Tag: prompt engineering

Role, Rules, and Context: Structuring Prompts for Enterprise LLM Use

by Phillip Ramos

Structured prompts using role, rules, and context are the key to reliable enterprise LLM use. Learn how role-based prompting, chain-of-thought reasoning, and iterative testing improve accuracy, reduce hallucinations, and align outputs with business needs.

Reinforcement Learning from Prompts: How Iterative Refinement Boosts LLM Accuracy

by Phillip Ramos

Reinforcement Learning from Prompts (RLfP) automates prompt optimization using feedback loops, boosting LLM accuracy by up to 10% on key benchmarks. Learn how PRewrite and PRL work, their real-world gains, hidden costs, and who should use them.

NLP Pipelines vs End-to-End LLMs: When to Use Each for Real-World Applications

by Phillip Ramos

NLP pipelines and end-to-end LLMs aren't competitors-they're complementary. Learn when to use each for speed, cost, accuracy, and compliance in real-world AI systems.

Prompt Sensitivity in Large Language Models: Why Small Word Changes Change Everything

by Phillip Ramos

Small changes in how you phrase a question can drastically alter an AI's response. Learn why prompt sensitivity makes LLMs unpredictable, how it breaks real applications, and proven ways to get consistent, reliable outputs.