📅 Jan 10, 2026: Saturation Diagnostic Link: https://youtu.be/JtOW6oLL2MU
"It works but it’s super slow... ok great... looks like a bug... maybe one of the memory layers is saturating. I think the whole deal is gonna be that... Yeah, that’s it, the layer was saturating. It should embed from MT to LT too... but everything is slow, everything is slow... WOOO, that’s not a good summary! Okay! Gotta change everything, gotta change everything... (whistling). I'm singing, when it doesn't work, that's when you learn, right? Well, that's what you gotta tell yourself... In my pov terminal... Yeah, I didn't make a pretty interface, or even an interface at all yet. Ok, I get it, it's memory layer saturation. Ok, we're gonna fix this!"
The Reality: No fluff, no UI. Just the engine choking on a budget laptop. This is the exact moment I realized the bottleneck was the management of the ST/MT/LT layers. It’s slow, it’s raw, but the diagnostic is done.
🪵 2026/03/26 DEV LOG #02: ΩMEGA — Memory Efficiency & Local Sustainability
Objective: Validation of a constant-memory architecture for local LLMs (Mistral 7B) on consumer-grade hardware (Intel i7). 📊 Performance Analysis (200-Round Stress Test)
https://www.youtube.com/watch?v=Pev7Z3lxKQg
Memory Management: Confirmed RAM Homeostasis. The system maintained a footprint between 130MB and 400MB throughout the session. By implementing a tiered "Sedimentation" process (Short-Term → Medium-Term → Long-Term), we bypassed the linear context-growth bottleneck typical of standard RAG or LangChain implementations.
Thermal & Compute Load: The process remained sustainable on a single CPU. Periodic "breathing" cycles allowed for background summarization without causing thermal throttling or system instability.
Tiered Storage: Successfully demonstrated the automated transition of data through three levels of volatility.
Semantic De-duplication: The Long-Term memory (LT) currently lacks a similarity filter, leading to redundant data entries ("echo effect") during high-frequency cycles.
Recall Discrepancy: Initial failure in the recall benchmark due to a file-path synchronization error between the test environment and the production database.
I/O Latency: Peak latencies of 60s observed during concurrent inference and database compression.