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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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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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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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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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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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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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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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?

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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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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
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SHOW: 1030

SHOW TRANSCRIPT: The Enterprise AI Show #1030 Transcript

SHOW VIDEO: https://youtu.be/acOBfRI0P3U

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 - Was the first wave of AI adoption artificially cheap? - The industry may be transitioning from subsidized growth to usage-based economics. 

Key Topics 

1. Evidence AI Was Subsidized 

• Massive CAPEX vs low end-user pricing 
• Generous enterprise bundles 
• Frontier model access for $20/month 

2. The Hidden Economics of AI Agents - 

• Agents consume exponentially more inference 
• Tool orchestration, retries, memory, verification 

3. Why Frontier Labs Are Shifting Focus 

• From benchmark supremacy to orchestration 
• Governance, memory, connectors, MCP, workflows 

4. Forecasting AI Pricing 

• 12 Months:  
  • Commodity inference gets cheaper - 
  • Frontier reasoning remains premium 
• 24 Months:  
  • AI billing resembles AWS-style infrastructure billing 
  • Runtime, memory, latency and orchestration become billable 
• 36 Months: 
  • Outcome-based pricing emerges 
  • AI spending shifts from IT budgets to labor budgets Final Takeaways  
  • Commodity AI becomes utility-priced 
  • Frontier reasoning becomes premium 
  • Agents reshape enterprise economics

Key Conclusions

1. AI probably was subsidized
The economics strongly suggest adoption-first pricing.

2. The subsidy era may be ending
Premium tiers and metered pricing are emerging.

3. AI agents fundamentally alter economics
Usage scales exponentially with autonomy.

4. Commodity AI and frontier reasoning are separating
One becomes cheap.
One becomes premium.

5. The real battle is moving upward in the stack
The future moat may be:

• orchestration
• governance
• workflows
• enterprise context
• operational tooling

Final Closing Thought
“The biggest enterprise AI question may no longer be:
‘Which model is smartest?’

Instead:
‘Which organization can most effectively operationalize, govern, and economically scale AI agents across the business?’”

FEEDBACK?

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GUEST:  Ram Venkatesh, Co-Founder/CTO of Sema4.ai

SHOW: 1029

SHOW TRANSCRIPT: The Enterprise AI Show #1029 Transcript

SHOW VIDEO: https://youtu.be/Lc3XS44Ixg4

SHOW SPONSORS:

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

SHOW NOTES:

Topic 1 - Welcome to the show. Tell us about your background, and what led you to create Sema4.ai?. 

Topic 2 - AI Agents vs. Automation 2.0. What Actually Changed. Tell us about the Sema4.ai platform and capabilities. What challenges does it solve today?

Topic 3 - You’re initially focused on solving challenges for the CFO, which means there is a ROI-focus all the time. Why did you target that segment of the business first?

Topic 3a - What are the biggest hidden costs in enterprise AI deployments today?

Topic 4 - Sema4.ai emphasizes “your LLM, your VPC, your data.”  What are the biggest considerations for companies looking to create these private/sovereign AI solutions? What typically gets overlooked?

Topic 5 - How do you tend to frame the conversation about AI trustworthiness, and the role of humans vs. agents for enterprise work? 

Topic 6 - It feels like so much has changed or evolved with AI in the last 2-3 years. How does an Enterprise think about this much change for something that will be core to many critical applications? What will the Enterprise Architecture look like in 2 years?

Topic 7 - Sema4.ai emerged partly from the acquisition of Robocorp and has roots in open-source automation.  Do you have a perspective on the role open-source will play in AI going forward? 

FEEDBACK?

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GUEST: Richard Harbridge, Principal Industry Advisor, Microsoft 365 at ShareGate

SHOW: 1028

SHOW TRANSCRIPT: The Enterprise AI Show #1028 Transcript

SHOW VIDEO: https://youtu.be/sgqg7uqErA0

SHOW SPONSORS:

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

SHOW NOTES:

• Nearly 1 in 3 Organizations Report AI-Driven Data Exposure Incidents
• Other Resources:
  • A complete checklist for Microsoft 365 governance https://sharegate.com/guides/checklist-for-microsoft-365-governance 
  • Request a demo of ShareGate: Get a 1:1 ShareGate demo tailored to your Microsoft 365 use case 
  • Article around that divide of confidence vs reality of data exposure sharegate.com/blog/93-of-it-leaders-are-confident-in-their-ai-governance-but-nearly-1-in-3-report-data-exposure-incidents 
  • The State of Microsoft 365 industry report with more stats and insights - State of Microsoft 365 2025 | Free survey report – ShareGate | Sharegate (new one coming SOON)

Topic 1 - Welcome to the show. Tell us about your background, and what you focus on today. Tell us about Sharegate. 

Topic 2 - How has generative AI changed the definition of “governance” inside Microsoft 365 environments?

Topic 3 - What are organizations underestimating about AI readiness in M365?

Topic 4 - What do you think about “oversharing risk” in the era of AI assistants?

Topic 5 - What patterns are you seeing around shadow AI and unsanctioned SaaS usage?

Topic 6 - How should organizations rethink identity and access management for AI-driven workflows?

Topic 7 - What does good AI governance look like operationally—not just as a policy document?

FEEDBACK?

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SHOW: 1027

SHOW TRANSCRIPT: The Enterprise AI Show #1027 Transcript

SHOW SPONSORS:

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

SHOW NOTES:

• Reviewing the Major AI Vendors 

FEEDBACK?

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GUEST: Wannie Park, Founder/CEO of PADO AI

SHOW: 1026

SHOW TRANSCRIPT: The Reasoning Show #1026 Transcript

SHOW VIDEO: https://youtu.be/satMQRxKQC8

SHOW SPONSORS:

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

SHOW NOTES:

1. AI’s Hidden Constraint: Power

• AI growth is no longer limited only by GPUs and compute
• Power generation, cooling, and grid interconnects are emerging as major bottlenecks
• Data centers could account for 10–12% of North American power demand in coming years

2. Why Data Centers Are Being Reimagined

• Traditional data centers were built for enterprise IT, not AI-scale workloads
• AI infrastructure introduces:
  • Massive power density needs
  • Advanced cooling challenges

3. The Grid Wasn’t Built for AI

• Utilities are designed around peak demand scenarios
• Most grids run well below peak capacity most of the time
• AI workloads create volatile and unpredictable consumption patterns
• Long interconnection timelines are pushing companies toward alternative infrastructure models

4. GPU Utilization Is Surprisingly Low

• GPU clusters are often underutilized because of:
  • Scheduling inefficiencies, Cooling limitations, SLA constraints
  • Effective GPU utilization may be as low as 12–13% in some environments

5. Cooling as a Major Optimization Layer

• Legacy data centers often cool entire zones inefficiently
• Pado AI aligns
• AI workloads, Cooling systems, Power allocation
• Workload-aware orchestration helps optimize cooling and compute efficiency

6. The Rise of “Compute Forecasting”

• Pado forecasts compute demand instead of energy demand
• The platform models:
  • GPU workloads, Power consumption, Cooling requirements, SLA priorities
  • Goal: maximize “compute per megawatt”

7. AI Workloads Become Time-Aware

• AI providers may increasingly:
  • Shift workloads to off-peak periods
  • Incentivize delayed non-urgent jobs
  • Dynamically balance compute demand
  • Users are already seeing variable inference latency in real-world AI systems

8. Sustainability vs Reliability vs Profitability

• Operators must balance:
  • Uptime expectations, Infrastructure costs, Sustainability goals
  • Renewable adoption is growing, but reliability still drives investment in natural gas and battery-backed systems

9. Brownfield vs Greenfield Opportunities

• Pado AI is focused primarily on existing (“brownfield”) data centers
• Existing enterprise infrastructure can often be extended and optimized instead of rebuilt
• Enterprises may gain significant AI capability without hyperscale GPU deployments

FEEDBACK?

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SHOW: 1025

SHOW TRANSCRIPT: The Reasoning Show #1025 Transcript

SHOW VIDEO: https://youtu.be/Gl-49dmAgBs

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 months show

FEEDBACK?

• Email: show @ the enterprise ai show dot come
• Bluesky: @TheEntAIShow.bsky.social
• Twitter/X: @TheEntAIShow
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GUEST: Brandon Whichard, Software Defined Talk

SHOW: 1024

SHOW TRANSCRIPT: The Reasoning Show #1024 Transcript

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

SHOW SPONSORS:

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

SHOW NOTES:

Brian’s Picks

1. Google
2. Major AI-centric IPO in 2026 ($1T valuation)
3. Amazon (cloud)
4. Company has more Agents that Employees
5. TSMC (hardware)
6. AMD (hardware)
7. Family asks about AI at the holidays
8. Data center issue causes a significant change to human existence

Brandon’s Picks

1. Anthropic
2. NVIDIA
3. Broadcom
4. OpenAI (frontier model)
5. AI Consumption-based pricing (end of subsidies)
6. AI Energy Demand
7. The end of “vibe-coding”
8. Sam Altman out at CEO of OpenAI

FEEDBACK?

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GUEST: Sam Ramji, CEO/Co-founder at Sailplane

SHOW: 1023

SHOW TRANSCRIPT: The Reasoning Show #1023 Transcript

SHOW VIDEO: https://youtu.be/q50s0oL37pQ

SHOW SPONSORS:

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

SHOW NOTES:

• Halt and Retool (presentation) 
• OpenAI Harness Engineering
• Anthropic Harness Engineering

1. The “Halt and Retool” Moment

• A single-day build and deployment of a production feature triggered a company-wide realization
• Paused all development to reassess how AI fundamentally changes engineering workflows
• Creating “shock moments” (like stopping work) is key to driving mindset shifts

2. From Coding to Agent Orchestration

• Developers are shifting from writing code → managing AI agents
• Work resembles “multi-boxing” or conducting an orchestra of parallel agents
• Success depends on coordinating tasks, not executing them directly

3. The Rise of Harness Engineering

• Defined as everything between raw AI prompts and production-ready output
• Focus: eliminating friction across the software development lifecycle 
• Key practices:
  • Logging agent errors and friction points
  • Continuously refining workflows and tooling
  • Letting AI reflect on and improve its own mistakes

4. Spec-Driven Development Becomes Critical

• Poor specifications lead to exponential inefficiencies
• Teams now spend significantly more time on design and specs than coding

5. Measuring the Impact

• ~3x increase in code velocity
• Near-zero “bit rot” 
• Faster feature delivery—sometimes within 24 hours

6. Token Maxing & Developer Fitness

• Higher token usage often signals better workflows and deeper integration with AI
• Performance becomes about system design, not efficiency constraints

7. New Tools & Interfaces

• Increased use of voice interfaces over typing
• Terminal-first workflows replacing traditional IDE-centric approaches
• AI-accessible knowledge bases becoming standard

8. The Future of Software Engineering

• Within ~6 months: developers may stop writing code
• Within ~12 months: developers may stop reading code
• Focus shifts to:
  • Intent, design, and orchestration. Domain expertise and problem modeling

FEEDBACK?

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GUEST: Matt Moore, CTO at Chainguard 

SHOW: 1022

SHOW TRANSCRIPT: The Reasoning Show #1022 Transcript

SHOW VIDEO: https://youtu.be/9Q0kWkTYRs8

SHOW SPONSORS:

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

SHOW NOTES:

• Chainguard Factory 2.0
• DriftlessAF

Scaling Challenges & “Factory” Evolution

• Early automation relied on tools like GitHub Actions
• At scale, simple systems broke due to:
  • Massive event volumes
  • API rate limits (e.g., GitHub quotas)
  • Exponential fan-out effects
• Key innovation: custom work queue + reconciliation model
  • ~90% event deduplication
  • Controlled throughput and backpressure
  • Improved reliability and system stability
• Introduced Driftless 
• Built on reconciliation principles (inspired by Kubernetes):
  • Compare desired vs. actual state
  • Continuously reconcile differences
• Benefits:
  • Resilience to missed events
  • Automatic retries and recovery
  • Scales better than purely event-driven systems

AI Agents in Software Development

• AI is dramatically accelerating development workflows
• Chainguard uses agents to:
  • Remediate vulnerabilities (CVEs)
  • Update dependencies
  • Fix failing tests and adapt to upstream changes

Key Design Philosophy

• Least privilege → “least tool call”
  • Avoid giving agents full system access
  • Provide narrowly scoped tools for specific tasks
• Delegate execution to sandboxed systems (e.g., CI pipelines)
• Focus on safe, controlled automation

Industry Shift: Velocity vs. Security

• Explosion of AI-driven tools (e.g., autonomous PR generation)
• Massive increase in development velocity
• New risks:
  • Poorly secured agent frameworks
  • Malicious or unsafe automation patterns

Key Takeaways

1. Scale changes everything
   • Simple systems break under massive workloads
   • Purpose-built infrastructure becomes necessary
2. Reconciliation > pure event-driven systems at scale
   • More resilient, predictable, and controllable
3. AI is a force multiplier—but requires guardrails
   • Unrestricted agents introduce serious risk
   • Constrained, purpose-built agents are safer and more effective
4. Continuous learning is mandatory
   • AI tooling is evolving too fast for static skillsets
   • Teams must actively experiment and adapt

FEEDBACK?

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GUEST: Marissa Hummon, CTO Utilidata

SHOW: 1021

SHOW TRANSCRIPT: The Reasoning Show #1021 Transcript

SHOW VIDEO: https://youtu.be/ItcpU8UjOFE

SHOW SPONSORS:

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

SHOW NOTES:

• Utilidata (homepage)
• AI Data Center to Receive 50% Capacity Boost with AI Power Orchestration

KEY TOPICS:

• Differences between grid power dynamics vs. AI workloads
• Edge AI for real-time power flow optimization
• Unlocking stranded capacity in existing infrastructure
• “4-to-make-3” vs. “4-to-make-4” data center design
• AI training vs. inference power consumption patterns
• Role of NVIDIA-powered edge compute modules
• Grid modernization and coordination with utilities
• Security and resilience in critical infrastructure

KEY MOMENTS:

• From centralized AI models to edge-based decision-making
• Defining efficiency: utilization vs. thermal performance
• Why AI workloads aren’t as constant as they seem
• NVIDIA partnership and edge compute in power systems
• Using redundancy to increase usable capacity
• Increasing density of AI compute and hidden capacity
• Data center vs. utility responsibilities
• Addressing data center bottlenecks and scaling challenges
• Customer landscape: hyperscalers to enterprise
• Security, resilience, and critical infrastructure

KEY INSIGHTS:

• AI workloads are dynamic, not constant: Training and inference create fluctuating power demands that can be optimized.
• Edge intelligence is critical: Real-time sensing and decision-making at the edge unlock efficiency gains not possible with centralized models.
• Hidden capacity exists: Many data centers have up to 2x unused power capacity due to lack of visibility and control.
• Software-defined power is the future: Faster control loops allow systems to safely exceed traditional design limits.
• Efficiency = utilization: The biggest gains come from better use of existing infrastructure, not just improving hardware efficiency.

TAKEAWAYS:

• AI infrastructure growth is as much an energy challenge as a compute challenge
• Real-time, edge-based control systems are key to scaling sustainably
• Existing grid and data center investments can go further with smarter orchestration
• The future of AI scaling depends on aligning compute innovation with energy intelligence

FEEDBACK?

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GUEST: Uri Haramati, CEO at Torii

SHOW: 1020

SHOW TRANSCRIPT: The Reasoning Show #1020 Transcript

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

SHOW SPONSORS:

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

SHOW NOTES:

• Torii (homepage)

Topic 1 - Welcome to the show. Tell us about your background and your focus at Torii. 

Topic 2 - Is Shadow AI really a security problem—or is it a product-market fit problem inside the enterprise?

Topic 3 - Why does Shadow AI spread faster—and become more dangerous—than traditional Shadow IT?

Topic 4 - What’s the first signal a company should look for to know Shadow AI is already happening?

Topic 5 - How do you balance visibility vs. control without killing the productivity gains that drove Shadow AI in the first place?

Topic 6 - How should organizations rethink ‘data loss prevention’ in a world where the leak is a prompt, not a file?

Topic 7 - What does a ‘well-governed’ AI environment actually look like in practice—day-to-day for an employee?

Topic 8 - “Do you think Shadow AI ever fully goes away—or does it become a permanent operating model that companies need to design around?”

FEEDBACK?

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GUEST: Brandon Whichard, Co-Host of Software Defined Talk

SHOW: 1019

SHOW TRANSCRIPT: The Reasoning Show #1019 Transcript

SHOW VIDEO: https://youtu.be/q0mksIKcBzk

SHOW SPONSORS:

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

SHOW NOTES:

• The New Kingmakers (Stephen O’Grady - 2014)
• Developer Growth Rates

[Via ChatGPT]  A useful way to think about it:

• Typing code → mostly commoditized
• Designing systems → partially assisted
• Owning outcomes → still very human

Topic 1 - How many years into Public Cloud did we assume that Cloud had solved the IT problem? 

Topic 2 - Developers - what are we solving for?

• 10% of time coding, mostly on the last 10-15% 
• Lots of time in planning meetings (decoding requirements, resource planning, updates, etc.)
• Decent amount of time fixing, troubleshooting, technical debt reduction

Topic 2a - Business people have unlimited ideas, and most ideas are money + tech

• What would be their interface to problem solving without developers? (is this just a shift to consultants)
• Is this a massive opportunity for a great PaaS 3.0 company (e.g. is Vercel an example?)

Topic 3 - [Hypothetical] Let’s assume a fairly normal company fired all their software developers tomorrow. How long before they could get a moderately complex new application of integration into production? 

Topic 4 - Nobody likes to work on legacy code - missing source, missing engineers, etc. What do we call any code written by AI that was abandoned within the last 6-12 months? 

FEEDBACK?

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GUEST: Roie Schwaber-Cohen, Head of Developer Relations at Pinecone

SHOW: 1018

SHOW TRANSCRIPT: The Reasoning Show #1018 Transcript

SHOW VIDEO: https://youtu.be/-kZZEMR341Q

SHOW SPONSORS:

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

SHOW NOTES:

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

Topic 2 - Let’s begin by talking about RAG systems. What are they? Why do companies choose to use them? What benefits do they provide in AI systems?

Topic 3 - At a high level, RAG sounds straightforward—retrieve relevant context, generate an answer. But in practice, where does it break first as systems scale?

Topic 4 - I’ve heard that RAG systems can return answers that are technically correct but fundamentally wrong. What’s a concrete example of that happening in production—and why does it slip past most teams?

Topic 5 - In traditional systems, we assume there’s a single source of truth. But in enterprise environments, ‘truth’ is often versioned, contextual, and conflicting. How should teams rethink ‘truth’ when building AI systems?

Topic 6 - A lot of teams assume their knowledge base is ‘good enough’ for RAG. What do they usually underestimate about the messiness of real enterprise data?

Topic 7 - There’s a growing narrative that better reasoning models can compensate for weaker retrieval. From what you’ve seen, where does that idea fall apart?

Topic 8 - If correctness depends on things like timing, policy scope, or configuration, how should teams design systems that understand context—not just content?

Topic 9 - Looking ahead, what replaces today’s RAG architectures? What patterns are emerging among teams that are actually getting this right?”

FEEDBACK?

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GUEST: Jeff Keyes, Field CTO at AllStacks 

SHOW: 1017

SHOW TRANSCRIPT: The Reasoning Show #1017 Transcript

SHOW VIDEO: https://youtu.be/cXPu8iWeB0k

SHOW SPONSORS:

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

SHOW NOTES:

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

Topic 2 - You’ve been talking to a lot of engineering leaders using AI coding tools—what’s the most surprising gap you’re seeing between increased code generation and actual delivery outcomes?

Topic 3 - Why does increasing developer output with AI often lead to more debugging, duplication, or cleanup instead of faster delivery?

Topic 4 - You’ve described an ‘invisible rework loop’—can you walk us through what that looks like inside a modern engineering team?

Topic 5 - As code generation gets easier, where does the real bottleneck shift in the software delivery lifecycle?

Topic 6 - How do unclear product or engineering specifications get amplified in an AI-assisted development environment?

Topic 7 - If traditional metrics like lines of code or velocity are becoming misleading, what should engineering leaders actually measure to know if AI is improving delivery?

Topic 8 - What does a ‘healthy’ AI-assisted development workflow look like 12–18 months from now?

FEEDBACK?

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GUEST: Anish Agarwal - CEO/Cofounder of Traversal

SHOW: 1016

SHOW TRANSCRIPT: The Reasoning Show #1016 Transcript

SHOW VIDEO: https://youtu.be/hF3MCRDhMno

SHOW SPONSORS:

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

SHOW NOTES:

• Traversal (homepage)

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

Topic 2 - AI is dramatically accelerating code generation, but not improving production outcomes. What’s fundamentally breaking in the traditional SRE model—and where do you see the biggest friction between speed and reliability?

Topic 3 - What are the most common failure patterns or mistakes you’re seeing in production from AI-generated code—and what’s driving them?

Topic 4 - AI can generate functional code, but it often lacks context about how systems behave in production. How is this changing what ‘good observability’ needs to look like?

Topic 5 - How do you see SRE evolving in an AI-first world? Does it become more automated, more policy-driven, or even partially autonomous?

Topic 6 - For organizations that want to embrace AI-assisted development but avoid production chaos, what are the most important guardrails they should put in place?

Topic 7 - If we fast-forward 2–3 years, what does a ‘modern’ production stack look like in a world where most code is AI-generated? What capabilities become absolutely essential? In one sentence—what’s the #1 thing a CTO should do right now?

FEEDBACK?

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GUEST: Shashi Upadhyay (President of Product, Engineering, and AI at Zendesk)

SHOW: 1015

SHOW TRANSCRIPT: The Reasoning Show #1015 Transcript

SHOW VIDEO: https://youtu.be/IQaxE-DjIpo

SHOW SPONSORS:

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

SHOW NOTES:

• The future of service belongs to self-improving AI

Topic 1 - Welcome to the show. Tell us a bit about your background and your focus today. 

Topic 2 - You describe this moment as a shift from systems of record to intelligent systems of action. What’s fundamentally broken in today’s customer service model that’s forcing this transition now? What changed in the last 2–3 years to make this possible?

Topic 3 - There’s been a lot of AI in customer service that overpromised and underdelivered. What are the biggest gaps between what customers actually need—like resolution—and what legacy automation has been delivering?

Topic 4 - The concept of a “self-improving” system is really powerful. What’s actually new here—what enables AI to improve with every interaction without constant human tuning?

Topic 5 - You’ve moved from assistive copilots to what you call “agentic AI” that can resolve issues end-to-end. Where are we today on that journey—and what still requires human involvement?

Topic 6 - Voice has historically been one of the hardest channels to automate. What changes with this new generation of AI that makes even complex, multi-step voice interactions solvable?

Topic 7 - If we fast-forward 2–3 years, what does a “best-in-class” customer service experience look like in an AI-first world?

FEEDBACK?

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SHOW: 1014

SHOW TRANSCRIPT: The Reasoning Show #1014 Transcript

SHOW VIDEO: https://youtu.be/XwyAC-hxOQY

SHOW SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

• Links to all the AI News covered in this months show

FEEDBACK?

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• Twitter/X: @TheEntAIShow
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SHOW: 1013

SHOW TRANSCRIPT: The Reasoning Show #1013 Transcript

SHOW VIDEO: https://youtu.be/zEmEH0t67js

SHOW SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

Topic 1 - How long have you been living the Claude-life, and when did it dawn on you to make this central to your day-to-day activities? 

Topic 2 - What were the biggest hurdles you had to overcome before you trusted the system and started letting it have ownership over tasks and workflows?

Topic 3 - What are some of your best practices in terms of machine setup, how or where you store data, how you decide what to give it access to? Walk me through your thoughts around things like keeping things simple, where to be complex, how you think about security, etc.

Topic 4 - How are you learning to give it more responsibilities, or just figure out new ways to be productive with it? 

• Good resources you’re pulling from? 
• Any tips to make it use less tokens?
• Skills marketplaces?

Topic 5 - What have been some of the biggest barriers to successful adoption, or just areas where you’re still struggling to get it to do the things you want? Or are you still in the learning curve stage and things just keep growing on one another?

Topic 6 - If you took the knowledge and skills you have now in Claude-life into your day-job, how do you see yourself working, as well as working with the rest of your team/teams? Would it bother you if you didn’t think they were using AI tools as much? 

FEEDBACK?

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SHOW: 1012

SHOW TRANSCRIPT: The Reasoning Show #1012 Transcript

SHOW VIDEO: https://youtu.be/aXOr91q76yM

SHOW SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

• NVIDIA GTC 2026 (Keynote)
• NVIDIA NemoClaw - OpenClaw + OpenShell + NVIDIA Agent Toolkit
• NVIDIA adds Groq LPU to their rack systems
• NVIDIA to invest $26B in Open Weight Models
• Interview with Jensen about Accelerated Computing (Stratechery)

Topic 1 - Jensen’s trying to paint the bigger picture of accelerated computing everywhere (robotics, autonomous driving, gen-ai, physical ai - but also just everyday enterprise apps). Everything is about keeping the stock price up, and margins high. The stock price provides the warchest to fight off all foes. 

Topic 2 - The inference architecture is a complex mix of GPUs, CPUs, ASICs/LPUs, high-speed networking and seems very different from the training architecture. How big is the burden on data center providers? What are the inference alternatives emerging? 

Topic 3 - Jensen talked a lot about OpenClaw and eventually about NVIDIA’s NemoClaw. How does his interest in Agentic AI tie into his interest in building NVIDIA’s own frontier model

FEEDBACK?

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SHOW: 1011

SHOW TRANSCRIPT: The Reasoning Show #1011 Transcript

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

SHOW NOTES:

• Kagenti (homepage)
• Kagenti (use-cases)
• “Old Things that look like Agents”
• “What makes Agents different?”
• CNV - What Makes Agents Different?
• “Handing your phone to a stranger, why Agents need their own identity”

Topic 1 - Welcome to the show. Tell us a little bit about your background and areas you focus on today. 

Topic 2 - Tell us a bit about the Kagenti project and the types of challenges it’s trying to solve for Agentic AI deployments. 

Topic 3 - How much commonality exists between different Agentic frameworks that a common, agnostic agentic orchestration approach can work? And how much difference still exists and would drive companies to silo’d deployments? 

Topic 4 - How far should an Agentic Orchestration framework go, and what types of things do you expect will still be Agentic framework dependent? 

• Is Kagenti more of a control-plane element, or more of a data-plane element? 

Topic 5 - As Kagenti evolves, what are some of the adjacent things that people should be keeping an eye on that might be a dependency, or could shift the direction of the project?

FEEDBACK?

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SHOW: 1010

SHOW TRANSCRIPT: The Reasoning Show #1010 Transcript

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

SHOW SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

WHY THE NEED FOR A CODE RED? 

• Velocity of Code (new companies)
• Velocity of Productivity (employees)
• Velocity of Analysis (strategy)
• AgentOps
• Token Factories
• Devs for Business, Re-Wiring the Concept of Business Analyst

FEEDBACK?

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SHOW: 1009

SHOW TRANSCRIPT: The Reasoning Show #1009 Transcript

SHOW VIDEO: https://youtu.be/7xARBtgiMQg

SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

• OpenClaw - Personal AI Assistant
• OpenClaw - Reddit
• OpenClaw, OpenAI and the Future (Peter Steinberger - OpenClaw creator)
• OpenClaw Foundation (coming soon)

Topic 1 - Welcome to the show. Tell us a little bit about your background in software engineering. 

Topic 2 - You recently jumped into the deep end of the pool with OpenClaw. Tell us about the week of immersion with this new technology. 

• What did you go into it thinking about?
• What did you learn, what did you create?
• What new sorts of things did you have to try?

Topic 2a - For anyone that’s new to OpenClaw, can you give us the basics of what OpenClaw does?

Topic 3 - You mentioned that this is a very different (or completely different) paradigm of how software is created. Can you walk us through the differences, your observations, how you had to really rethink things that you did before and after?

Topic 4 - In your day job, you’re focused on software that’s used by large enterprises that have to be concerned with security and stability, as much as they do innovation. How do you see the existing OpenClaw fitting into that world? 

• How do you expect that OpenClaw might need to change?
• How do you expect that enterprises might need to change to adapt to this new capability that might be unleashed with their employees?

Topic 5 - You (very) recently were accepted as a committer to the OpenClaw project. I know it’s only been a few days, but what is opening your eyes about how this community operates, especially in comparison to other open projects you’ve worked on? 

• We could probably have an entire podcast on AI development in open communities.

FEEDBACK?

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SHOW: 1008

SHOW TRANSCRIPT: The Reasoning Show #1008 Transcript

SHOW VIDEO: https://youtu.be/eA8vpPmSW0Y

SPONSORS:

• VENTION - Ready for expert developers who actually deliver?
  Visit ventionteams.com

SHOW NOTES:

Topic 1 - Welcome to the show. Tell us a bit about your background, and what you focus on now at Crusoe. 

Topic 2 - There has obviously been a lot of coverage of AI data center buildouts all over the world for the last few years. Tell us about Crusoe, and your approach to providing “neocloud” services. 

Topic 3 - What are the biggest challenges facing Crusoe today and in the immediate future - is it technology, energy, financing for expansions, etc.?

Topic 4 - Crusoe started as a bitcoin-focused company and has evolved to more of a GenAI-focus. What types of architectural changes did you have to make for this new type of workload? And how do those impact the quality of the services your customers expect from Crusoe?

Topic 5 - Is your focus more on environments to enable model training and customization, or more focus on inference for customer-facing applications? 

Topic 6 - A lot has changed in AI in the last couple years. What has changed the most in the last couple years, and what are you expecting to change the most over the next couple years? 

Topic 7 - Sovereign AI and Private AI have become much bigger topics over the last 12-18 months, and we’d expect that to grow. What unique things is Crusoe doing to adapt to these changing requirements from customers?

FEEDBACK?

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SHOW: 1007

SHOW TRANSCRIPT: The Reasoning Show #1007 Transcript

SHOW VIDEO: https://youtu.be/4tdj0S0AyhM

SHOW SPONSOR:

• VENTION - Ready for expert developers who actually deliver?
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SHOW NOTES:

Topic 1 - We’re 3+ years into the Generative AI era. Why do you think AI Agents, or Agentic AI, is now getting so much attention? 

Topic 2 - If someone asked you to explain what an AI Agent is, how would you do that? 

Topic 3 - What are some of the core elements of AI Agents that you’re seeing impact how people think about and use agents?

• How to define tasks
• Languages and frameworks
• Ability to orchestrate multiple agents
• Human-in-the-Loop vs. Autonomous
• Other?

Topic 4 - AI Agents are going to spark the great “how much should I pay for this?” discussion. Have you given this any thought yet?  

Topic 5 - How do you expect to use AI agents in your day-to-day work, and how do you expect this to impact Enterprise businesses?

ESSENTIAL READING

• Building Effective Agents" by Anthropic: designing agents with tools, memory, reasoning loops
• A Comprehensive Review of AI Agents: how agents perceive, reason, decide, act
• Top 20 AI Agent Concepts You Should Know: covering ReAct, Chain of Thought, memory types
• AI Agents in Action: Foundations for Evaluation and Governance: structured foundation for safety aspects of agent deployment

Essential Viewing

• AI Agentic Design Patterns w/ AutoGen: build autonomous agents that use tools
• AI Agent Systems w/ crewAI: orchestrating teams of agents
• LangGraph Course: how to build stateful, reliable agents

Frameworks & Tools 

• LangGraph: standard for complex, stateful agents (nodes, edges, loops)
• CrewAI: Best for structured task delegation and multi-agent collaboration
• AutoGen: Microsoft's framework for multi-agent conversational systems
• Model Context Protocol (MCP): standard for connecting agents, tools, data
• n8n: no-code/low-code visual agent building

FEEDBACK?

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SHOW: 1006

SHOW TRANSCRIPT: The Cloudcast #1006 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

SHOW NOTES:

• Link to February 2026 News and Articles

FEEDBACK?

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FEEDBACK?

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SHOW: 1005

SHOW TRANSCRIPT: The Cloudcast #1005 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"

SHOW NOTES:

Topic 1 - What are we announcing? (“The Reasoning Show”, a.k.a. “Reasoning”)

• New name, same RSS feeds (same podcast players)
• New logo
• Some existing/renamed and some new social media channels (will be listed)
• Same co-hosts (and maybe some new friends)

Topic 2 - Why are we changing The Cloudcast?

• The majority of our content is AI focused now
• Cloud has become mostly stable, AI is at the beginning and so much is changing
• We’re not abandoning Cloud, just giving it the amount of coverage needs (monthly Cloudcast, monthly CNOTM)
• Social media algorithms have changed audience acquisition

Topic 3 - Hasn’t The Cloudcast already been covering AI for a while? 

• Yes, it’s been about 50/50 since 2024
• We’ve been discussing this change for almost a year. 
• We actually discussed having an OpenAI-specific podcast at one point, but so much as changed in the market (which is a good reason for a diverse podcast)

Topic 4 - What can we expect from the new podcast?

• Still on Wednesday and Sunday
• Both audio and video formats (Apple, Spotify, YouTube, TikTok/Insta (clips))
• Trying to make it easier for someone new to follow along - more concentration around core topics, but not exclusively
• AI Technology, AI Economics, AI Trends, AI (Business) Use-Cases, AI Things to Watch, AI Productivity, AI Regulation
• We’ll still do a “Cloudcast” once a month, as the Cloud underpins almost everything AI
• We’ll likely do a “Reasoning Basics” spin-off, like Cloudcast Basics. 
• We’ll get a newsletter pulled together (hopefully weekly). 

Topic 5 - Anything else?

• Listeners don’t have to do anything to keep getting their week podcast
• Subscribe to the social media channels (show notes)
• Leave a 5-star review on the podcast players
• Tell a friend to check out the show

FEEDBACK?

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SHOW: 1004

SHOW TRANSCRIPT: The Cloudcast #1004 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

CHAPTERS

00:00 - Celebrating Milestones and AI Insights

02:48 - The Cost of AI Agents and Realizations

06:05 - Centralization vs. Decentralization in AI

08:51 - The Evolution of AI Economics

12:03 - Future Trends in AI and Project Management

14:52 - Connecting AI to Real-World Economics

KEY TOPICS:

• AI agent costs and pricing models
• The shift from centralized to decentralized computing
• Token budgets and project economics in AI
• Historical transitions in computing infrastructure
• Future trends in AI project management

SHOW NOTES

• When AI Tokens cost more than your employees 
• Should you own (or generate) your own tokens? 
• On running a startup of Claude Code agents: 1 Billion tokens a month
• Can AI grow corn? 

WE'VE REACHED A POINT WITH AI WHERE PEOPLE ARE STARTING TO THINK ABOUT THE BUSINESS IMPACTS

• How much should an AI project cost?
• How do we translate an AI token into some unit that a business can understand?
• How companies be their own AI token factories?

FEEDBACK?

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SHOW: 1003

SHOW TRANSCRIPT: The Cloudcast #1003 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SHOW NOTES:

• Last Week in AI Podcast #234
• Artificial Analysis.AI
• Opus 4.6 Release
• GPT Codex 5.3 Release
• GLM-5 Release
• OpenAI Preparedness Framework
• Sam’s Tweet that 5.3 Codex hit “high” ranking for cybersecurity
• Fortune Article on 5.3 high ranking

TAKEAWAYS

• The frequency of AI model releases can lead to numbness among users.
• Evaluating AI models requires understanding their specific use cases and benchmarks.
• Enterprises must consider the compatibility and integration of new models with existing systems.
• Benchmarks are becoming more accessible but still require careful interpretation.
• The rapid pace of AI development creates challenges for enterprise adoption and integration.
• Companies need to be proactive in managing the versioning of AI models.
• The industry may need to establish clearer standards for evaluating AI performance.
• Efficiency and cost-effectiveness are becoming critical metrics for AI adoption.
• The timing of model releases can impact their market reception and user adoption.
• Businesses must adapt to the fast-paced changes in AI technology to remain competitive.

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SHOW: 1002

SHOW TRANSCRIPT: The Cloudcast #1002 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

A FLY ON THE WALL IN 3 ROOMS IN 2026

• Room1 - NVIDIA’s M&A Room (Chips, Software Stack, Hosting Services, Agentic Tools, etc.)
• Room 2 - Anthropic’s Agentic Vision
• Room 3 - TSMC’s 2028-2030 Planning

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SHOW: 1001

SHOW TRANSCRIPT: The Cloudcast #1001 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

SHOW NOTES:

• Stratechery (Ben Thompson)

WHAT DO WE WISH WE KNEW ABOUT AI IN 3 YEARS?

• Economics
• Politics
• Technology
• Regulations
• Partnerships
• Buying Patterns
• Usage Patterns
• Devices
• Job Creation/Destruction

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SHOW: 1000

SHOW TRANSCRIPT: The Cloudcast #1000 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

SHOW NOTES:

• Chainguard introduces Factory 2.0
• On running a startup of Claude Code agents
• Agentic Product Development and the Theory of Constraints
• Software Abundance

HOW SHOULD SOMEONE THINK ABOUT THE ECONOMICS OF SW DEV IN 2026?

• If someone walked into your office today and asked you to build a framework for how to value software development, how would you think about it? 

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SHOW: 999

SHOW TRANSCRIPT: The Cloudcast #999 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES

• The SPAC-king is going to fix legacy software 
• All Enterprise software is dead 
• Microsoft and Software Survival (Stratechery)

WHAT HAPPENS TO ENTERPRISE SOFTWARE NEXT?

• How much do enterprises want to write their own software? 
• How much do enterprises wish they could write more software?
• How much do enterprises not understand the economics of owning their own software?
• How much does “big SaaS” or just “big Enterprise software” actually help because people already know it?
• Is it possible that this new Agentic-driven software could create a type of new software community? 
• Are “open” software communities prepared for the emerging economics of AI-created software? 

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SHOW: 998

SHOW TRANSCRIPT: The Cloudcast #998 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES

• AWS European Sovereign Cloud 
• Azure European Sovereign Services
• Google Cloud Sovereign Cloud
• Red Hat Digital Sovereignty
• Broadcom Digital Sovereignty
• Oracle Digital Sovereignty
• Digital Sovereignty in Europe, What’s the Plan B? (IDC)
• Digital Commons EDIC Established (2025)
• EU AI Act
• “Sovereign Clouds and the Digital Sovereignty Imperative: Europe's Quest for Digital Independence” (IDC #EUR149098122, December 2022)
• The Evolution of Digital Sovereignty: Moving Beyond Data and Cloud” (Rahiel Nasir, IDC, January 13, 2023)

THE FUNDAMENTALS OF DIGITAL SOVEREIGNTY 

• What is the definition of Digital Sovereignty? What about Digital Assurance? 
• Sovereignty from who or what? 
• What laws are you attempting to comply with? How are they audited or measured? 
• Data Sovereignty - Maintaining control over how data is collected, classified, processed and stored to ensure that data regulations are met
• Technical Sovereignty - Running workloads without dependence on a provider’s infrastructure or software, and protected from all extra-territorial interference and scrutiny.
• Operational Sovereignty - Visibility and control over provider operations from provisioning and performance management, to monitoring of physical and digital access, to the infrastructure.
• Assurance Sovereignty -Ability to independently verify and assure the integrity, security, and reliability of digital systems and processes including resilience of critical services.

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SHOW: 997

SHOW TRANSCRIPT: The Cloudcast #997 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"

SHOW NOTES:

• Link to January 2026 News and Articles

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SHOW: 996

SHOW TRANSCRIPT: The Cloudcast #996 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

SHOW NOTES:

Q1 - What didn’t Cloud 1.0 achieve from the grand vision?

Q2 - What seemed promising but might have been the wrong timing? 

Q3 - Why didn’t more SaaS get bundled by the hyperscalers?

Q4 - Does multi-cloud become easier?

Q5 - Do primitives continue to be the core offering, or do more integrated offerings dominate the landscape?

Q6 - Do a bunch of existing primitives get turned off to make room for new AI capabilities (DC capacity)?

Q7 - Is security on by default? 

Q8 - Do more private/sovereign capabilities get offered?

Q9 - What are the new AI capabilities that nobody has even thought of yet?

Q10 - How does the mix of AI workloads get distributed across clouds, or across private and public? 

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SHOW: 995

SHOW TRANSCRIPT: The Cloudcast #995 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" 

SHOW NOTES:

Lesson 1 - Why did we create The Cloudcast? [Career expansion]

Lesson 2 - How did we learn all the topics we covered? [Skills development]

Lesson 3 - What have been the biggest Cloud trends we’ve covered [Trends]

Lesson 4 - How did you think about technology transitions over the last 10-15 years? [Change]

Lesson 5 - How important was it for you to learn the business side of cloud? [Follow the money]

Lesson 6 - What structural changes do you think Cloud will have on IT in 10 years? [Legacy]

Lesson 7 - What lesson from an episode do you think about the most frequently?

Lesson 8 - What surprised you the most about the Cloud 1.0 era?

Lesson 9 - What did you expect to happen, which never really happened?

Lesson 10 - What were the most important lessons you personally learned? [Lessons Learned]

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SHOW: 994

SHOW TRANSCRIPT: The Cloudcast #994 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES

• AWS in 2026: The year of proving they still know how to operate (This Week in AWS)

WHAT IS AND ISN’T CLOUD IN 2026?

• Cloud isn’t a single company
• Cloud isn’t just public cloud
• A CIA cloud isn’t a Gov cloud isn’t your Enterprise Cloud
• Multi-cloud is a real thing that needs technology
• Google, the people that invented “cloud” are a real company in cloud
• Defining cloud by purity, or IaaS/PaaS/SaaS terms doesn’t really matter
• Does data locality matter more in an AI-Cloud era?
• Do we begin to see price wars over the core Cloud 1.0 primitives?
• Are we in the 9th inning of Cloud, and the 1st inning of what’s next? 
• AI has replaced SaaS in immediacy, so does that have impact on Cloud services? 
• Does the lack of application portfolio finally come back to bite AWS? 
• Can niche cloud services emerge (e.g. is Vercel another Digital Ocean, or something unique?)

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SHOW: 992

SHOW TRANSCRIPT: The Cloudcast #992 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SHOW NOTES:

• Tonic.ai website
• Tonic Validate Product Page
• Tonic Validate GitHub

Topic 1 - Adam, welcome to the show. Give everyone a brief introduction.

Topic 2: Our topic today is RAG systems, specifically RAG in production. Let’s start with customization sources and types. When it comes to customizing off-the-shelf LLMs, RAG is one option, as is an MCP connection to a SQL database, and there is pre- and post-training, as well as fine-tuning. How does an organization decide what path is best for customization?

Topic 3 - RAG came on the scene as the savior for organizations that want to use customer AI without the need for fine-tuning and additional training. It has either gone through or is currently still in the trough of disillusionment. What are your thoughts on RAG's evolution and the challenges it faces?

Topic 4 - Let’s walk through the basics of validation. Once you set up RAG, how would an organization know it works? How is accuracy measured and validated? Are you looking for hallucinations? Context quality?

Topic 5 - What is Tonic Validate, and where does it fit into this stack? Is it in band? Out of band? Built into the CI workflow?

Topic 6 - Accuracy is one aspect, but we hear more and more about ROI for Enterprises. How should ROI, risk, and compliance be measured?

Topic 7 - Where and how does security fit into all of this? Also, your thoughts on synthetic data for training vs. real data?

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SHOW: 991

SHOW TRANSCRIPT: The Cloudcast #991 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SHOW NOTES:

• Percona website

Topic 1 - Welcome to the show, Peter. Give everyone a brief introduction, and we’ll also dig into the details of Percona after that.

Topic 2 - Percona is basically a household name in our space. Part of that is the excellent tech, and part of that is the longevity. Tell everyone the origin story of Percona.

Topic 3 - How have OSS databases evolved? Going back 20 years is a bit far, but what recent trends stand out? How have cloud (i.e. the hyperscalers) and SaaS in particular changed this landscape 

Topic 4 - Percona plays in the same space, and with, MySQL, MongoDB, PostgreSQL. If you don’t mind, help everyone connect the dots there and why that matters.

Topic 5 - What are the typical business cases and implementations you are seeing today? What are organizations trying to solve for the most?

Topic 6 - How has AI and the rise of embeddings and vector databases impacted the OSS space? What are your thoughts here? Is this complementary/competitive/both?

Topic 7 - What do you wish people knew more about Percona?

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SHOW: 990

SHOW TRANSCRIPT: The Cloudcast #990 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"

SHOW NOTES:

• Link to December 2025 News and Articles

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SHOW: 989

SHOW TRANSCRIPT: The Cloudcast #989 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES:

• CLOUD & AI NEWS OF THE MONTH - NOV 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - OCT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - SEPT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - AUG 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUL 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUN 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAY 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - APR 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAR 2025 (show)

2026 CLOUD + AI PREDICTIONS (AND BIG ISSUES TO REVIEW)

• OpenAI Revenues and Focus Areas
• NVIDIA customer profitability
• Companies moving to GOOG TPUs
• Enterprise success beyond CoPilot/Gemini
• Enterprise data+model trainability
• Enterprise price hikes
• Broadcom, AMD, Groq - alternative HW options
• Data Center buildouts
• Does AI spending shift
• What is Agentic AI?
• Long term spending + short term refocuses

PREDICTIONS:

• At least one big AI IPO in 2026, and it won’t go well. (Aaron says Anthropic)
• People will question whether Sam Altman is the right person to lead OpenAI
• AI will be a central issue in the 2026 US elections, either about job losses or electricity prices
• One major LPU/TPU/dedicated inference chip will break through in 2026
• Azure will be the Number One Cloud… (Aaron has to keep it going)
• We will start to see a shift in the Enterprise from big models in the sky (1+trillion parameters) to dedicated, purpose-built models of 500M or less in size for efficiency and security
• Gemini will dominate the consumer/prosumer space, OpenAI will go through the trough of disillusionment
• The industry will shift to a base/instruct and a reasoning split of models
• AWS and Azure will double down on being a solutions provider instead of a primitive supplier for AI and infrastructure

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SHOW: 988

SHOW TRANSCRIPT: The Cloudcast #988 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES

IT WAS AN INTERESTING YEAR IN CLOUD AND AI TECHNOLOGY

• AI has become a mainstream technology, political and social talking point
• AI went through 7yrs of news cycles in 1 yr
• DeepSeek - Maybe NVIDIA chips aren’t needed?
• NVIDIA acquihired Grok and their technology
• Maybe AWS’ lead in the cloud is now in question
• Google got their act together with GenAI, after inventing the technology in 2017
• Microsoft and OpenAI sort of broke up, or at least they are seeing other people
• OpenAI forecasts 100x their current revenue in future computing needs
• The US Gov’t either bailed out, or socialized Intel
• Bitcoin - 94k, up to 125k, down to 84k

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SHOW: 987

SHOW TRANSCRIPT: The Cloudcast #987 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

SHOW NOTES

• CLOUD & AI NEWS OF THE MONTH - NOV 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - OCT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - SEPT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - AUG 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUL 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUN 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAY 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - APR 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAR 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - FEB 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JAN 2025 (show)

2025 AI YEAR IN REVIEW

• The Year of OpenAI
• The Year of NVIDIA
• The Year of Microsoft
• The Year of Google
• The Year of Oracle
• The Year of China AI
• The Year of Apple
• The Year of Coding Agents (Anthropic, Cursor, Windsurf, CLIs, etc..)
• The Year of Data Centers
• AI Highlights and Lowlights (Corporate Layoffs, Acquihires, Funding, etc..)
• 2026 AI Draft

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SHOW: 986

SHOW TRANSCRIPT: The Cloudcast #986 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES

• Planning for AGI and Beyond (OpenAI) 
• Machines of Loving Grace (Anthropic)
• Microsoft and Google has different visions/opinions on AGI
• Amazon reorganizes around new AGI team reporting to Andy Jassy
• Mistral CEO says that AGI is a marketing move 
• AGI is defined by an independent committee in new Microsoft and OpenAI agreement
• Why does being first to AGI matter?
• Bret Taylor on the current status of AGI (Acquired/AC2 podcast, 2025)

WHAT DOES REACHING AGI PROVIDE FOR HUMANITY (or ANYTHING)?

• Y2K bug, 2038 Bug (techies are good at dates when things need to be patched)
• The % of people with Internet access
• The % of people with a smartphone
• The % of people with a certain level of education (basic or advanced)
• How much smarter is humanity than 10yrs ago? 20yrs ago? 
• How much smarter could existing humanity be at any given time? 
• Nobody has a consistent or measurable definition of AGI
• What are the Top 10 problems of humanity that need to be solved? (direct or indirect)
• Does reaching AGI enable certain government or corporate actions to start happening that couldn’t happen now? 

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SHOW: 985

SHOW TRANSCRIPT: The Cloudcast #985 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW NOTES:

• CLOUD & AI NEWS OF THE MONTH - NOV 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - OCT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - SEPT 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - AUG 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUL 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JUN 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAY 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - APR 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - MAR 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - FEB 2025 (show)
• CLOUD & AI NEWS OF THE MONTH - JAN 2025 (show)

2025 CLOUD YEAR IN REVIEW

• Cloud of the year 
• Cloud concept of the year (non-AI)
• Cloud memory of the year
• Cloud revenues in 2025
• Are NeoClouds in the hyperscaler discussion? 
• Was Cloud (circa 2007) the actual downfall of Intel? (Cloud vs Mobile choice)
• Rank the clouds, end of 2025 (cloud draft 2025)
• Do outages matter if they are only once a year? 
• Where does AWS go next?

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SHOW: 984

SHOW TRANSCRIPT: The Cloudcast #984 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

• [Mailtrap] Try Mailtrap for free
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.

SHOW NOTES

• OpenAI looks to train their models to replace junior bankers

WHAT WOULD BE THE STAGES OF AN EXPERT AGENT?

• Train it on a set of standard knowledge (e.g. Masters of Accounting, Auditing, International Tax)
• Train it on a set of well-defined case studies, to provide industry context
• Train it on a set of adjacent case studies and other domains (business, law, specific industries)
• How to train corner cases?
• How to train gray areas like ethics, morality, or cost-benefit analysis? 
• Who is motivated to train these experts? 
• What would the cost of these experts be? Can it be similar to a human, or need to be a fraction, or a premium? 
• Is there a way to build memory (e.g. experience) without disclosing client information? 
• Is there a way to build shareable knowledge between agents for reinforcement training/learning?

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter/X: @cloudcastpod
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FEEDBACK?

• Email: show @ the enterprise ai show dot come
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SHOW: 983

SHOW TRANSCRIPT: The Cloudcast #983 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SPONSORS:

• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [Mailtrap] Try Mailtrap for free

SHOW NOTES:

• Hitachi Vantara (website)

Topic 1 - Welcome to the show. Tell us about your background.

Topic 2 - How is AI changing the way enterprises need to think about infrastructure?

Topic 3 - What makes AI workloads so different from traditional workloads? How is AI exposing the limitations of broken cloud environments?

Topic 4 - Where are organizations feeling the most pressure? What are the biggest misconceptions enterprises have about preparing for AI?

Topic 5 - What problems come from managing separate systems? What is the biggest driving factor toward unified data platforms?

Topic 6 - How is Hitachi Vantara helping customers handle the growing infrastructure demands created by AI?

FEEDBACK?

• Email: show at the cloudcast dot net
• Bluesky: @cloudcastpod.bsky.social
• Twitter/X: @cloudcastpod
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• TikTok: @cloudcastpod

FEEDBACK?

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

SHOW: 982

SHOW TRANSCRIPT: The Cloudcast #982 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

• [Mailtrap] Try Mailtrap for free
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.

SHOW NOTES

• Vercel v0
• Building Web Apps with just English and AI (Acquired podcast, Feb 2025)
• Vercel on The Cloudcast (2024)
• Vercel on The Cloudcast (2021)
• 8 tools to build your own PaaS (2025)

IS PAAS READY TO TAKE THE NEXT STEP? 

• Where could PaaS evolve to now?
  • Can new PaaS services abstract the developer, and just focus on business logic and business ideas? 
  • What languages or design patterns would be mandated? (web only, mobile only, web + mobile? )
  • Can we template “best practices” enough to be reliable?
  • Can we template compliances needed to handle financial transactions, customer data, etc.?
  • Can troubleshooting become an automated service?
• Where was PaaS in the past? (Heroku, Google AppEngine, Cloud Foundry, Kubernetes)
• Language specific
• Cloud specific
• Abstracting the infrastructure and security

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter/X: @cloudcastpod
• BlueSky: @cloudcastpod.bsky.social
• Instagram: @cloudcastpod
• TikTok: @cloudcastpod

FEEDBACK?

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

SHOW: 981

SHOW TRANSCRIPT: The Cloudcast #981 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"

SPONSORS:

• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [Mailtrap] Try Mailtrap for free

SHOW NOTES:

• Link to November 2025 News and Articles

FEEDBACK?

• Email: show at the cloudcast dot net
• Bluesky: @cloudcastpod.bsky.social
• Twitter/X: @cloudcastpod
• Instagram: @cloudcastpod
• TikTok: @cloudcastpod

FEEDBACK?

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

SHOW: 980

SHOW TRANSCRIPT: The Cloudcast #980 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

• [Mailtrap] Try Mailtrap for free
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast

SHOW NOTES

THINGS TO BE THANKFUL FOR:

• Thankful for health
• Happy Birthday to ChatGPT
• The feature on an iPhone that remembers the code sent in an SMS message
• Role playing, brain storming, scenario planning on ChatGPT/Gemini
• Tools like Vercel that let non-programmers use AI to build apps (the future of PaaS)
• Tools like NotebookLM making complex stuff like LLM training, RAG patterns,  
• True competition in the cloud market as differentiation emerges
• The beginnings of alternatives to NVIDIA in the AI HW Acceleration market
• The evolution of wearables like fitness trackers, or AirPods (better sound quality, noise cancelling, language translation, etc.) 

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter/X: @cloudcastpod
• BlueSky: @cloudcastpod.bsky.social
• Instagram: @cloudcastpod
• TikTok: @cloudcastpod

FEEDBACK?

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

SHOW: 979

SHOW TRANSCRIPT: The Cloudcast #979 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SPONSORS:

• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast
• [Mailtrap] Try Mailtrap for free

SHOW NOTES:

• InfluxData homepage
• Evan on The Cloudcast #394
• SpaceNews article on Time Series and AI in Space
• Time Series is critical to Physical AI

Topic 1 - Welcome back to the show, Evan. Give everyone a brief introduction.

Topic 2 - We last spoke in 2019, and our goal with that show was to give everyone an introduction to time series databases. There’s a link in the show notes for those who want to go back and get a refresher. But, if folks aren’t up to speed, give everyone a quick definition of time series and its impacts in recent years

Topic 3 - First, we need to discuss Physical AI. What is Physical AI, and how is it different from, say, GenAI or Agentic AI? It seems that AI in the mainstream equates LLMs with AI, but that isn’t correct. We are talking about deterministic AI, not probabilistic solutions. Can you explain to everyone the difference and why it matters?

Topic 4 - Why is the concept of time series so crucial to Physical AI? Additionally, you provided a great analogy comparing time series data collection to low-resolution and high-resolution images. Can you explain to everyone why this is so important?

Topic 5 - Let’s talk about some use cases. How and where does this intersection of Physical AI and time series impact organizations the most? Is this specific to certain industries (robotics, aerospace, IoT, etc.) or specific collection mechanisms (telemetry, sensor data, etc.)

Topic 6 - Are we shifting with AI to a state that is less reactive and more proactive with an active intelligence?

Topic 7 - What kind of demands do real-time, modern workflows and data streaming place on the infrastructure? When I think of time series, I think of real-time data, which means ultra-low latency and processing near the source, among other things. 

FEEDBACK?

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FEEDBACK?

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

SHOW: 978

SHOW TRANSCRIPT: The Cloudcast #978 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast
• [Mailtrap] Try Mailtrap for free
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.

SHOW NOTES:

• NVIDIA Earnings (Q3FY2026 - November 2025)

WHAT WILL BE THE NEW METRICS AND MILESTONES TO TRACK?

• Customer Revenues (e.g. CoreWeave, OpenAI)
• “Alternatives” Revenues (e.g. Google/TPUs, AMD, China, etc.)
• Customer Success Stories (%ROI, Business Differentiation, Business Acceleration)
• Growth of Data Centers (e.g. buildouts, zoning approvals, etc.)
• Electricity Buildouts (e.g. nuclear, coal, alternative, regulatory changes, municipality adoption)
• Accounting Deep-Dives into NVIDIA (not fraud, but days receivables, inventory buybacks, etc.)
• $500B in back orders (Oracle, Microsoft, OpenAI, GrokAI)

FEEDBACK?

• Email: show at the cloudcast dot net
• Twitter/X: @cloudcastpod
• BlueSky: @cloudcastpod.bsky.social
• Instagram: @cloudcastpod
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FEEDBACK?

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

Rohan Sathe (@rssathe, CEO @NightfallAI) discusses the rise of Shadow AI, where employees unknowingly leak sensitive corporate data through generative AI tools like ChatGPT. 

SHOW TRANSCRIPT: The Cloudcast #977 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SPONSORS:

• [Mailtrap] Try Mailtrap for free
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast

SHOW NOTES:

• Sunday Perspective touches on Shadow AI
• Nightfall website

Topic 1 - Welcome to the show, Rohan. Give everyone a brief introduction, including your time at Uber Eats.

Topic 2 - How do you define Shadow AI? We hear Shadow AI compared to Shadow IT back at the start of cloud. However, this looks different because everyone's learning curve is much smaller. For Shadow IT to happen, you had to know IT (servers, storage, etc.). Is this the correct way to think about the problem?

Topic 3 - How big is the Shadow AI problem today?

Topic 4 - Normally, data leaks would be discovered by traditional DLP (data loss prevention) tools. In my experience, those tools have been cumbersome and clunky, and you often face the classic trade-off between user productivity and security, as well as the need to lock down access. How has this mindset evolved in the era of AI? 

Topic 5 - What happens when AI-powered attacks meet AI-powered defense?

Topic 6 - Let's talk about the technical architecture. How does Nightfall actually work across SaaS apps, endpoints, browsers, and AI tools?

FEEDBACK?

• Email: show at the cloudcast dot net
• Bluesky: @cloudcastpod.bsky.social
• Twitter/X: @cloudcastpod
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FEEDBACK?

• Email: show @ the enterprise ai show dot come
• Bluesky: @TheEntAIShow.bsky.social
• Twitter/X: @TheEntAIShow
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SHOW: 976

SHOW TRANSCRIPT: The Cloudcast #976 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw

CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"

SHOW SPONSORS:

• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast
• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.

SHOW NOTES:

• A whole bunch of AI-related stats
• Sam Altman on BG2 podcast

DO WE HAVE ANY IDEA HOW TO MEASURE THE IMPACT OF AI?

• How much is one model better than another (e.g. Gemini vs. CoPilot)?
• How much improvement should a software developer get?
• How much improvement should a knowledge worker get?
• How much cost savings should a chatbot provide?
• How long should it take to make a model understand a company’s data?
• How many workers can a company displace with AI?
• OpenAI in 2030 - 26 gigawatts could power between 3.7 million to 17.3 million modern GPU servers
• OpenAI in 2035 - 50 gigawatts could power between 37 million to 173 million modern GPU servers

FEEDBACK?

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• Twitter/X: @cloudcastpod
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FEEDBACK?

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

SHOW: 975

SHOW TRANSCRIPT: The Cloudcast #975 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS" 

SPONSORS:

• [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.
• [TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast

SHOW NOTES:

• LaunchAny website
• apicoach.io (note)
• Lessons learned after a decade of API Strategy
• Latest book: “Principles of Web API Design: Delivering Value with APIs and Microservices (Addison-Wesley under the Vaughn Vernon signature series)
• Upcoming report on AI-Assisted API Design
• James on The Cloudcast #153
• James on The Cloudcast #435

Topic 1 - Welcome back to the show James. It’s hard to believe it’s been 11 years since we last spoke on the show! Give everyone a brief introduction.

Topic 2 - To say we’ve come a long way with APIs as an industry is an understatement. But let’s set the table for everyone. In your interactions with Enterprise customers, what trends or standards are currently top of mind? 

Topic 3 - You wrote an article (link in show notes) titled Lessons after a Decade of API Strategy. What struck me from the article was the combination of technology, business, and even culture, all of which have to come together. When talking to Enterprises these days, have we moved past understanding what APIs are and straight to solving problems with APIs?

Topic 4 - What are the most common use cases you see today? API transformation? API sprawl and consolidation/documentation? Integration of SaaS/3rd party services?