#ai#python#software-engineeringTesting LLM Applications Is Nothing Like Testing Regular Software — Here's What Actually Works200 unit tests passed. The chatbot still hallucinated a dentist's phone number. LLM testing needs evals, LLM-as-judge, and regression for non-determinism.23 aprel 202616 dəq.6
#ai#python#llmBuild a RAG Chatbot in 30 Minutes with LangChain and Neon PostgreSQLBuild a RAG chatbot with LangChain, OpenAI embeddings, and Neon PostgreSQL. pgvector, no Pinecone, full Python code, 30 minutes.28 mart 202614 dəq.6
#ai#llm#infrastructurevLLM vs TGI vs Ollama: Self-Hosting LLMs Without Burning Money or Losing SleepOllama peaks at 41 tok/s. vLLM hits 793. TGI is in maintenance mode. Here's the self-hosting guide I wish existed before I started.16 aprel 202615 dəq.5
#ai#llm#architectureAI Agents in Production: 94% Fail Before Week Two88% of AI agents never reach production. $547B in failed AI investments. The five gaps that kill agents and the architecture that actually survives.9 aprel 202615 dəq.5
#python#data-engineering#performancePolars vs DuckDB vs Pandas: The 2026 Decision GuidePolars is 8.7x faster than pandas. DuckDB is 9.4x faster. Both handle larger-than-RAM data. Here's when to use each — with benchmarks.5 aprel 202613 dəq.5
#career#data-engineering#mlML Engineering: The 87% Failure Rate and How to Beat ItNearly 87% of ML projects never reach production. The failures aren't about models — they're about engineering.19 fevral 202617 dəq.5
#ai#career#llmAI Engineer Roadmap 2026: From Software Developer to $206K in 6 MonthsA phase-by-phase roadmap to become an AI engineer: LLMs, RAG, agents, and what interviews actually ask.15 fevral 202614 dəq.5
#architecture#backend#performanceRate Limiting, Circuit Breakers, and Backpressure: The Three Patterns That Keep Distributed Systems AliveA missing timeout killed our checkout on Black Friday. Rate limiting, circuit breakers, and backpressure are the three patterns that prevent cascading failures.20 aprel 202621 dəq.4
#ai#llm#pythonLLM Evals Are Broken — How to Actually Test Your AI App Before Users Do65% of companies use generative AI. Almost none test it properly. Here's the eval framework that caught our $47K hallucination disaster.13 aprel 202616 dəq.4
#ai#llm#pythonStructured Output Changed How I Build LLM Apps — Pydantic, Tool Use, and the End of Regex ParsingI spent 6 months parsing LLM output with regex. Then Pydantic + structured outputs eliminated every 3 AM parsing alert. Here's the migration.15 aprel 202615 dəq.3
#ai#llm#performanceSemantic Caching Saved Us $14K/Month in LLM API CostsOur LLM bill hit $23K/month. Three layers — prompt caching, semantic caching, and model routing — cut it to $8.6K. Here's how.14 aprel 202616 dəq.3
#ai#llm#mcpMCP Explained: The Protocol Connecting LLMs to EverythingMCP went from Anthropic side project to industry standard in 16 months. Here is how it works and why it matters.29 mart 202613 dəq.3