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
• Instagram: @TheEntAIShow

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?

• Email: show @ the enterprise ai show dot come
• Bluesky: @TheEntAIShow.bsky.social
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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?

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