Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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When Anthropic released Opus 4.5 on November 24, 2025, the reaction was muted. Another model, another set of benchmarks, another incremental improvement. But in the weeks that followed, something happened that no benchmark could capture. Claude Code, Anthropic’s agentic coding product built on top of Opus 4.5, began accomplishing tasks that had never been possible before. Complex, multi-hour coding projects were being completed autonomously, correctly, without human intervention at each step.
The model hadn’t changed. What changed was the harness. The orchestration layer that sits between the user and the model, directing how the model is called, when it is called, what tools it uses between calls. How its output is verified before being delivered back.
In the chatbot paradigm, the relationship is simple: a human types a prompt, the model generates tokens, and those tokens are delivered to the human. The model is the product. In the agentic paradigm, a human gives an instruction to a software system, the agent, which then decides how to decompose that instruction into subtasks, which models to invoke for each subtask, which deterministic tools to employ for verification, and how to iterate on failures without returning to the human for guidance. The model is a component. The harness is the product. It is the lens we bring to our work at Monetizely. (see Figure 4)
This distinction is the single most important structural fact about the economics of agentic AI.
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