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LLMs for Code Generation: A Deep Dive Into Benchmarks, Best Practices, and Limits
Which LLMs write the best code in 2026, what the benchmarks actually measure, how to get better output, and where generated code will still burn you.
OpenAI API and Batch Processing Guide for Developers
Complete OpenAI API reference for 2026 - model catalog, chat completions, function calling, structured outputs with JSON schema, embeddings, rate limits, and cost management.
Prompting for Data Extraction: Structured Output From Unstructured Text
A complete guide to extracting structured data from text with LLMs - field definitions, JSON schemas, function calling for guaranteed structure, missing field handling, batch efficiency, and accuracy limits.
Few-Shot Example Selection: How to Choose Examples That Actually Help
The science of choosing few-shot examples - diversity, representativeness, ambiguity, relevance, dynamic selection, negative examples, ordering effects, and the empirical 3-5 example sweet spot from Brown et al. 2020.
ReAct Prompting: How to Make LLMs Reason and Act in Alternating Steps
ReAct prompting alternates Thought, Action, and Observation steps so the model commits reasoning before choosing an action. Here is how to use it effectively in 2026.
Negative Prompting: How to Break LLMs Out of Their Default Patterns
Models default to generic structures, hedging phrases, and formulaic openings. Negative prompts tell them what not to do and break those patterns effectively.
Advanced System Prompt Patterns for Production AI Applications
Production AI applications need system prompts built from specific patterns: persona anchoring, format specification, knowledge boundaries, escalation, and self-correction.
Testing HTTP APIs Effectively: Beyond the Happy Path
Unit vs integration tests, test database strategies, auth in tests, and making sure your 400, 401, 403, 404, and 500 responses are all verified.
Debugging Techniques That Actually Work: Beyond console.log
Breakpoints, binary search debugging, the scientific method applied to bugs, and when a proper debugger is faster than any amount of logging.
Coolify vs Fly.io vs Render: Self-Hosted and Managed Hosting Alternatives to Vercel
Coolify for cost control, Fly.io for global latency, Render for simplicity. Here is the honest breakdown of each platform and when to use it.
Drizzle ORM Guide: TypeScript-First SQL That Stays Close to the Database
Drizzle defines your schema in TypeScript, builds SQL-like queries with full type safety, and ships a smaller bundle than Prisma. Here is how it works.
Sentry Error Tracking Guide: From Setup to Production Insights
Sentry groups errors, captures breadcrumbs, and records session replays. Here is how to set it up in Next.js and use it to actually fix bugs faster.
