Hacking the algorithm is a dead end. We are building the Audience-Cognition-Codex, a uniquely complex open-source project that uses Scheme for symbolic narrative logic and Julia for high-performance RevOps automation. We aren't building a bot; we are building a strict, programmatic "gym" for digital creators to force progressive overload on their content creation skills. No black-box LLM noise, just pure symbolic computation and strict execution flows. Looking for contributors who understand cognitive modeling and systems architecture. Read the technical manifesto here. 👇
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OpenCreatorKinetix
Julia and Scheme research engine for creator training, audience retention, symbolic narrative analysis, RevOps discipline, progressive overload, and measurable content skill acquisition.
OpenCreatorKinetix
OpenCreatorKinetix is an open-source training engine for creators who want to improve retention, narrative clarity, and publishing discipline through progressive overload.
The project does not promise viral shortcuts. It treats creator skill like strength training: measure the weak point, prescribe a hard exercise, increase the load, deload when necessary, and repeat until the skill becomes durable.
Created by Ciprian Stefan Plesca.
Public Repository Description
OpenCreatorKinetix is a Julia and Scheme research engine for creator training, audience retention, symbolic narrative analysis, RevOps discipline, progressive overload, and measurable content skill acquisition.
Suggested GitHub topics:
julia, scheme, creator-economy, revops, progressive-overload, audience-retention, attention-modeling, symbolic-ai, content-creation, ab-testing, analytics, training-engine, open-source, education, mit-license
Why This Exists
Most creator tools optimize symptoms: trends, templates, captions, thumbnails, or one-off script generation. OpenCreatorKinetix focuses on the structural causes of poor performance:
- weak hooks
- …
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