don't forget to sign up for The Deep View daily newsletter. We don’t just cover AI, we decode it. In a world flooded with hype, we deliver sharp, no-nonsense insights to keep you ahead of the curve and help you put AI to work every day: subscribe.thedeepview.com