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36 articles
200 unit tests passed. The chatbot still hallucinated a dentist's phone number. LLM testing needs evals, LLM-as-judge, and regression for non-determinism.
A missing timeout killed our checkout on Black Friday. Rate limiting, circuit breakers, and backpressure are the three patterns that prevent cascading failures.
Ollama 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.
I spent 6 months parsing LLM output with regex. Then Pydantic + structured outputs eliminated every 3 AM parsing alert. Here's the migration.
Our LLM bill hit $23K/month. Three layers — prompt caching, semantic caching, and model routing — cut it to $8.6K. Here's how.
65% of companies use generative AI. Almost none test it properly. Here's the eval framework that caught our $47K hallucination disaster.
88% of AI agents never reach production. $547B in failed AI investments. The five gaps that kill agents and the architecture that actually survives.
Polars 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.
uv is 10-100x faster than pip and replaces 7 tools. ruff replaces 10 linting/formatting tools. Migration takes 5 minutes. Here's how.
Python 3.14's free-threaded build is officially supported. 10x speedups on CPU-bound tasks, 51% package compatibility, and Django runs without the GIL.
uv, ruff, Polars, Pydantic v2, orjson — all Rust under the hood. 13 Python tools rewritten in Rust, all 10-100x faster. The 95/5 pattern explained.
T-strings return a Template object, not a string. That one change enables SQL injection prevention, XSS-safe HTML, and shell safety built into the language.
LangChain chains steps in a line. LangGraph builds state machines. Most comparisons miss this fundamental difference.
If a server dies mid-workflow, Temporal resumes exactly where it left off. $5B valuation, 183K developers, used by Stripe and Netflix.
A realistic month-by-month roadmap with salary data, skill requirements, and what most guides get wrong.
MCP went from Anthropic side project to industry standard in 16 months. Here is how it works and why it matters.
Build a RAG chatbot with LangChain, OpenAI embeddings, and Neon PostgreSQL. pgvector, no Pinecone, full Python code, 30 minutes.
OpenAI acquired Astral, the company behind uv, ruff, and ty. What it means for Python's most loved tools.
Backend engineers average $174K in 2026. Here is the real roadmap — languages, databases, cloud skills, and a 12-month plan.
How I bootstrapped birjob.com from 14 browser tabs to 10,000+ job listings with $25/month infrastructure.
FastAPI handles 3x more requests. Django ships products faster. Here is when each Python framework wins.
When Graph RAG doubles retrieval accuracy and when it wastes your money. Benchmarks, costs, frameworks, and a decision framework.
A2A lets AI agents discover, delegate, and coordinate without knowing each other's internals. Here is how it works.
They sound similar but the day-to-day, salary ceiling, and career trajectory are completely different. Here is how to choose.
Nearly 87% of ML projects never reach production. The failures aren't about models — they're about engineering.
A phase-by-phase roadmap to become an AI engineer: LLMs, RAG, agents, and what interviews actually ask.
Razer RTX 5090, MacBook M4 Max 128GB, ThinkPad P16, Framework 16, and a $1,300 budget pick. Compared.
A 20-week roadmap to become a data analyst: SQL, Python, BI tools, AI integration, portfolio strategy, and what interviews actually test.
Four years of building Azerbaijan's biggest job aggregator as a solo founder on $25/month infrastructure.
RAG tutorials teach the easy 20%. Here are the five production problems they skip — and how to actually solve them.
Redis is not just a cache. Sorted sets, streams, pub/sub, and HyperLogLog changed how I architect everything.
I replaced GPT-4 with 7B models in production. Same quality, 95% cheaper. Here is why small language models are winning.
How I killed a 2,400-line Python ETL pipeline and replaced it with 300 lines of SQL using CTEs, materialized views, and pg_cron.
Honest comparison of Airflow, Dagster, and Prefect for data pipelines in 2026. Code examples, pricing, and what I actually use.
What actually works for web scraping in 2026: tools, stealth browsers, AI extractors, anti-detection, and the legal reality.
A practical guide to fine-tuning LLMs with LoRA, QLoRA, Unsloth, and OpenAI. Real costs, real code, and when to fine-tune vs RAG.