12-factor11 min read
The 12-Factor App in 2026 — Revisiting Cloud-Native Best Practices
The 12-Factor App methodology remains relevant in 2026. Review each principle with modern interpretations for Kubernetes, multi-cloud, and monorepos.
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Google's A2A Protocol — How AI Agents Talk to Each Other in Production
Explore Google's Agent-to-Agent (A2A) protocol for production multi-agent systems. Learn agent cards, task lifecycles, and how to orchestrate multiple AI agents at scale.
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backend7 min read
Abuse of Public Endpoints — When Your Free Tier Becomes Someone Else's Compute
Your free-tier AI image generation endpoint is being used to generate 50,000 images per day by one account. Your "send email" endpoint is being used as a spam relay. Your "convert PDF" API is a free conversion service for strangers. Public endpoints need abuse controls.
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backend5 min read
Accidental Full Table Scan — The Query That Brought Down Production
The query works fine in development with 1,000 rows. In production with 50 million rows it locks up the database for 3 minutes. One missing WHERE clause, one implicit type cast, one function wrapping an indexed column — and PostgreSQL ignores your index entirely.
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a-b-testing7 min read
A/B Testing LLM Models and Prompts — Replacing Guesswork With Data
Use shadow mode, statistical significance testing, and gradual rollouts to confidently replace your LLM models and prompts.
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ai-agents12 min read
AI Agent Architecture Patterns — ReAct, Plan-Execute, and Reflection Loops
Deep dive into core agent patterns: ReAct loops, Plan-Execute-Observe, reflection mechanisms, and preventing infinite loops with real TypeScript implementations.
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ai-agents12 min read
AI Agent Error Recovery — When Agents Fail, Hallucinate, or Get Stuck
Master error detection, reflection prompting, alternative tool selection, human-in-the-loop escalation, and graceful degradation for production agents.
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ai-agents11 min read
Evaluating AI Agents — Trajectory Testing, Tool Use Accuracy, and Task Completion
Master agent evaluation: trajectory analysis, tool accuracy, task completion rates, efficiency scoring, and LLM-as-judge evaluation frameworks.
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ai-agents13 min read
AI Agent Memory — Short-Term Context, Long-Term Storage, and Episodic Recall
Build memory systems for AI agents with in-context history, vector stores for semantic search, episodic memories of past interactions, and fact-based semantic knowledge.
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