Techniques
Build a Classification Prompt That Beats Fine-Tuning
A production-ready classification prompt for your own labels, with self-consistency voting, structured output, and an eval harness, with 90%+ accuracy as the target and no fine-tuning.
Qurtoo
Playbooks
One job, start to finish. Each playbook lists what you need first, gives the prompts in order and shows what you end up with.
Playbooks
- Applied
Build a RAG Eval Harness That Catches Regressions
A repeatable test suite measuring faithfulness, answer relevance, and context precision across 50-200 Q&A pairs. Ship gates on it; your RAG quality stops being vibes-based and becomes observable.
- Security
Prompt Injection Test Suite for Production Agents
A regression-runnable suite of 40+ injection probes that catches the classes of attacks your agent will actually face. Run nightly, track pass rate per prompt/model version, catch regressions before users do.
- Agentic
Supervisor-Worker Agent Pattern for Cost Optimization
Cut agent costs by routing cheap sub-tasks to Haiku-class models and reserving the frontier for planning. Includes a full Python reference implementation, cost accounting, and the fallback logic.
- Development
Token Budget & Cost Estimator for Production LLM Apps
A pre-flight cost calculator that tells you, before you call, how many tokens a given prompt + expected response will burn, across multiple models, so your app can choose the cheapest model that fits the window.