Category: AI Strategy & Governance - Page 3

Governance Committees for Generative AI: Roles, RACI, and Cadence

Governance committees for generative AI ensure ethical, compliant, and safe AI use. Learn the essential roles, RACI structure, meeting cadence, and models that work-backed by real-world data from Fortune 500 companies.

How to Prompt for Performance Profiling and Optimization Plans

Learn how to ask the right questions to uncover real performance bottlenecks in your software. Use profiling tools effectively, avoid common traps, and build optimization plans that actually improve speed without wasting time.

Standards for Generative AI Interoperability: APIs, Formats, and LLMOps

MCP is the new standard for generative AI interoperability, enabling seamless tool integration across vendors. Learn how APIs, formats, and LLMOps are converging to make enterprise AI scalable and compliant.

Key Components of Large Language Models: Embeddings, Attention, and Feedforward Networks Explained

Understand the three core parts of large language models: embeddings that turn words into numbers, attention that connects them, and feedforward networks that turn connections into understanding. No jargon, just clarity.

Vibe Coding Adoption Roadmap: From Pilot Projects to Broad Rollout

Vibe coding lets anyone turn plain language into working apps-but only if you start small, refine with humans, and scale with rules. Learn the real roadmap from pilot to rollout.

Operating Model for LLM Adoption: Teams, Roles, and Responsibilities

A clear operating model for LLM adoption defines teams, roles, and responsibilities to avoid costly failures. Learn the essential roles like prompt engineers and LLM evaluators, how to structure cross-functional teams, and why most LLM projects fail due to organizational gaps-not technical ones.

Tool Use with Large Language Models: Function Calling and External APIs

Function calling lets large language models interact with real-time data and external tools using structured JSON requests. Learn how it works, how major models differ, where it shines, and what pitfalls to avoid.