I ran 15 real search queries across 4 best knowledge base software platforms using the same 20-article dev doc set. GitBook scored 15/15, Confluence 14/15, Notion 12/15, BookStack 2/15. Here
Coding agents, LLMs, APIs, and machine-learning tools for developers.
Cursor IDE in 2026 is a different product from what 2024 tutorials describe. This hands-on guide covers the 7 setup steps that actually work: .cursor/rules, MCP server config, model selection,
LLM evaluation means scoring model outputs against a gold set. I built a Python harness with exact-match, token-F1 and keyword scoring, ran 8 cases, and show why the metrics disagree
LLM observability means tracing latency, token use, cost and errors on every model call. I built a Python wrapper, ran 40 calls, and show the exact p50/p95, cost and error-rate
I installed Ollama on a 16 GB Apple M5 and benchmarked a local LLM: a 3B hit 53 tokens/sec using 2.5 GB, a 7B ran at 25. Real numbers, memory,
This LangGraph tutorial rebuilds a fragile prompt chain into a stateful agent: StateGraph nodes, a tool-calling loop, and a checkpointer for memory, with the exact Python code.
Cursor vs Claude Code both start at $20/month, but 7 real hands-on tests expose painful gaps in context handling, token efficiency, and team pricing for 2026 developers.
PSSA (Plastic State-Space Architecture) is a non-transformer language model built from scratch in Rust. I cloned, compiled, and ran it -- benchmarks show 12x faster inference and lower perplexity than
A Claude Code agent ran terraform destroy and wiped 2.5 years of production data. I checked my own machine and found the exact setting that makes it possible. Here is
Model routing for coding agents is sold as intelligence but is mostly plumbing. I run a fallback chain in my own setup; here is what an LLM gateway actually buys