Augment Code puts your team’s collective knowledge — codebase, documentation, and dependencies — at your fingertips via chat, code completions, and suggested edits. 

Get up to speed, stay in the flow and get more done. Lightning fast and highly secure, Augment works in your favorite IDEs and Slack.

Augment Code

Every engineer using AI runs into the same wall: you can copy someone’s “magic prompt” from a screenshot, but it rarely survives contact with your own codebase.

That’s because prompts aren’t just one clever sentence. The way you structure system prompts, tools, skills, and user messages determines whether your agents listen carefully or ignore half your instructions. 

In our next Engineering Coffee Chat, we will walk through practical prompting tips and agent design patterns drawn from our own production stack. We'll talk about how we think about the four layers of prompting (system prompts, tools, skills/guidelines, and user messages), and how you can combine them to get reliable behavior instead of “vibes‑based” results. 

In this session, we’ll cover:

*   **Prompting as infrastructure, not a one‑off spell:** How to separate concerns across system prompts, tools, skills, and user messages, and what each layer is actually responsible for in a robust agent. 
*   **Concrete prompting tips that actually move the needle:** Why clarity, specificity, and consistency matter more than clever wording; how to use emphasis, examples, and repetition effectively; and how to avoid self‑inflicted contradictions that confuse models. 
*   **Designing agents that choose the right tools:** How to use tool availability and descriptions as prompts, when to remove tools like *grep* so agents lean on your context engine, and why too many MCP tools can quietly tank performance. 
*   **Keeping context under control:** Why reusing the same thread forever is a trap, how to think about context windows, and when to lean on planning docs or evals instead of ever‑longer conversations. 
*   **Becoming AI‑native in your day‑to‑day:** Practical habits you can adopt this week, like asking models to propose verification steps, evaluate alternative approaches, or refine your own prompts.

Bring your own questions about prompts that keep “going off the rails,” tool overload, or making your team more AI‑native.
