The annual Kagan Media and Telecom Summit in New York is in the books and it not only covered a lot of market activity, but it was also surrounded by a number of media and sports rights headlines. Justin Nielson, Eric Keith, Scott Robson and Seth Shafer joined host Eric Hanselman to look at what was covered in the expansive event and the time around it. There were big shifts in media rights and a couple of sports team sales that led to lively discussions. Networks are balking at some of the lofty prices for sports media rights in the face of streaming services’ higher demand. The realignment of regional sports coverage is still shaking out, as well. Media consolidation keeps hovering, but will it always be next year’s prospect? Macroeconomic uncertainty seems to be playing a role and the pendulum on cord cutting seems to be swinging back around. In broadband, the reset of the BEAD program has states scrambling to reapply under the new, much tighter deadline. Will this drive fixed wireless access (FWA)? Satellite is still a possibility in remote regions, but costs may hold it back. Private equity activity in fiber networks could be reaching a tipping point, as their investments mature and operators’ partners shift strategies. There was a lot in store and much more to come. More S&P Global Content: Kagan Media and Telecom Summit event link For S&P Global subscribers: A sneak preview of the Kagan Media & Telecom Summit 2025 See it in charts: TV Networks, June 2025 Comcast strikes sports network deal; Streaming services expand sports viewing New media rights deal a slam dunk for the NBA Kagan Media & Telecom Summit 2025: Broadband panel discussion Credits: Host/Author: Eric Hanselman Guests: Justin Nielson, Erik Keith, Scott Robson, Seth Shafer Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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Security for MCP
The Model Context Protocol (MCP) specification has helped to accelerate access to a wide range of data sources for AI applications. But there are questions about the security and trust implications around a protocol that is still in its infancy. Scott Crawford and Justin Lam return to the podcast to examine the concerns that have been raised and changes that are underway in the specification with host Eric Hanselman. The previous episode introduced MCP and some of the market forces that are in play. Security considerations didn’t appear to be fully sorted out in the first version of the specification, but more work is being done to move beyond the OAuth-based approach. Automating the data access process can be powerful, but also fraught with the potential for abuse. The larger questions in MCP revolve around understanding risk and establishing trust. Data exposure has been a constant concern in AI, but the more complex issues exist in the integrity of the data that’s being used. AI technology is moving forward rapidly and adversaries that are looking to compromise it and moving right along with these advances. More S&P Global Content: The 2025 Generative AI Outlook Next in Tech | Ep. 224: Context Around MCP For S&P Global Subscribers: Technology Primer: Model Context Protocol explained Databases and analytic services get the agentic AI treatment at Google Cloud Next 2025 IT Insider 3: A roundup for IT decision-makers Credits: Host/Author: Eric Hanselman Guests: Scott Crawford, Justin Lam Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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26:42
Context Around MCP
Linking generative AI models to the agents that are going to use them now has a standard for queries, the Model Context Protocol (MCP). Suddenly all sorts of things are vying to be your data source of choice. What could go wrong? Analysts Jean Atelsek, James Curtis and Henry Baltazar join host Eric Hanselman to provide an introduction to what MCP is, what all the fuss is about and where this is headed. Since Anthropic released the standard in November of 2024, there has been significant progress in expanding and clarifying it, but it is still very much a work in progress. Database providers and storage vendors have been the obvious participants and many others are joining in. The larger questions are around ensuring trust and transparency in this market. Basic authentication has been worked out, but more sophisticated authorization mechanisms need to be defined. The mad dash is already leading to M&A activity, with storage vendors looking to expand their opportunities and maintain their relevance. Microsoft has released its MCP definition and Google has created an agent-to-agent (A2A) protocol for direct agent interactions. There are many pieces that are coming together to enable fully agentic operations and there is still a lot of work to be done. More S&P Global Content: The 2025 Generative AI Outlook For S&P Global subscribers: Technology Primer: Model Context Protocol explained Databases and analytic services get the agentic AI treatment at Google Cloud Next 2025 IT Insider 3: A roundup for IT decision-makers Credits: Host/Author: Eric Hanselman Guests: Jean Atelsek, James Curtis, Henry Baltazar Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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28:44
Developer Experience and Automation
Developer experience is one of the areas where AI applications are showing significant return on investment, but there are significant hurdles to overcome in both changing established development patterns, as well as integrating AI tooling. Analyst Jean Atelsek and AWS vice president for developer experience Deepak Singh join host Eric Hanselman to explore the current state of AI code assistance and look at where it’s headed. Auto-complete, where the next bit of a line of code is filled in for a programmer, has been evolving over a number of years, but the arrival of agents to augment code generation and task automation is being to revolutionize software development. Changing development patterns is hard, but the benefits offer strong incentives to change habits. Where early uses had AI engines generate smaller code snippets that developers integrated, that’s changing to having AI tackle full functions that are then reviewed and corrected. Tooling around AI implementations are tailoring they way in which they interact with individual developers, enhancing their experience. Application modernization is an area where AI can shine, as it can assess a massive codebase whose authors are no longer available and provide not only documentation, but also prioritize recoding efforts. It’s a task where the hours required for manual assessment can be daunting and error prone. Leveraging AI code generation securely requires that organizations have sufficiently secure development pipelines. Mitigating risks from confabulation and errors in AI generated code is the same process as ought to be in place for human coders, an area where some less mature organizations may have some catching up to do. More S&P Global Content: The 2025 Generative AI Outlook For S&P Global subscribers: Can generative AI modernize legacy code bases? It depends Tech Trend in Focus: Generative AI in programming Generative AI Market Monitor & Forecast Credits: Host/Author: Eric Hanselman Guests: Jean Atelsek, Deepak Singh Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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FinOps – Managing Cloud and AI Costs
Managing IT costs has always been challenging and the FinOps movement is working to tackle this problem. Analysts Jean Atelsek and Melanie Posey return to the podcast to discuss their research and what they saw at the FinOps X conference with host Eric Hanselman. Cost angst has been exacerbated by the move to cloud. The shift from capital expense to operational expense has been a complicated transition for many. The infrastructure spending growth that being driven by AI initiatives has only just begun, but is already concerning. As cloud costs have become material expenses, more focus has been put on managing them. There are a host of startups that are looking to provide tools and cloud providers all have some form of cost management tooling. The shift to virtualization opened the door to optimization, but was one that only few walked through. Efforts at charge-back and show-back accounting created better visibility, but FinOps is looking to take things a step further by identifying costs early in the development cycle. Putting the vast quantities of operational data that cloud throws off to work requires a new focus. It’s another area where AI can help businesses work their way out of the looming costs that AI applications create. It requires bringing together lines of business, development teams and IT operations, but the benefits could be significant. More S&P Global Content: Webinar: AI Has Swallowed the Tech Industry: Indigestion to Follow? Cloud Shifts podcast For S&P Global Subscribers: FinOps Foundation showcases Scopes initiatives, user deployment experiences at FinOps X Day FinOps adoption expands as generative AI amplifies public cloud cost challenges – Highlights from VotE: Cloud, Hosting & Managed Services and Cloud Native FinOps Market Monitor & Forecast Credits: Host/Author: Eric Hanselman Guests: Jean Atelsek, Melanie Posey, Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
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