Vibe-coding without a map: AI speed without understanding the problem

Vibe-coding —building software at speed with artificial intelligence, without serious prior design or research— accelerates delivery. That is not a myth: in days you can have screens, system connections, even a prototype that “feels” like a product.

Trouble starts when that speed is mistaken for direction. Here “map” means understanding the business problem and how the work will be done before asking AI to invent everything. At SGD that map is the Requirements Manual (Manual de Requerimiento): the project’s working guide, not paperwork. Without that map it is easy to build something large that poorly reinvented what was already there. In B2B that costs time, debt, and a product that never reaches clean production.

A recent example is Liam Powell’s essay Bend 2 and the Vibe-Coding Trap. We are not citing it to attack anyone: it shows a pattern we also see in companies when AI accelerates “building” faster than “understanding.”

At Somos Gente Digital we do not sell “prompts”. We bring software and AI into operation with judgment: technology serves the product, not the other way around.

Vibe-coding is asking an AI assistant to generate and adjust software while you steer by intuition, demos, and the feeling that “we are moving.” The loop is addictive: you describe, generate, test, fix. In a few hours there is visible progress. In a few weeks there is a system.

That speed is real. It is also incomplete. AI answers what you ask; it rarely stops you to say “this already exists in a better form” or “you are taking the hard road.” If you bring no map, it helps you build faster… in the wrong direction.

In LatAm B2B the risk grows: small teams, pressure to show progress, and the temptation to skip understanding the problem because “the AI is already building it.”

Powell writes about Bend 2, a programming language aimed at the AI era: people write rules, AI writes the rest, and a tool checks that those rules hold. In the homepage demo, stating one simple game rule already takes a lot of text; the “proof” the AI generates to support those rules runs to hundreds of lines.

His point is not “Bend is bad.” It is more useful for a product owner: vibe-coding makes it possible to assemble something large before learning enough about the problem to notice a cleaner path already existed. In the essay, the author shows that a little prior research leads to a much shorter result aligned with what the field already knew how to do.

The business lesson that matters to us: if you ask an AI to “invent a full system for X,” it will invent one. It will not, on its own, tell you that much of X is already solved and that you could stand on that. Understanding the problem and what already exists is not bureaucracy: it is the map that prevents poorly reinventing.

We attribute the argument to Powell and invite you to read the original. We use it as a bridge: how often, in custom software and AI, do we build something “impressive” without asking whether the domain already had a simpler answer?

At Somos Gente Digital the “map” is the Requirements Manual (Manual de Requerimiento): the project’s working guide, not a document to file away and not paperwork. It is the living agreement the team uses to understand the problem and how the work will be done — before asking AI to invent blindly.

Without that Manual, vibe-coding produces surface: demos, screens, happy paths. With it, the same AI speed becomes an advantage: you accelerate on decisions that are no longer improvised.

“AI to production” does not mean pasting a chat on the site. It means an AI-assisted flow lives inside real work: trustworthy data, permissions, controlled costs, and a person accountable when the model is wrong.

The bridge from Bend is clear: you can vibe-code an entire system and still miss what the field already solved better. Inside a company, you can vibe-code an “assistant” or “copilot” and poorly reinvent a flow your sales system, your ERP (the system for inventory, orders, and finance), or a serious service already covered — or build something that does not survive the first incident.

At SGD we see the pattern in three forms:

1. A prototype that becomes “product” with no owner, no tests, and no ship plan.
2. Reinventing something commodity (common and already solved) because nobody looked at the market or the internal stack.
3. Choosing tools for prompt fashion, not for the product and operations they must sustain.

If the dilemma between depending on a platform and building your own with judgment sounds familiar, we have also covered that tension when a cloud service outage forces you to ask what you actually control.

Custom software is not “ask the AI to write everything.” It is deciding what to build, what to buy, and what to connect — then using AI to accelerate those decisions.

Our approach is deliberately anti-theater:

• First the business problem and the systems map.
• Then an MVP cut (minimum viable product) that can operate, not only demonstrate.
• Then AI acceleration where it helps (repetitive code, tests, migrations, docs), with human review where it hurts (security, money, personal data, critical integrations).
• Finally operations: monitoring, costs, handoff to the team, and continuous improvement.

That is the opposite of selling prompts. It is bringing software and AI to a state the client’s team can live with.

1. Nobody can name three existing alternatives to the chosen approach.
2. The “design” lives only in the AI chat thread.
3. There is no owner for key data or for how the system ships.
4. The demo impresses, but there is no path to a test/production environment with a way back.
5. Connections to other systems are left “for later,” even though the real value sits there.
6. Technology is justified by what is trending, not by product constraints.

We are a human team at a B2B web/tech agency. We use AI every day. We also insist on the Requirements Manual — the map, the working guide — before blind speed.

In practice: an honest conversation about the problem, the Requirements Manual as the working guide, “ready for day-to-day use” criteria, and custom software when the business needs it — not when the chat suggests it. To see how that method looks, read software development that works and the rest of our services.

And if you are choosing a partner, a B2B agency checklist still helps: ownership, integrations, and operations weigh more than a reel of AI-made demos.

Is vibe-coding bad?

No. It is a powerful tool for prototyping and acceleration. It gets expensive when it replaces understanding the problem, architecture, and operations in B2B contexts where mistakes have real cost.

What is the “map”?

At SGD the “map” is the Requirements Manual (Manual de Requerimiento): the project’s working guide, not paperwork. It is the living agreement on the problem and how the work gets done, before asking AI to invent everything. Without that, you build blind even if the demo “works.”

How do you avoid reinventing with AI on a B2B project?

Start with the Requirements Manual — the working guide — and use AI to accelerate those decisions, not to invent the whole system blind.

Does Bend prove AI is useless?

No. Powell’s essay uses Bend as an example of a broader pattern: build speed without enough research into what already existed. Read it in context; we translate it into enterprise product risk.

How do we take AI to production in LatAm B2B?

With process judgment: data, permissions, costs, visibility into what is happening, and ownership (who owns it). AI accelerates; it does not replace flow design or operational responsibility.

When does custom software beat SaaS?

When your differentiator is your process, your rules, or your deep integration — and the total cost of forcing a generic tool exceeds building with control. That decision is map, not fashion.

If you are accelerating with AI and the project is growing faster than clarity, let’s talk. At SGD we help you put a map in place — and then vibe-code with direction toward production.