Next Steps for Staff+ AI Engineering
Treat AI as a discipline, not a novelty, to shape how teams build, debug, and deploy software.
We'll cover the following...
Here’s a recap of Staff+ AI skills and how to take the next step:
Prompt contracts: Write prompts as contracts, with a definition of done, precedence rules, and private reasoning.
Next step: Learn schema-driven prompting and evaluation frameworks to automate CI compliance checks.
RAG: Ground answers with retrieval to reduce hallucinations, starting with
llm.txtbriefing files.
Next step: Build a full RAG pipeline with chunking, hybrid search, re-ranking, citations, and freshness monitoring.
Model ecosystems: Delegate like you would to a team; apply reasoning models for planning, mid-tier for execution, and IDE agents for incremental work.
Next step: Design a routing strategy that caps latency and cost, and logs which model did what.
Agent orchestration: Replace “mega-agents” with orchestrator–worker systems that are composable, observable, and safe.
Next step: Explore agentic design patterns that keep autonomy predictable and limit blast radius.
Where to learn more
You can get hands-on with building these essential skills in our most popular AI courses:
All You Need to Know About Prompt Engineering for mastering prompting techniques (and knowing when to use each one).
Fundamentals of Retrieval-Augmented Generation with LangChain to start building your RAG pipeline with the in-demand tool, LangChain.
Agentic System Design to understand the unique needs of agentic systems through real-world case studies from hyperscalers like NVIDIA.
Master Agentic Design Patterns to get hands-on experience with AI design patterns like orchestrator-worker, prompt chaining, routing, parallelization, and more.
Let’s move on to “Reliability Under Fire,” which is a fancy way of saying how to stop your systems (and agents) from dying when John forgets to renew a cert.