Codex as a Team Member: Where the Agent Falls Short in a Real-World SMM System

The practical experience of integrating an AI agent into a real-world work environment rarely matches the marketing hype. An article on Habr is a perfect example of this: the author has been using Codex for several days within his SMM system, built on the Buildin.ai platform, and honestly documents the errors that appeared literally from the very first runs.

Key context: An SMM system is not an off-the-shelf product, but a working environment consisting of databases and web pages. This means that the agent doesn’t work with an abstract API, but with a specific data structure, where an error in interpreting a field or a relationship between tables immediately results in a visible failure in the content.

The author doesn’t just describe the problems—he shares solutions that helped reduce the likelihood of these errors recurring. This is valuable: most articles about agents are either laudatory or theoretical, whereas this one follows a practical “error → fix → verification” cycle.

The full-text version is not available in the source material, so the specific list of errors and solutions from the article is worth reading in the original. But the message itself is important for anyone deploying agents in production: the first few days aren’t a honeymoon—they’re a flood of edge cases—and you need to prepare for them before, not after, deployment.

Source: All Articles in a Row / Artificial Intelligence / Habr