Claude, Vibe Coding and the False Promise of Operational Autonomy
There’s a lot of talk about Vibe Coding and agent-based workflows with Claude, and for good reason. We’re no longer limited to autocompletion; the goal today is for AI to take a requirement, consume the repository context, write the logic, build the tests, and raise a Pull Request ready for review. That operational capability exists.
The problem is the giant misunderstanding in the industry: believing that paying for the corporate license gives you operational independence from day one. The reality is harsher. Most organizations don’t have the infrastructure or processes to support this level of automation.
An agent’s autonomy isn’t a feature that comes included with the API. It demands engineering discipline, adopting Spec Driven Development (SDD) seriously when necessary, and above all, designing a well-thought-out context architecture.
A global system prompt and good SDD aren’t enough. If you have a system with multiple modules, the rookie mistake is putting all the guidelines in a single CLAUDE.md file at the project root or having multiple skills and rules in a single .claude folder. If the agent is going to touch the payments module, it needs the exclusive billing rules and context; having the database schema of other domains in memory is useless.
We could modularize it into multiple skills, but there’s a clear trade-off: injecting the listing and its descriptions penalizes the context window. At scale, this overhead generates inefficient token consumption, so this strategy only scales well in smaller projects or repositories.
For this to scale, you need to design specialized contexts and agents. In a mature backend environment, you don’t use a single instance for everything. You have an orchestrator that analyzes the ticket and routes, an isolated agent in its domain that writes the logic, a strict code reviewer (with performance rules and linters), and perhaps another dedicated solely to documentation.
If you inject the entire repository into each iteration out of sheer laziness to segment, the model will get lost in the noise, it will hallucinate, and you’ll burn millions of tokens. Eventually, it will resolve the task through corrections, but the API cost will skyrocket trying to make the AI guess a poorly managed architecture.
Think of it like when we add an engineer to the team. You don’t throw them a two-line ticket and leave them alone in front of all the source code. They require onboarding, constant collaboration, empathy to understand the end user’s problem, and adaptability to fit into each module’s conventions. Asking AI for automation requires equally structured onboarding: defining the limits of its specialty and providing a framework where agents interact without stepping on each other.
It’s a very similar process to when we implement an AI feature in our own code to automate a process that requires data modification: it’s necessary to start with a closer HITL (Human In The Loop). With Claude it’s the same — at first, you review every piece of code or commit with a magnifying glass. As the agent gains confidence, maturity, and demonstrates consistency in the domain, you automate more and give it greater freedom.
Conclusion
Attempting to skip this technical maturity stage to force early automation is a serious management mistake. Artificial intelligence isn’t here to fix your lack of architecture or your poor internal processes.
True automation and operational autonomy are conquered iteration after iteration: managing contexts with clinical precision, segmenting responsibilities into specialized agents, and demanding absolute quality in specifications. They can’t be bought with a credit card. If you have a culture of good engineering, Claude will automate entire parts of your development cycle. But if your setup is a mess, you’ll simply end up paying sky-high bills for infinite iterations you could have avoided by structuring the work properly from the start.
I’m convinced that Vibe Coding is already a standard. I apply it in my day-to-day, but with great responsibility. I don’t agree with companies that apply it solely because it’s trendy, without at least concerning themselves with the bare minimum requirements: security and efficiency.