SUMMARY:  Brian Gracely (@bgracely) and Aron Delp (@aarondelp) discuss the biggest AI news stories from the month of June, 2026. 

SHOW: 1041

SHOW TRANSCRIPT: The Enterprise AI Show #1041 Transcript

SHOW VIDEO: https://youtu.be/SXmPOgE5jGk

SHOW SPONSORS:

• Nasuni - Activate your data for AI and request a demo
• ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

SHOW NOTES:

• Links to all the AI News covered in this month’s show

FEEDBACK?

• Email: show @ the enterprise ai show dot come
• Bluesky: @TheEntAIShow.bsky.social
• Twitter/X: @TheEntAIShow
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SUMMARY: As AI within the Enterprise matures, we look at 10 concerns and challenges that are still causing Chief AI Officers to worry about success in the future. 

SHOW: 1040

SHOW TRANSCRIPT: The Enterprise AI Show #1040 Transcript

SHOW VIDEO: https://youtu.be/RyB4m17YK_4

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:

THESIS: After spending time with a number of Enterprise companies, what are a list of challenges and concerns they still have in implementing GenAI across a broad set of use-cases within the Financial Services industry?

1. Everybody started with what was available (e.g. CoPilot)
2. Enterprise implementations (now) aren’t autonomous
3. Rising costs are the looming concern
4. Governance is a rising concern
5. Measurements of improvement are available, but varied
6. Explaining measurements is complicated
7. Explaining trust is more complicated
8. Use-cases are fragmented, but there if you apply the technology, but not always obvious
9. De-centralized (shadow AI) to Centralized to De-centralized (semi-controlled) 
10. The learning curves are very asymmetrical across teams
11. Not everyone has access to Mythos or GPT-5.5-Cyber (yet)

FEEDBACK?

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SUMMARY: What does a Forward-Deployed Engineer actually do? And what about deploying AI Harness? Let’s dig into the real-world with these evolving AI concepts and technologies. 

SHOW: 1039

SHOW TRANSCRIPT: The Enterprise AI Show #1039 Transcript

SHOW VIDEO: https://youtu.be/QY0fqu2O84M

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:

• Mozilla Thunderbolt launched 
• Mozilla Thunderbolt (homepage)

Topic 1 - Welcome to the show, tell us a bit about your background and what you focus on these days.

Topic 2 - Let’s talk about the role of Forward Deployed Engineer, it’s being talked about a lot, but you’re living in that world now. What problems are FDEs usually tasked with trying to solve, or new things to implement?

Topic 3 - We’ve seen other roles (DevOps, PlatformEng, etc.) that evolved from other roles or skills. What type of background lends itself to success in FDE? What skills are needed going forward?

Topic 4 - You’re also working on some AI harness implementations. What can you tell us about those challenges and the technologies behind the harness?

Topic 5 - At what point does an AI harness make sense for a company? What types of AI challenges typically require those next steps? 

Topic 6 - Working in the middle of this evolving AI space, what are some perspectives you’ve gained over the last 6-12 months? What do you wish you knew ahead of time? 

FEEDBACK?

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SUMMARY: On Father's Day, how would you explain some of the volatility of the AI market to your father? What advice might he give you to navigate the ups and downs and uncertainties?

SHOW: 1038

SHOW TRANSCRIPT: The Enterprise AI Show #1038 Transcript

SHOW VIDEO: https://youtu.be/T2ZIYLpl_cE

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:

• Leaked documents show OpenAI is losing billions
• Anthropic’s Fable and Mythos models banned from non-US foreign nationals
• The AI layoff wave is becoming a powder keg
• Professors says AI-related job losses are inevitable

THESIS: On this Father’s Day, with an AI market that often times doesn’t make any sense, I thought about the type of advice that my father gave me over the years and how it would apply to this time of significant change.  

• Show up, keep up and shut up
• Make yourself invaluable
• Focus on what you can control
• Be an expert in something
• When in doubt, get closer to people and how money is made
• When things don’t make sense, focus on fundamentals
• Markets can be irrational way longer than you can be solvent
• Try and think a couple steps ahead

FEEDBACK?

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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?

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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?

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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?

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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?

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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
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SUMMARY: The biggest enterprise AI question is which organization can most effectively operationalize, govern, and economically scale AI agents across the business.

SHOW: 1032

SHOW TRANSCRIPT: The Enterprise AI Show #1032 Transcript

SHOW VIDEO: https://youtu.be/GsK_RUnYroI

SHOW SPONSORS:

• ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.
• Nasuni - Activate your data for AI and request a demo

SHOW NOTES:

Opening Thesis - How will team collaboration evolve within Enterprise AI?

Question: Any suggestions on how to introduce enterprise-level governance and standardisation for agentic coding? Like skills, rules, plugins, context etc

Key Topics 

1. This isn’t a Coding-specific problem. Every team has this issue. 

• If your processes weren’t well defined and enforced before, they will be worse now
• Not it’s not just process standardization, but “buy-in” standardization

2. Everything moves so fast, so managers don’t have the answers (yet) 

• AI value is being created bottom-up, but paid for (and mandated) top-down
• The current measurements aren’t useful (tokenmaxxing, all-or-nothing, etc.)

3. The governance tools don’t exist yet.

• And it’s not clear that anyone wants them. They didn’t want them before. 
• How do you even define governance? What’s the baby step before that, reuse and basic sharing? 

4. Are we ready to invest in “Centers of Excellence” again? 

5. We under-estimate the “creativity” element in human buy-in. 

• Is success measured in improvement or replacement?
• How much of that did “you” do? We don’t know how to measure that.
• We haven’t lived through an AI-centric promotion cycle yet

6. Bottom-up and Top-down need to find some common language and middle ground. 

• Have they walked a mile in each other’s shoes yet (or lately)?
• How to bring a reality to the hype vs. demands vs. learning curve?
• How long is an AI-centric cycle vs. a pre-AI-centric cycle? 

FEEDBACK?

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SUMMARY:  Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of May, 2026. 

SHOW: 1031

SHOW TRANSCRIPT: The Reasoning Show #1031 Transcript

SHOW VIDEO: https://youtu.be/MNihDdBSteI

SHOW SPONSORS:

• Nasuni - Activate your data for AI and request a demo
• ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!

SHOW NOTES:

• Links to all the AI News covered in this month’s show

FEEDBACK?

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