🛠️ DevLog – Rough Design: CognitiveLevel Module for Smarter Network Task Evaluation We've drafted the initial version of the CognitiveLevel contract - a new module that manages performance-based levels for nodes handling network tasks, modeled after patterns used in NodeStats and NodeReputation. 🔹 What It Does - Tracks per-node task outcomes: success/failure counts, streaks, and average token size - Oracle nodes can upgrade/downgrade a node’s level based on historical performance 🔹 How It Fits - The Cognitive module (which manages network-level tasks) reports completion to CognitiveLevel - Oracle nodes evaluate each miner's task result, including token length, validity, and latency - On each new task, Cognitive queries CognitiveLevel to dynamically set prompt complexity based on each node's current level - Because oracle nodes are sharded, evaluations can be distributed for scalability 🔹 Why This Matters - Enables precision orchestration across a heterogeneous network (from Pi to H100) - Ensures high-load or mission-critical tasks go to high-reliability nodes - Forms the backbone for long-term task scheduling, tiered incentives, and trustworthy decentralized inference 🔹 What's Next - Will require significant updates to oracle and miner codebases - Oracle nodes must track token counts for every task to verify level eligibility - Miner logic will need programmable prompt templates that adjust with each node's assigned level This is still an early brainstorm/PoC, but it unlocks a smarter, more adaptive Cortensor network. We'll keep refining design through this and the next phase. #Cortensor #DevLog #CognitiveLevel #NetworkTasks #AdaptiveInfra #DecentralizedAI #DePIN

🛠️ DevLog – Designing CognitiveLevel for Smarter Network Task Routing We're in the design phase of a new module called CognitiveLevel, which manages capability-aware node selection for network tasks - similar to how NodePool manages ephemeral nodes for user tasks. 🔹 Core Concept - CognitiveLevel tracks each node’s abstracted performance tier (e.g. CPU/GPU class, reliability) - Only the Oracle can upgrade or downgrade node levels Scoring is based on recent network task samples (accuracy, response time, etc.) 🔹 How It Fits - The Cognitive module powers the network task layer - it evaluates and routes user jobs before they are passed into user task workflows - create, prepare, and precommit steps will query CognitiveLevel to ensure only eligible nodes are selected 🔹 Why It Matters - Just as NodePool filters nodes for user task session reliability, CognitiveLevel enables performance-aware orchestration at the network layer - Ensures heavier AI workloads land on proven, high-capacity nodes Still early-stage, but sets the stage for trustable and scalable AI inference. #Cortensor #DevLog #CognitiveLevel #NetworkTasks #NodeRanking #DePIN #DecentralizedAI #AIInfra