A multi-agent orchestration system routes diverse incoming requests to the right specialist and then executes each as a multi-step agentic task. The mistake most teams make is using one framework for both jobs and getting the worst of each. This is Part 4 of The Token Scarcity Playbook — assembling routing (Part 1), model-agnostic design (Part 2), and the…
Read articleAn agent framework is the harness that orchestrates a model's reasoning, tool calls, state, and multi-agent coordination. This is Part 3 of The Token Scarcity Playbook — a technical comparison of the major frameworks built so you can score them against your own needs. It centers on a decision matrix rated on the criteria that actually drive selection — ease…
Read articleA model-agnostic application is one you can move from one model to another — to capture a cheaper option or route per task — without rewriting logic or shipping silent regressions. Routing (Part 1) only pays off if your system survives the swaps. This is Part 2 of The Token Scarcity Playbook.
Read articleModel routing is the practice of sending each request to the cheapest model that can actually handle it, instead of defaulting every task to the flagship. It is the single largest cost lever in the token scarcity era — and, done well, it improves quality and cost at the same time. This is Part 1 of The Token Scarcity Playbook.
Read articleThe token scarcity era is the moment the economics of building with AI inverted — when "use the biggest model for everything" stopped being clever and started being expensive. This is Part 0 of The Token Scarcity Playbook: why every team shipping AI in 2026 is suddenly counting tokens, and the tactics that follow.
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