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AI Landscape & Players

Who makes what, and how to choose — the labs and the field.

  1. The Map: Who Makes What (2026)Intro7 min readA plain-language guide to the major AI labs - OpenAI, Anthropic, Google DeepMind, Meta, Mistral, xAI, and DeepSeek - what they actually ship, and how to think about the landscape without the hype.
  2. OpenAI vs Anthropic vs Google: What Each Lab Is Actually BuildingIntro8 min readGPT, Claude, and Gemini each come from a different theory of what AI should be. This plain-language breakdown covers product philosophy, model strengths, and which shop to reach for when building something real.
  3. Open-Weight Models: Llama, Mistral, DeepSeek, and Qwen ExplainedCore9 min readOpen-weight AI models let you download, run, and fine-tune powerful LLMs on your own hardware - but "open" means different things for different models. Here's what builders need to know.
  4. Frontier vs Open: How to Choose a ModelCore8 min readA practical decision framework for builders: when to reach for a frontier closed model, an open-weight model, or a fine-tune - based on cost, control, latency, and task type.
  5. The Inference Layer: Groq, Together, Fireworks, and CerebrasCore8 min readInference speed and cost are their own competitive frontier. Meet the providers sitting between the model labs and your app - and why choosing the right one matters.
  6. Where the Field Is Heading: A 12-18 Month View for BuildersDeep9 min readReasoning models, million-token context, and multi-agent systems are reshaping what you can build with AI. Here is an honest, grounded look at where the field is heading and what to prepare for.