LLM costs
Cost per action, not only per token
The right operating unit is the cost of a useful prioritization, validated brief, or accepted draft. This prevents choosing a cheap model that creates too many corrections.
A profitable AI workflow is not judged only by price per token. You need to track call volume, context size, retries, human validation, and cost per useful action.
LLM costs
The right operating unit is the cost of a useful prioritization, validated brief, or accepted draft. This prevents choosing a cheap model that creates too many corrections.
LLM costs
A more expensive model can be profitable if it reduces rework, targeting errors, and rejected messages. The test should track human validation rate, not only raw cost.
LLM costs
Each MCP workflow should have thresholds: budget per list, maximum call count, dry-run mode, logging, and automatic stop when quality drops.
Extraits citables
PurposeA profitable AI workflow is not judged only by price per token. You need to track call volume, context size, retries, human validation, and cost per useful action.
Workflow proofThe right operating unit is the cost of a useful prioritization, validated brief, or accepted draft. This prevents choosing a cheap model that creates too many corrections.
Assistant promptEstimate the cost of a Yadulink MCP workflow that triages LinkedIn leads, prepares briefs, and generates drafts, separating AI calls, context, human revisions, and budget guardrails.
Méthode de vérification
Maillage docs
AI providers
Choose the right AI assistant for each Yadulink workflow.
MCP
Connect Yadulink to Claude, ChatGPT, or an MCP-compatible assistant.
AI prompts
Ready-to-adapt prompts for running Yadulink with AI.
MCP tools
Understand which Yadulink tools to expose to an AI assistant.
API
Use Yadulink API keys without exposing your LinkedIn account.