Author: Collin Pace - Page 4
How to Use Large Language Models for Marketing, Ads, and SEO
Learn how to use large language models for marketing, ads, and SEO without falling into common traps like hallucinations or lost brand voice. Real strategies, real results.
- Sep 5, 2025
- Collin Pace
- 8
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Continuous Documentation: Keep Your READMEs and Diagrams in Sync with Your Code
Keep your READMEs and diagrams accurate by syncing them with your codebase using automation tools like GitHub Actions, ReadMe.io, and DeepDocs. Stop manual updates. Start living documentation.
- Aug 31, 2025
- Collin Pace
- 10
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Security KPIs for Measuring Risk in Large Language Model Programs
Learn the essential security KPIs for measuring risk in large language model programs. Track detection, response, and resilience metrics to prevent prompt injection, data leaks, and model manipulation in production AI systems.
- Aug 23, 2025
- Collin Pace
- 5
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Autoscaling Large Language Model Services: How to Balance Cost, Latency, and Performance
Learn how to autoscale LLM services effectively using the right signals-prefill queue size, slots_used, and HBM usage-to cut costs by up to 60% without sacrificing latency. Avoid common pitfalls and choose the right strategy for your workload.
- Aug 6, 2025
- Collin Pace
- 10
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KPIs and Dashboards for Monitoring Large Language Model Health
Learn the essential KPIs and dashboard practices for monitoring large language model health in production. Track hallucinations, latency, cost, and user impact to avoid costly failures and build trustworthy AI systems.
- Jul 29, 2025
- Collin Pace
- 8
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Supervised Fine-Tuning for Large Language Models: A Practical Guide for Real-World Use
Supervised fine-tuning turns generic LLMs into reliable tools using real examples. Learn how to do it right with minimal cost, avoid common mistakes, and get real results without needing an AI PhD.
- Jul 18, 2025
- Collin Pace
- 6
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