Building with LLMs

Scope

Covers

• Building and shipping LLM-powered features/apps (assistant, copilot, light agent workflows)
• Prompt + tool contract design (instructions, schemas, examples, guardrails)
• Data quality + evaluation (test sets, rubrics, red teaming, iteration loop)
• Production readiness (latency/cost budgets, logging, fallbacks, safety/security checks)
• Using coding agents (Codex/Claude Code) to accelerate engineering safely

When to use

• “Turn this LLM feature idea into a build plan with prompts, evals, and launch checks.”
• “We need a system prompt + tool definitions + output schema for our LLM workflow.”
• “Our LLM is flaky—design an eval plan and iteration loop to stabilize quality.”
• “Design a RAG/tool-using agent approach with safety and monitoring.”
• “We want to use an AI coding agent to implement this—set constraints and review gates.”