# Source report summary: Teleodynamic AI is an approach where a system’s structure and parameters co-evolve under resource constraints.  In pract

**Evidence label:** Architectural inference  
**Reviewed UTC:** 2026-06-26T18:37:04Z  
**Raw source path:** `docs/source-reports/raw-markdown/teleodynamic-ai-is-an-approach-where-a-systems-structure-and-parameters-co-evolve.md`  
**SHA-256:** `fc41a09c9a863b76acbc7e694a80113e8a6a103f0c62ce18b0a3384a9c912db3`

## Source type

User-supplied Markdown report preserved as local project source material. It is not treated as a peer-reviewed paper, a deployment incident, or proof that any described scenario is currently occurring.

## What this report contributes

**Teleodynamic AI** is an approach where a system’s structure and parameters co-evolve under resource constraints. In practice for LLMs, this suggests adding or pruning small *skill modules* only when the expected performance gain exceeds their cost. A **skill module** here means a self-contained, specialized sub-model or adapter that provides a distinct capability (e.g. summarization, translation, or domain knowledge). Users can choose combinations of these tiny LLM modules, which are then downloaded (as serialized model files) into the browser and run via a Rust/WASM runtime.

## Main concepts detected

- Executive Summary
- Teleodynamic AI & Skill Modules
- State-of-the-Art Tiny LLMs and Modular Architectures
- Tiny LLMs
- Modular Architectures
- Model Formats and Serialization for Browser Delivery
- Rust/WebAssembly Runtimes and Browser APIs
- Module Composition & Orchestration Patterns
- Dependency Management, Packaging, and Download Strategies
- Performance, Latency, and Throughput Tradeoffs

## Site interpretation

The report is used to expand Cognivirus.com as a critical, evidence-bound observatory. Its strongest contribution is scenario language for understanding why small interchangeable components, LoRA adapters, model breeding, code beading, human incentives, frugal deployment, and teleodynamic selection can become governance problems when they are coupled into a transition graph.

## Publication boundary

The public site should cite this as a source dossier, not as established empirical evidence. Operational replication, evasion, social manipulation, steganography, backdoor construction, exploit, or autonomous-spread instructions must not be reproduced in public-facing pages. Safe content may be paraphrased into risk analysis, control design, and evidence-maturity guidance.

## Related site areas

- `/apex-threat/self-replicating-multi-lora-ecosystems`
- `/control/adapter-reproduction-boundaries`
- `/research/uploaded-source-dossier-index`
- `/reference/source-report-preservation-policy`