Introduction and Overview › Glossary for the Networking Language · 2 min read
Feedback describes how the effects of an action influence the action itself.
Experiences, responses, and results flow back into decisions, rules, or behavior.
This enables individuals, groups, and entire networks to learn, adapt, and evolve.
This creates learning-capable systems instead of rigid structures.
A river does not simply end in the sea.
Through evaporation, water rises again, condenses into clouds, and returns as rain to new landscapes and back to its source.
This illustrates feedback:
What a system produces affects its own conditions in return.
Decisions in the TEIKEI network are not made solely at a central level.
They emerge through feedback between:
This is important because supply is not just planned digitally.
It is carried out, tested, adjusted, and developed on-site.
A shared platform only remains part of a living network if practice can influence it:
Without this feedback, a linear control model emerges.
Decisions made by a responsibility circle are, if necessary, fed back to affected circles.
An error is often a sign that information, feedback, and review were insufficient.
Then, the process, delegation, or feedback mechanism is adjusted.
Embodied knowledge arises through time, experience, repetition, responsibility, and feedback.
Swarm intelligence and collective intelligence also rely on feedback among many participants.
The recursive network economy relies on feedback rather than mere execution.
The Agora should be a space where supply, responsibility, and feedback can be collectively managed.
This is about reliable feedback between people and places, not central control.
Feedback describes how the effects of one’s own actions are perceived and incorporated into the next action, allowing a network to learn from its practice.
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By the TEIKEI editorial team, with support from AI (Claude)
Created on October 11, 2026 · Last updated on October 11, 2026
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