Vibe Coding: A durable workflow for building software with AI agents

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Bol Vibe coding is not asking an AI for random code and hoping for the best. It is still software engineering. You define the outcome, shape the architecture, organize the workspace, give the agent the context and tools it needs, and decide what counts as correct. The agent writes more of the code; you keep ownership of the system. Vibe Coding: A durable workflow for building software with AI agents is a practical guide for developers, founders, and first-time agent users who want a workflow that survives changes in models, products, and hype. Inside, you will learn how to: - choose and install a first coding agent - create a clean workspace before touching the code - turn vague intent into an executable plan - manage context, permissions, MCP, skills, and subagents - understand why the harness matters as much as the model - verify, debug, recover, and ship with evidence >The book begins with the simplest possible mistake: asking an AI to "make a calculator" without saying where it runs, what it must do, or what it should look like. From there, it shows how precise direction and engineering judgment turn prompting into durable software work. You do not stop being the developer because you stop typing every line. You become responsible for a larger loop.

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Vibe coding is not asking an AI for random code and hoping for the best. It is still software engineering. You define the outcome, shape the architecture, organize the workspace, give the agent the context and tools it needs, and decide what counts as correct. The agent writes more of the code; you keep ownership of the system. Vibe Coding: A durable workflow for building software with AI agents is a practical guide for developers, founders, and first-time agent users who want a workflow that survives changes in models, products, and hype. Inside, you will learn how to: - choose and install a first coding agent - create a clean workspace before touching the code - turn vague intent into an executable plan - manage context, permissions, MCP, skills, and subagents - understand why the harness matters as much as the model - verify, debug, recover, and ship with evidence >The book begins with the simplest possible mistake: asking an AI to "make a calculator" without saying where it runs, what it must do, or what it should look like. From there, it shows how precise direction and engineering judgment turn prompting into durable software work. You do not stop being the developer because you stop typing every line. You become responsible for a larger loop.


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