Tag: Agentic AI

This post compares ChatGPT to traditional retrieval-augmented generation (RAG) and the Progress Agentic RAG solution, highlighting the difference between AI tools built for personal use and those designed to serve as governed knowledge layers across an organization.

ICYMI: Juan Mendoza on the Rise of Volitional Personalization and the Collapse of Traditional Martech Assumptions

If 2023–2024 were the years of pilots and prototypes, 2025–2026 will be about orchestration, governance and scale. The signal across serious researchers is consistent: adoption is widespread and business impact concentrates where companies redesign workflows, measure outcomes and hard-wire trust and controls into the stack. McKinsey reports that ~80% of companies use generative AI (GenAI), yet most still aren’t seeing material earnings contribution, because scaling practices and operating models lag the hype. This gap is a roadmap that can be leveraged by Frontier Firms and individuals looking for an advantage (or many) in today’s AI-powered world.

Discover how agentic RAG combines Retrieval-Augmented Generation with autonomous AI agents to deliver accurate, context-aware and trustworthy responses. Learn why this advanced architecture outperforms traditional RAG for enterprise AI by facilitating dynamic workflows, compliance and efficiency.

Discover how to use OpenAI’s structured output feature to return predictable, schema-compliant JSON responses from LLMs.