The 7 Skills You Need to Build AI Agents

Summary

The video argues that building production-ready AI agents requires much more than prompt writing. Because agents take actions—such as calling APIs, querying databases, and making decisions—the work is closer to engineering a complete software system than crafting instructions for a model.

It outlines seven important skills:

1. System design: Structure how models, tools, databases, and possibly sub-agents work together. Plan data flow, task coordination, and how components handle failures.
2. Tool and contract design: Define precise tool inputs and outputs. Strict schemas, clear requirements, and examples reduce ambiguity and prevent agents from inventing values.
3. Retrieval engineering: In RAG systems, the quality of retrieved context strongly affects performance. Important considerations include document chunk size, embedding quality, and re-ranking results for relevance.
4. Reliability engineering: Prepare for API and network failures with retries and backoff, timeouts, fallback paths, and circuit breakers.
5. Security and safety: Defend against prompt injection and other malicious or malformed inputs. Use input validation, output filtering, and permission limits so agents can access or do only what they need.
6. Evaluation and observability: Record agent decisions and tool calls with tracing. Measure success rate, latency, and cost, and use test cases and automated checks to catch regressions.
7. Product thinking: Design for human users by setting expectations, communicating uncertainty and limitations, handling errors gracefully, and deciding when to ask for clarification or escalate to a person.

Practical Guidance

For people moving from prompt engineering toward agent engineering, the presenter recommends:

• Review tool schemas and make them clear and specific, with strict types and examples.
• Investigate a real agent failure by tracing the system backward—checking retrieval results, tool selection, and schema clarity—instead of immediately changing the prompt.

The central takeaway is that reliable agents depend on well-designed systems, measurable performance, security, and thoughtful user experience—not prompts alone.

Main Speaker and Source

• Presenter: Bri Kopecki, in an IBM Technology video.