Closing content gaps: more technologies, more comparisons, and cost guides with no invented prices

The technology library was missing entries for tools that come up constantly in real client conversations: Google Gemini, GitHub Copilot, Cursor, the Model Context Protocol (MCP), Hugging Face, LlamaIndex, and named vector database options (Pinecone, Weaviate, pgvector) that had previously been lumped into one generic 'vector database' page. Each got its own page rather than a shared umbrella entry, because they're not interchangeable in a real build.

Comparisons grew the same way: Claude vs GPT vs Gemini, Cursor vs GitHub Copilot, LangChain vs LlamaIndex, Pinecone vs Weaviate vs pgvector, and custom software vs SaaS. We deliberately left out benchmark percentages in all of them — model benchmark numbers go stale within months and get cherry-picked easily, so the comparisons are written around documented ecosystem and structural fit instead.

We also shipped a new Buyer Guides section for the 'how much does this cost' questions that show up before almost every serious inquiry. Every guide names qualitative cost drivers — what pushes a project's price up or down — tied to the same budget bands already on our contact form, and never states an invented 'average project cost.' If we don't have a real number, we don't publish one.