Cognitive Tempo

devagile
Written By Brian Conn

Summary

Cognitive Tempo refers to the pattern and rhythm of how someone processes information and makes decisions. Normally, this refers to fast and impulsive vs slow and methodical. Combined with Anticipatory Processing, Cognitive Tempo can be both fast and methodical.

Description

In high-pressure scenarios like production incidents, wall clock time is extremely important when resolving the issue. Debugging takes time, and incident commanders must preload decisions before SMEs complete their debugging so they can minimize the processing time before taking action on the system or instigating additional debugging. Constantly considering the decision tree is inefficient (many of the scenarios never happen), but it optimizes the two metrics that matter: time to resolution and thoroughness.

With the advent of AI coding assistants, Cognative Tempo is equally important during development to increase productivity and stay in a flow state. AI agents may take minutes to consider and implement changes. That time can either be spent waiting (and risk exiting the flow state) or considering how to evaluate the agent’s response, what to implement or tweak next, or how to test the code the agent will write.

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Cognitive Tempo

Cognitive Tempo refers to the pattern and rhythm of how someone processes information and makes decisions. Normally, this refers to fast and impulsive vs slow and methodical. Combined with Anticipatory Processing, Cognitive Tempo can be both fast and methodical.

Anticipatory Processing

Anticipatory processing is an approach where you think about potential outcomes while current actions are still resolving, creating a continuous cycle of action and preparation. While waiting for an action (such as making a change during a production incident or asking an AI coding assistant to write code), consider the outcomes so that once the action resolves, you’re able to immediately take the next action, maximizing Wait Time Utilization.

Key Alerting Metrics

Good alerting is critical to operating a SaaS (or any other software) platform. Good alerts are timely, actionable, understandable, and correct. In this context, correct means minimizing false positives (alerting when there is not an issue) and false negatives (not firing when there is an issue).

Key Alerting Metrics are four metrics to monitor a whole system, subsystem, or microservice based on customer pain which all production engineers can understand.

Brian Conn https://connsulting.io
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Anticipatory Processing