Video by CNCF [Cloud Native Computing Foundation] via YouTube
CNCF CTO Chris Aniszczyk shares why it’s never too early to get involved in cloud native, and the many ways to contribute beyond code. Start at contribute.cncf.io.
Learn how to scale open-source remediation across 50,000+ repositories using OSERA standards and new tooling.
Dov Katz (Managing Director at Morgan Stanley) addresses the massive operational challenge of remediating software vulnerabilities across enterprises maintaining tens of thousands of source code repositories. He details how the OSERA (Open Source Enterprise Resiliency Alliance) initiative establishes low-risk back-patching tooling – such as the open-source Risk Navigator – and unifies financial industry standards to push back against fragmented, unstandardized private security patches.
🗽 Catch Us in New York! Join global financial leaders shaping open-source supply chain standards and enterprise security at OSFF New York on November 4–5, 2026.
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🕒 Timestamps:
0:00 Managing Security Across 50,000+ Source Code Repositories
1:00 OSERA Tools & Operating Model: Local Scans & Low-Risk Back-Patching
2:14 Setting Industry Standards: Pushing Back on Proprietary Patches
3:20 Standardized Naming Conventions: Unifying the Voice of the Industry
📊 The Problem: The Enterprise Repository Patching Flood
Large financial institutions maintain tens of thousands of source code repositories (often exceeding 50,000 repos). When vendors and third parties flood the market with uncoordinated, private patches lacking standardized version numbers or uniform labeling, enterprise platform teams face paralysis. Without agreed-upon naming conventions, institutions cannot safely determine upgrade paths or automate remediation across their entire software estate without risking production breakage. 🏗️ The Solution: OSERA Tooling & Unified Naming Standards
Dov Katz outlines OSERA’s dual approach to scaling vulnerability remediation: Risk Navigator Tooling: Scanning internal software estates locally to isolate "dead-end" dependencies and execute low-risk, adjacent-version back-patches instead of forcing dangerous major version upgrades. Collective Industry Voice: Establishing clear, standardized naming conventions and public back-patching principles so institutions can present unified requirements to patch providers and design partners.
⚙️ Why This Matters for Financial EngineeringEliminating Upgrade Friction:
Standardized patch metadata allows automated tooling and agentic fleets to parse and apply dependency updates across 50,000+ repositories deterministically. Safe Space Collaboration: Financial institutions work together in a neutral venue to mutualize patch capacity and compel upstream suppliers to adhere to enterprise security standards.
Managing security at scale is a significant hurdle for financial institutions. Patching vulnerabilities individually is no longer sufficient when dealing with thousands of repositories. This session outlines the OSERA framework, designed to move beyond fragmented fixes toward a unified industry approach for the software supply chain.
By implementing consistent security standards, teams can prioritize effectively and reduce technical debt. We explore how tools like Risk Navigator facilitate this, offering a path to deploy critical patches within hours rather than weeks. This proof of concept demonstrates how an open operating model can streamline your entire maintenance lifecycle.
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Dave is just a normal guy with a normal job that he doesn’t like that much. That is, until he meets Leo, and gets the job he never imagined. Action, adventure, betrayal, love, loss, and some serious weirdness happen throughout this science fiction thrill-ride.
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=== Timestamps ===
00:00 Beginning
00:01 Introduction to Zima Board 2
00:37 Hardware
02:27 Project 1 – Get Streaming
05:48 Hardware impressions for Project 1
Video by Open Data Science and AI Conference via YouTube
MCP’s Biggest Rewrite: Statelessness, Tool Design, and Agent Skills
The Model Context Protocol (MCP) is evolving toward a stateless architecture designed to make AI agent systems easier to scale and operate in production.
In this episode, host Sheamus McGovern speaks with Kyle Stratis, founder of Stratis Data Labs and author of AI Agents with MCP, about the latest MCP changes, MCP clients and servers, tool design, state management, security, and why Agent Skills and MCP are complementary rather than competing approaches.
Learn what these changes mean for building more scalable, reliable, and production-ready AI agents with MCP.
00:00 MCP Servers vs. Agent Skills: What’s the Difference?
00:47 AI Agents with MCP: Introduction with Kyle Stratis
02:25 From Software Engineering to AI Agent Development
05:51 AI Agent Evals, Guardrails & Common Engineering Mistakes
08:45 Building AI Agents with the Model Context Protocol (MCP)
12:36 AI Agents vs. Agentic Workflows: Key Differences
16:03 MCP Architecture: Connecting AI Agents, Tools & Data
18:23 MCP Clients Explained: The Overlooked Part of Model Context Protocol
21:06 Stateless MCP Architecture: What Changed in the Latest MCP Spec
24:44 AI Agent Memory & State Management with MCP
27:08 Error Handling, Retries & Long-Running AI Agent Workflows
29:04 MCP Security: Clients, Servers & Trust Boundaries
33:01 MCP Tool Design: How Many Tools Should an AI Agent Have?
36:18 MCP vs. REST APIs: Why Wrapping API Endpoints Doesn’t Work
40:45 MCP Tool Discovery, Tool Selection & Context Management
44:26 Is MCP Dead? MCP vs. Agent Skills Explained
49:25 MCP + Agent Skills: How They Work Together
53:18 How to Design Better MCP Tools for AI Agents
57:13 The Future of MCP & AI Agent Development
59:17 Final Advice for Building Production AI Agents
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See how McCarthy Building Companies uses SAP SuccessFactors HCM to build an employee data foundation for growth, retention, and faster workforce decisions.
McCarthy Building Companies is a 100% employee-owned construction leader with 160 years of history and 8,000 employees across the United States. As the company continues growing, it needs to manage the complexity of a mobile workforce, 300 different unions, and employees moving from project to project across changing job sites.
With SAP SuccessFactors HCM, McCarthy has created a core source of truth for employee data. By going live with Employee Central, Onboarding, and Learning at the same time, the company built a foundation that helps leaders better understand employees, support growth, and make more informed workforce decisions.
That visibility matters in an industry where people are the product. McCarthy now has a more holistic view of its workforce, helping managers make better, faster decisions and support employee retention. While industry turnover is typically around 17% to 18%, McCarthy’s turnover is closer to 10%, a difference the company attributes to managers having better information about employees. For McCarthy, this is about more than improving HR today. It’s about building a platform for the future.
Learn how McCarthy Building Companies is building a future-ready workforce on an employee data foundation: https://sap.to/6057B1IvT7
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As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/6052B1Ivp8
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