The AI Distribution Playbook
Lessons Learned From SaaS & Streaming Giants
Show me any business and I will look at it from a distribution strategy angle, force of habit I guess.
It was about time I took a closer look at how LLM models like OpenAI’s ChatGPT, Google’s Gemini, Mistral AI’s Le Chat, Claude and DeepSeek, design their partnership strategy.
Much has been said about the partnership deals they strike to feed their models (e.g. News Corps, Axel Springer and most recently The Guardian) so let me focus on the distribution strategy of the models themselves. As much as we like to think they are unstoppable, they need to answer the same crucial question streamers do: how do I reach users at scale? This is the question I’ll try to answer today.
Today at a glance:
Key LLM Models Overview
Lessons Learned From SaaS & Streaming Giants
A New Kind Of Bundle
Mentioned in this edition: OpenAI, Google, Mistral AI, DeepSeek, Claude, Free, Microsoft, Amazon, Netflix, Apple, Samsung
Key LLM Models Overview
LLMs adopt a SaaS (Subscription As A Service) model which follows the traditional cloud software distribution approach: users subscribe directly to access AI services via web, mobile platforms or APIs. Users only need to focus on utilising the software, as maintenance and infrastructure management are handled by the service provider.
→ Key characteristics of SaaS distribution:
• Subscription tiers (free, premium, enterprise).
• Direct web access & mobile apps (self-service).
• API integrations (for businesses and developers).
• Feature-based and Pay-per-use models (e.g., OpenAI API pricing based on token usage).
→ Breakdown of each key LLM Model’s user base, pricing, distribution:
How many users do they have? Let’s go with a visual representation to give you a quick snapshot of where they’re at: