| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 01. Building provider-agnostic GenAI integrations | |||
| 01. Choosing the right integration pattern.mp4 | 7.6 MB | ||
| 01. Choosing the right integration pattern.srt | 4.7 KB | ||
| 02. Demo Communicate with an AI service.mp4 | 23.7 MB | ||
| 02. Demo Communicate with an AI service.srt | 7.2 KB | ||
| 02. Versioning and evolution of GenAI APIs | |||
| 01. Why AI APIs change.mp4 | 5.3 MB | ||
| 01. Why AI APIs change.srt | 4.4 KB | ||
| 02. Demo Underlying model changes.mp4 | 16.9 MB | ||
| 02. Demo Underlying model changes.srt | 6.4 KB | ||
| 03. Interoperability standards | |||
| 01. Understanding Model Context Protocol (MCP).mp4 | 5.5 MB | ||
| 01. Understanding Model Context Protocol (MCP).srt | 3.6 KB | ||
| 02. Demo MCP-enabled architecture.mp4 | 24.9 MB | ||
| 02. Demo MCP-enabled architecture.srt | 7.9 KB | ||
| 03. Understanding agent-to-agent (A2A) communication.mp4 | 4.8 MB | ||
| 03. Understanding agent-to-agent (A2A) communication.srt | 2.9 KB | ||
| 04. Demo Extend the Customer Support Assistant.mp4 | 22.4 MB | ||
| 04. Demo Extend the Customer Support Assistant.srt | 7.7 KB | ||
| 04. Governance for enterprise GenAI systems | |||
| 01. Applying AI governance frameworks.mp4 | 4.5 MB | ||
| 01. Applying AI governance frameworks.srt | 3 KB | ||
| 02. Demo Review architecture.mp4 | 33.3 MB | ||
| 02. Demo Review architecture.srt | 7.8 KB | ||
| 03. Implementing auditability and compliance.mp4 | 3.7 MB | ||
| 03. Implementing auditability and compliance.srt | 3.1 KB | ||
| 04. Demo Extend the Customer Support Assistant.mp4 | 31.4 MB | ||
| 04. Demo Extend the Customer Support Assistant.srt | 6.6 KB | ||
| 05. Governing AI evolution.mp4 | 4.5 MB | ||
| 05. Governing AI evolution.srt | 3.6 KB | ||
| 05. Designing enterprise interoperability.mp4 | 4.1 MB | ||
| 05. Designing enterprise interoperability.srt | 3.4 KB | ||
| 06. Demo Redesign the Customer Support Assistant.mp4 | 19.1 MB | ||
| 06. Demo Redesign the Customer Support Assistant.srt | 6.3 KB | ||
| 03. Versioning and feature management.mp4 | 4.6 MB | ||
| 03. Versioning and feature management.srt | 3.6 KB | ||
| 04. Demo Versioning the Spring Boot application.mp4 | 30.9 MB | ||
| 04. Demo Versioning the Spring Boot application.srt | 7.9 KB | ||
| 05. Migration and regression testing.mp4 | 4.6 MB | ||
| 05. Migration and regression testing.srt | 2.8 KB | ||
| 06. Demo Simple regression evaluation workflow.mp4 | 31.8 MB | ||
| 06. Demo Simple regression evaluation workflow.srt | 6.6 KB | ||
| 03. Building a provider-agnostic AI layer.mp4 | 6.1 MB | ||
| 03. Building a provider-agnostic AI layer.srt | 3.7 KB | ||
| 04. Demo Refactor the Spring Boot application.mp4 | 24 MB | ||
| 04. Demo Refactor the Spring Boot application.srt | 7 KB | ||
| 05. Standardizing AI contracts.mp4 | 3.5 MB | ||
| 05. Standardizing AI contracts.srt | 3 KB | ||
| 06. Demo Contracts simplify provider migration.mp4 | 23 MB | ||
| 06. Demo Contracts simplify provider migration.srt | 5.6 KB |
Ensuring Interoperability in GenAI Systems
https://WebToolTip.com
Released 10/2026
By Catalin Tudose
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Advanced | Genre: eLearning | Language: English + subtitle | Duration: 1h 27m 20s | Size: 357.4 MB
Modern GenAI applications often become tightly coupled to individual AI providers, making them difficult to evolve, migrate, and govern as APIs, models, and interoperability standards rapidly change.
Modern GenAI applications often become tightly coupled to individual AI providers, making them difficult to evolve, migrate, and govern as APIs, models, and interoperability standards rapidly change. In this course, Ensuring Interoperability in GenAI Systems, you'll gain the ability to design interoperable, provider-agnostic GenAI applications that remain maintainable, portable, and compliant throughout their lifecycle. First, you'll explore how to build standardized AI integrations using common API patterns, provider abstractions, and secure communication mechanisms. Next, you'll discover strategies for managing API evolution through versioning, feature management, and emerging interoperability standards such as Model Context Protocol (MCP) and Agent-to-Agent (A2A). Finally, you'll learn how to apply governance, compliance, auditability, and enterprise best practices to interoperable GenAI system designs. When you're finished with this course, you'll have the skills and knowledge of GenAI interoperability needed to build enterprise AI applications that can evolve confidently across providers, technologies, and regulatory requirements.
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