Tag: prompt engineering
Fixing AI Hallucinations: Practical Mitigation Strategies for Generative Models
Stop trusting blind guesses. Learn practical strategies like RAG, prompt constraints, and verification loops to reduce AI hallucinations and boost reliability.
- Sep 22, 2026
- Collin Pace
- 0
- Permalink
Cut LLM Costs: Architecture Decisions That Save Money Without Losing Quality
Discover six proven architecture decisions to cut LLM costs by 30-80% without sacrificing quality. Learn about model routing, semantic caching, and prompt optimization strategies.
- Sep 11, 2026
- Collin Pace
- 0
- Permalink
How to Teach LLMs to Say 'I Don’t Know': Reducing Hallucinations with Uncertainty Prompts
Learn how to reduce LLM hallucinations by teaching models to say 'I don't know'. Explore US-Tuning, uncertainty prompts, and practical implementation steps for reliable AI.
- Aug 7, 2026
- Collin Pace
- 10
- Permalink
How to Stop LLMs From Drifting and Repeating in Long-Form Text
Learn how to stop LLMs from drifting off-topic and repeating themselves in long-form text. Discover strategies like RAG, prompt engineering, and parameter tuning to maintain coherence.
- Jul 26, 2026
- Collin Pace
- 7
- Permalink
Multimodal Prompting Guide: Combining Text, Image, and Audio for Generative AI
Master multimodal prompting to combine text, images, and audio in generative AI. Learn how to use models like Gemini 1.5 Pro for better accuracy, cost management, and real-world applications.
- Jul 22, 2026
- Collin Pace
- 7
- Permalink
In-Context Learning Explained: How LLMs Adapt to Prompts Without Retraining
Discover how In-Context Learning enables LLMs to adapt to new tasks via prompts without retraining. Learn the mechanics, best practices, and limitations of few-shot learning.
- Jun 10, 2026
- Collin Pace
- 5
- Permalink
Prompt Sensitivity in Large Language Models: Why Wording Changes Output
Discover why small wording changes cause big output swings in LLMs. Learn how to measure prompt sensitivity using ProSA, compare model robustness, and apply proven strategies like GKP to build reliable AI applications.
- Jun 6, 2026
- Collin Pace
- 5
- Permalink
What Counts as Vibe Coding? A Practical Checklist for Teams
Learn what vibe coding really is, how it differs from traditional AI pair programming, and get a practical checklist to implement it safely in your team.
- Jun 1, 2026
- Collin Pace
- 7
- Permalink
Reinforcement Learning from Prompts: Iterative Refinement for LLM Quality
Discover how Reinforcement Learning from Prompts (RLfP) automates prompt engineering for LLMs. Compare PRewrite and PRL, understand costs, and learn implementation strategies.
- May 22, 2026
- Collin Pace
- 0
- Permalink
How to Stop AI Hallucinations: Mastering Constraints and Extractive Prompting
Stop AI hallucinations and improve output reliability. Learn how to use constraints, extractive prompting, and role-playing to get accurate, high-quality AI answers.
- Apr 18, 2026
- Collin Pace
- 10
- Permalink
Chain-of-Thought in Vibe Coding: Why Explanations Must Come Before Code
Discover how Chain-of-Thought prompting transforms vibe coding by requiring LLMs to explain logic before writing code, reducing errors and speeding up debugging.
- Apr 15, 2026
- Collin Pace
- 7
- Permalink
Prompt Libraries for Generative AI: Governance, Versioning, and Best Practices
Prompt libraries boost AI productivity but need strong governance and versioning. Learn how to prevent bias, meet compliance, and track changes. Real examples from PromptHero and FlowGPT. Key strategies for 2026.
- Feb 4, 2026
- Collin Pace
- 9
- Permalink
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