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AI Agents, Explained: The Loop Behind the Label
A beginner-friendly map of what makes a system agentic, how the model–tool loop works, and when a simpler workflow is the better design.
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Runnable IntelligencePractical AI notes by Ubaid MemonThe reading path
Three foundations for understanding agents.
Begin with the agent loop, follow a real tool call, then separate the systems hidden inside the word “memory.” Each article stands alone.
01AI agents · Foundational guideAI Agents, Explained: The Loop Behind the LabelA beginner-friendly map of what makes a system agentic, how the model–tool loop works, and when a simpler workflow is the better design.9 min read02Tool use · Practical explainerHow Tool-Using AI Agents Work: A Weather Assistant, Step by StepFollow one tool call from a user request to a validated result, then see what changes when an agent can take actions instead of only reading data.10 min read03Context & memory · Field guideAgent Memory, Explained: Context, Retrieval, and StateSeparate four mechanisms that are often called memory, then use the distinctions to design and test an agent that remembers the right things.10 min read
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About the author
Ubaid Memon
Ubaid is a senior software engineer exploring AI agents, intelligent systems, and the engineering choices that turn a promising demo into useful software. Runnable Intelligence makes those ideas clear through practical examples and source-backed explanations.