Open-Source Platforms for LLM Evaluation

Compare open-source LLM evaluation platforms that add observability, automated metrics, and CI/CD testing to reduce hallucinations and production errors.

How to Deploy Agentic AI in Production Safely

Discover key strategies for deploying agentic AI in production, including lessons learned, best practices, and real-world examples from industry leaders.

Complete Guide to Evaluating LLMs for Production

Discover the ultimate guide to evaluating LLMs for production, from benchmarks to real-world applications and efficiency insights.

Reconciling AI Benchmarks and Developer Productivity

Explore the gap between AI benchmark performance and real-world developer productivity in this in-depth analysis.

How to Add LLM Testing to GitHub Actions

Automate LLM testing in GitHub Actions: secure API keys, organize datasets, run Latitude evaluations, and fail builds on regressions.

LLM Prompts with External Event Triggers

Choose the right trigger—webhooks, queues, polling, or SSE—to balance latency, scalability, and reliability for production LLM workflows.

Open-Source vs Proprietary LLMs: Ethical Trade-Offs

Choosing between open-source and proprietary LLMs forces a trade-off: transparency and control versus centralized safety and convenience.

Scaling LLMs with Serverless: Cost Management Tips

Practical strategies to cut serverless LLM costs: model right-sizing, prompt and context optimization, caching, batching, routing, and real-time observability.

How Production AI Agents Work: Reliability & Practices

Discover how production AI agents operate, their reliability, and best practices based on recent empirical findings.