The Readiness Layer – Scaling AI Without Breaking the Business
Agentic AI will not work without the right foundations. In this final article, we focus on operational readiness. What needs to be true before you scale agents inside Salesforce? This is where strategy meets control.
The Execution Layer – Where Autonomy Becomes Real
Execution is where Agentic AI becomes real. This article explores how Salesforce enables autonomous action using Prompt Builder, Agentforce, and the Einstein 1 Studio stack.
The Process Layer – Where Logic Meets Autonomy
Automation is not enough. Agentic AI needs structure. In this article, we unpack how the process layer—flows, orchestration, business rules—enables safe, scalable, intelligent action.
The Data Layer – Why Agentic AI Needs Context, Not Just Records
AI is only as good as the data it has access to. In this article, we dive into the essential building blocks of the data layer: identity resolution, real-time signals, and trust. Without it, agents fail.
Agentic AI: What It Is, Why It Matters, and Why Now
Agentic AI is not a buzzword. It is a new model for scaling capability inside your business. This article defines what it is, why it matters now, and how Salesforce is making it real.
Track Your Prompts Like Code
As your agent matures, its prompt logic risks becoming invisible and unmanageable. This post shares a delivery-tested method to keep prompts versioned, testable and traceable so your team can debug and evolve AI behaviour with confidence.
The Cost of Choosing the Wrong AI Model in Agentforce
Choosing the right AI model is not just a technical decision, it shapes your speed, cost, and outcomes. Here's how we map models to jobs in Agentforce and avoid common delivery pitfalls.