The Enterprise AI Show

SUMMARY: As tools like Mythos create new AI-cybersecurity concerns, CIOs and CISOs need to be prepared for two challenges: Security Remediation and Patch to Production acceleration. 
SHOW: 1037
SHOW TRANSCRIPT: The Enterprise AI Show #1037 Transcript
SHOW VIDEO: https://youtu.be/H5KxoiEIfUo
SHOW SPONSORS:
Nasuni - Activate your data for AI and request a demo
OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architecture
ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
SHOW NOTES:
Project Lightwell (Red Hat and IBM)
Athena (Chainguard)
Anthropic Project Glasswing
OpenAI GPT 5.5-Cyber
THESIS: Major initiatives are forming to help enterprise organizations combat security vulnerability threats found or created using new AI-cyber tools such as Anthropic Mythos. What are the key considerations, and what additional steps do organizations need to take to be advantaged by these capabilities? 
Part 1
The Breaking Point and the Mythos Moment
The scope of open source security and support
Patches, disclosures and upstream open source
Clearinghouses, EOs, Laws and Communities
Remediation - Build vs. Buy
Part 2
How fast can you get from Patch to Production?
Mitigation before patching
Fast path and stable patch pipelines?
Automation in patching vs. automation in deployment
FEEDBACK?
Email: show @ the enterprise ai show dot come
Bluesky: @TheEntAIShow.bsky.social
Twitter/X: @TheEntAIShow
Instagram: @TheEntAIShow

SUMMARY: How can CIOs balance innovation and control as they roll our AI capabilities across their organization. How can they balance onboarding, experience, security and flexibility? 
SHOW: 1036
SHOW TRANSCRIPT: The Enterprise AI Show #1036 Transcript
SHOW VIDEO: https://youtu.be/ZgkMF7G3Yfo
SHOW SPONSORS:
OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architecture
ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
Nasuni - Activate your data for AI and request a demo
SHOW NOTES:
Andy Weir (The Martian) on Eps. 193
Systems of Record Won the SaaS Era - Clearinghouses Will Win the Agents Era
Harness Engineering is where Enterprise AI becomes real

THESIS: It comes up as different control points, but CIOs are ultimately trying to figure out how to get the value from Enterprise AI while delivering a set of consistency across different teams and use-cases. Let’s explore what this “Enterprise Harness” is starting to look like. 
Enterprise Clearinghouse 
Enterprise Intelligence (a.k.a. Middleware)
Enterprise Catalog - Models as a Service, Agents as a Service
Enterprise Skills or Shareable Prompt Harnesses
Symantec Routing to Models
AI Gateway Controls
FEEDBACK?
Email: show @ the enterprise ai show dot come
Bluesky: @TheEntAIShow.bsky.social
Twitter/X: @TheEntAIShow
Instagram: @TheEntAIShow

SUMMARY: If the cost of public AI continues to rise, because of various market shortages, should CIOs start looking at backup plans to better own their AI journeys and futures?
SHOW: 1035
SHOW TRANSCRIPT: The Enterprise AI Show #1035 Transcript
SHOW VIDEO: https://youtu.be/ngBBpP2Lgdo
SHOW SPONSORS:
ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
Nasuni - Activate your data for AI and request a demo
OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architecture
SHOW NOTES:
THESIS: Between pending IPOs (Wall St. demands), high user-demand, GPU/TPU shortages, Data Center shortages, Model prices increasing (open models fading away), the cost of using AI is going to get more expensive over time. Should CIOs start thinking about a Backup plan to their current AI adoption that has lower cost alternatives?

Topic 1 - Assuming you could get access to GPUs/TPUs/Accelerators, and suitable data center space to host them, what would be your thinking as a CIO if you felt like you needed to own some aspect of your AI roadmap/journey? 
Topic 2 - Assuming the normal “Shadow AI” backlash that you’d receive for offering something that wasn’t “frontier” level, how would you go about trying to communicate that within your organization?
Topic 3 - What metrics or KPIs would you initially target to try and get buy-in that your approach was acceptable and moving towards the company goals?

FEEDBACK?
Email: show @ the enterprise ai show dot come
Bluesky: @TheEntAIShow.bsky.social
Twitter/X: @TheEntAIShow
Instagram: @TheEntAIShow

SUMMARY: When we get to the end of 2026, how will enterprise companies be measuring the success of their AI projects? And how well will their teams be sharing their AI learning curves?
SHOW: 1034
SHOW TRANSCRIPT: The Enterprise AI Show #1034 Transcript
SHOW VIDEO: https://youtu.be/TvIFwNN-6ck
SHOW SPONSORS:
Nasuni - Activate your data for AI and request a demo
OutShift - “Scaling Out Superintelligence”  The Internet of Cognition architecture
ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
SHOW NOTES:
Why AI Economics are changing
How will team collaboration evolve with Enterprise AI?

Topic 1 - How do we measure AI-adoption success? 
Number of workloads?
Financial metrics (Spend, ROI, Costs-Saved, etc.)?
Speed improvements?
People-level?
Topic 2 Right now the AI tools are very individual-centric 
The machinery to share, even at the basic enterprise-level, is very difficult
The experience to share is non-deterministic, just as everyone’s working style is different.
Topic 3 - The motivation to share is still unknown. 
How do you encourage collaboration when so many companies are laying off people, or the specter of that happening is growing?
What was the motivation before (team goals?) and how does that change now? 
People don’t want to be monitored, so how does a manager have visibility?
What happens when companies remove the managers (“the counters”)? 
FEEDBACK?
Email: show @ the enterprise ai show dot come
Bluesky: @TheEntAIShow.bsky.social
Twitter/X: @TheEntAIShow
Instagram: @TheEntAIShow

SUMMARY: After the first successful AI IPO of 2026, we dig into what makes the Cerebras WSE architecture unique in the market for fast inference. 
GUEST: Andy Hock, Chief Strategy Officer at Cerebras AI
SHOW: 1033
SHOW TRANSCRIPT: The Enterprise AI Show #1033 Transcript
SHOW VIDEO: https://youtu.be/ed2nVbOtZiA
SHOW SPONSORS:
OutShift - “Scaling Out Superintelligence”  The Internet of Cognition architecture
ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
Nasuni - Activate your data for AI and request a demo
SHOW NOTES:
OpenAI announces 750MW partnership with Cerebras
Cerebras and AWS partnership
Cerebras announces IPO

Topic 1 - Welcome to the show. Tell us about your background, and what you focus on today. 
Topic 2 - For anyone that’s not familiar with Cerebras, give us an overview of the company, and especially an overview on the Cerebras technologies (e.g. Wafer-Scale Engine).
Topic 3 - Cerebras’ WSE architecture is different from many of the GPU or GPU-like architectures in the market today. Centralized vs. distributed architectures always have their tradeoffs. Walk us through the technical and economic value of the Cerebras architecture.
Topic 4 - Congratulations on the recent IPO (raised $5.55B). Let’s use that as a point in time vs the previous planned IPO. How has the market changed in that timeframe, and how has the Cerebras position changed? 
Topic 5 - Cerebras (today) offer both WSE hardware, and Cerebras Cloud (API) - very different GTM paths. Can we expect both of those to stay top priorities, or have the market dynamics shifted such that the priorities shift more towards the WSE business - as we’re seeing OpenAI, AWS and other engagements announced?
Topic 6 - Is Cerebras a training and inference company, or are the economics of inference significantly different enough that it needs to be the sole focus of the company (for now)? 
Topic 7 - How much effort is it for any company to add support for the Cerebras chips if they have previously been using other architectures?
Topic 8 - An IPO is a major milestone for any company, but the markets will now look for your future story. How do you see the AI market evolving over the next 2-5 years, and what are some things that people aren’t understanding yet about how it will evolve?

FEEDBACK?
Email: show @ the enterprise ai show dot come
Bluesky: @TheEntAIShow.bsky.social
Twitter/X: @TheEntAIShow
Instagram: @TheEntAIShow