LangChain vs LlamaIndex vs DSPy vs Custom: How to Pick the Right AI Orchestration Framework for Your Product
How to pick between LangChain, LlamaIndex, DSPy, and a custom framework layer for your AI product build.
Software decisions compound. A pricing model picked in week three of a SaaS launch sets the unit economics for years. A custom CRM that fits your sales motion saves a hire by month three. An AI layer scoped well in month one delivers measurable lift by quarter one. Three solid pieces from this archive should remove at least a week of guessing from the next decision in front of you.
Walk in mid-decision and walk out with a sharper view of it. Whether you are weighing build vs buy, picking a framework, scoping an AI layer that looked easy in the demo, redesigning a UX flow that loses users at step three, or deciding whether to keep patching a migration that quietly grew over months. The next decision should feel less guesswork-shaped.
Topics here range across AI implementation, SaaS strategy, custom CRM, HR tech, e-commerce, software engineering, data and analytics, design and UX, and domain-specific software for financial markets, TradingView, and real estate. Plus inside stories: short reads on what we learned building real products for real businesses.
What the Model Context Protocol actually is, which products benefit from adopting it now, and how to adopt without betting on the still-evolving standard.
How to Keep Production AI From Doing Embarrassing (or Dangerous) Things
How to See What Your AI Actually Does in Production
How to Pick the Right AI Agent Framework for Your Product
How to pick between LangChain, LlamaIndex, DSPy, and a custom framework layer for your AI product build.
What fine-tuning data really needs to look like, the 3 signs your data is not ready yet, and what nobody tells you about the labelling that produces it.
The 3 levels of "industry-trained AI" being sold today, how to tell which one you are being pitched, and when to buy versus build.
The 7 admin AI workflows already cutting staff hours in schools across every size, and the 3 ideas that keep getting pitched but fall apart on real students.
How to pick between open-source models (Llama, Mistral, Qwen) and closed-source models (GPT, Claude, Gemini) for a custom product build.
One article a fortnight. No fluff, no product pitches — just substantive thinking on building vertical software that works in the real world.