Promptsv1.0.0

A company deploys an LLM to handle customer inquiries. Using this skill, they define task success (resolution rate), constraints (no false promises), few-shot examples of good responses, and an evaluation set with edge cases. They iterate on prompts safely, monitor for quality regressions, and roll back if needed.

An e-commerce platform uses prompts to generate consistent, SEO-friendly product descriptions. The workflow ensures output format (bullet points, length limits), includes few-shot examples for different product types, and builds an eval set to check for factual accuracy and tone. Changes are canaried and monitored via click-through rates.

A health tech startup summarizes clinical notes using LLMs. The skill helps define strict constraints (no hallucinated medical facts, citation required), create a rubric for success, and build adversarial eval sets with multilingual patient data. Iterations are logged per version, and regression tests ensure safety.

A fintech company generates quarterly reports from raw data. The workflow specifies output JSON schema, length limits, and must-not rules (e.g., no forward-looking statements without disclaimer). Evaluation sets include adversarial cases (market downturns). Prompt versions are tracked, and canary deployments monitor for hallucination.

A legal tech platform drafts contracts and disclaimers. This skill guides the definition of task success (clarity, compliance), constraints (jurisdiction-specific clauses), and few-shot examples from previous contracts. Eval sets include edge cases (ambiguous terms). Regression testing ensures no drift in legal accuracy.

Offer consulting services to enterprises that need robust prompt workflows for production LLM applications. Revenue comes from hourly consulting or project-based fees for setting up evaluation sets, iteration protocols, and monitoring dashboards.

Build a SaaS platform that hosts prompt versioning, evaluation suites, regression tests, and canary deployments. Customers subscribe monthly to manage their prompts with CI/CD pipelines and monitoring.

Develop training courses and certifications for prompt engineering using this deep workflow. Revenue comes from course fees and certification exam costs, targeting developers and AI practitioners.