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The agent economy runs on ideas that didn’t exist two years ago — and vocabulary that’s still being written. Learn is where Forkast explains them: what agents actually are, how the protocols connecting them work, and what the acronyms your feed keeps using really mean.
Explainer
Generative AI creates new content — text, images, video, code, audio — by learning patterns from training data. Learn how transformers, diffusion models, and other architectures power modern AI systems.
◆ Theodore Wren
Explainer
AI alignment is the field of ensuring AI systems behave consistently with human values and intentions. Learn about outer and inner alignment, RLHF, Constitutional AI, and why alignment matters for autonomous agents.
◆ Theodore Wren
Explainer
How APIs enable digital business An API (Application Programming Interface) is a standardized contract that lets one piece of software request a service from another—without needing to know how that service works internally. When you tap “Pay” in a ride-sharing app, the app calls a payment API. When a logistics company checks a shipping rate, […]
◆ Theodore Wren
Explainer
## Why agent identity matters Traditional identity systems assume two categories: humans who authenticate with passwords or biometrics, and service accounts that authenticate with static API keys. AI agents break this model in four ways: 1. **Agents are autonomous.** They make decisions and take actions without a human pressing a button for each step. 2. […]
◆ Theodore Wren
Explainer
Agent governance is the set of policies, oversight mechanisms, and accountability structures that control how autonomous AI agents make decisions, access data, use tools, and interact with humans and other agents. It is the framework that ensures these systems operate within defined boundaries, remain accountable for their actions, and align with organizational objectives. Analogy: Think […]
◆ Theodore Wren
Explainer
Prompt engineering is the practice of designing, refining, and optimizing the text instructions (prompts) given to a large language model (LLM) to elicit reliable, useful, and accurate outputs. It is a foundational skill for building with AI — distinct from fine-tuning (which changes the model itself) and Retrieval-Augmented Generation (which adds external knowledge).
◆ Theodore Wren
Explainer
The Invisible Decision-Maker Imagine you are hiring a highly capable, tireless research assistant. You give them a complex task—say, “Find the best travel route for a multi-city trip and book the hotels.” You don’t expect them to guess the answer instantly. You expect them to look at a map, check flight availability, compare hotel prices, […]
◆ Theodore Wren
Explainer
Defining the Agentic Economy Imagine you are planning a complex business trip. Today, you might use a chatbot to find flight options, but you still have to manually book the tickets, reserve the hotel, and update your calendar. In the emerging agentic economy, you don’t do the booking. Instead, you delegate the entire workflow to […]
◆ Theodore Wren
Explainer
What Agentic Commerce Actually Means Agentic commerce represents a fundamental shift in how goods and services are bought and sold online. Instead of a human browsing a website, comparing options, and clicking “Buy Now,” an AI agent handles the entire commercial workflow — discovery, evaluation, negotiation, and payment — on behalf of the user, or […]
◆ Theodore Wren
Explainer
Shift from Chat to Action Most of us are familiar with AI as a conversational partner — a chatbot that answers questions or drafts emails. But agentic AI represents a fundamental shift. Instead of waiting for the next prompt, these systems are designed to execute goals. They break down complex objectives, decide on the necessary […]
◆ Theodore Wren