Avoiding Common Pitfalls

00:00 With agentic coding becoming more capable, it’s easier than ever to fall into traps. Here are three of the most important pitfalls to watch out for. The first pitfall is assuming that one agent type handles everything.

00:14 IDE agents excel at interactive real-time editing. Terminal agents are built for complex, multi-file work. PR agents catch issues asynchronously after you push.

00:26 And cloud agents handle longer, more autonomous tasks. Each mode has a sweet spot. Matching the workflow to the task matters more than picking a single tool and using it for everything.

00:39 The next pitfall is ignoring privacy and compliance constraints. Many cloud agents run on remote infrastructure. PR agents operate in shared repositories, while cloud-backed IDEs and terminal agents send your code to external APIs for inference.

00:57 Before adopting any agent, check whether your code is allowed to leave your local machine and review your company’s policies on AI tool usage. Some teams can only use local models or self-managed environments.

01:11 The third pitfall is over-automating without review. Assume that AI-generated code contains mistakes. It may have subtle bugs, weak exception handling, or patterns that don’t match your team’s conventions.

01:26 Review all generated code carefully before merging. The more autonomous the agent is, the more important the developer oversight becomes. A careful review is much cheaper than a production failure.

01:37 Coding agents pay off when you treat them as collaborators, not replacements. Pick the right agent for each task, respect your team’s privacy boundaries, and keep a human reviewer in the loop.

01:50 In the next lesson, you’ll wrap up with a summary of everything you’ve learned.