Vibe Coding

Vibe coding is a development practice in which a person builds software by describing in natural language what they want to achieve and delegating the writing of the code to a generative AI model, instead of typing every line by hand. The term was popularized by Andrej Karpathy in early 2025 to describe a way of working in which the developer "goes with the flow" of the model's suggestions: prompt, result, adjust, repeat. The human stops being the one at the keyboard and becomes the one who directs, tests and validates the output.

The underlying idea is a change of role: the developer works more like a director than a typist. They describe the intent ("add a contact form that validates the email and saves the lead"), the AI proposes the code, and the human runs it, observes the behavior and asks for corrections in natural language. It is a concrete expression of agentic AI applied to software development, and it depends on the quality of the prompt and of the context the model receives.

In the Salesforce ecosystem, this approach becomes tangible with tools such as Agentforce Vibes, the platform's AI-assisted development environment. Bringing these practices into a production environment (with governance, testing and human review) is exactly the kind of work the Vantegrate team takes on.

How it works in practice

Vibe coding is not magic: it is an iterative loop between a human and a language model. The developer opens an assistant (an AI IDE such as Cursor, a built-in copilot, or an environment such as Agentforce Vibes), describes what they need and gets working code back. From there, the typical flow is describe, run, observe and correct: if something breaks, the human does not necessarily read the stack trace, but pastes the error back into the model and asks it to fix it. The emphasis is on the observable result, not on understanding every generated line.

This sets it apart from traditional autocomplete-assisted programming. With classic autocomplete, the human is still the author and the AI suggests snippets. In pure vibe coding, the AI writes the bulk of the code and the human validates the behavior. That difference in degree matters: it changes who holds the mental model of how the system works.

Why it matters for a business

For a company, vibe coding promises to speed up the creation of prototypes, internal tools and automations that used to require a dedicated developer or sat on the backlog. An operations analyst at a distributor in Buenos Aires can, for example, put together a small dashboard that cross-references orders with stock without writing SQL by hand, just by describing it in natural language. It lowers the barrier to entry and frees up technical teams' time for more complex problems.

But the real value shows up when you distinguish between two uses. For a throwaway prototype or a proof of concept, vibe coding is ideal: speed over polish. For software that goes to production (that touches customer data, money or critical processes), the generated code needs the same rigor as any other code: review, testing, security and maintenance. The most common mistake is confusing a prototype that "works in the demo" with a production-ready system.

Common mistakes

• Accepting code without understanding it and deploying it to production without human review, piling up invisible technical debt.
• Ignoring security: a model can generate code with vulnerabilities (injection, insecure credential handling) that the human will not catch unless they look for them.
• Assuming the AI keeps the full context of the project; in large codebases, the model loses track of earlier decisions and introduces inconsistencies.
• Skipping automated tests because "the model already tested it." The model does not run the code; it predicts plausible text.
• Not versioning or documenting, which leaves no way to audit what changed and why.

How it differs from traditional assisted programming

The line is not always sharp, but the key is who authors the code and how much human validation each line gets.

The human factor is still decisive

Vibe coding does not eliminate the developer; it changes the job. The key skill shifts from "knowing how to write code" to knowing how to describe a problem well, read a solution critically and judge whether it is correct. Mature practice combines the speed of vibe coding with human-in-the-loop practices: the human reviews what goes to production, writes or supervises the tests, and keeps control over architecture decisions. In environments such as Salesforce, where code runs on customer data and real business processes, that review is not optional: it is what separates an experiment from a reliable system.