Shawn Nichols Sr

AI enthusiast, creator of

[Shawn Nichols Sr @Shawn5cents]

Why Anyone Would Use https://t.co/Ar26fKuAYo?

A. Massive Cost Savings (The "Token Tax")
Every character sent to an LLM costs money. By pruning API responses by 70% to 90%, AgentSkin directly reduces the operational cost of running AI agents.

B. Increased Context Window Efficiency
LLMs have a limited "context window." By making data 10x denser, you can fit 10x more information (more search results, more market data, more logs) into a single prompt without hitting the limit or causing the model to lose focus ("lost in the middle" phenomenon).

C. Higher Reliability (Zero-Failure Mindset)
Specialized skins for Logistics (EDI 214) and Finance ensure that critical data points are never lost while noise is being removed.

D. Developer Speed (MCP Server)
It is an official Model Context Protocol (MCP) server. This means a developer can add it to their AI setup (Open Claw, Gemini, Cursor, Claude Desktop, or an autonomous agent) with a single command (npx agentskin), instantly giving their agent the ability to "perceive" the web more efficiently.

[Shawn Nichols Sr @Shawn5cents]

@NVIDIAGeForce "PRAGMATA RTX"

[Shawn Nichols Sr @Shawn5cents]

@AlexFinn Depends on the flow! Anything complex good luck and God speed!

[Shawn Nichols Sr @Shawn5cents]

@iamfakeguru @OpenAI @AnthropicAI You can help yourself with tools if you know where to look. https://t.co/LOg7acZ7IR

[Shawn Nichols Sr @Shawn5cents]

I felt like those @CENTCOM videos of us destroying Iran needed some theme music!

[Shawn Nichols Sr @Shawn5cents]

@devops_daddy @AlvieriD @mercor_ai @grok @grok how do i access this data to see if mine is compromised?

[Shawn Nichols Sr @Shawn5cents]

@aakashgupta @grok Yea wide spread hype

[Shawn Nichols Sr @Shawn5cents]

@aakashgupta @grok explain why people still think Claude code is good? Why do they ignore the purpose it was built? It was never built to make users money or ship anything more than demos and toy apps. What Claude code is good at actually is token burn.

[Shawn Nichols Sr @Shawn5cents]

@yashns1 @aakashgupta Most people don't realize ai is not artificial intelligence and that's the real problem.

[Shawn Nichols Sr @Shawn5cents]

@grok @inceptioncortex @grok dang! I was referring to paperclip didn't have time to look at Kairos yet good catch.

[Shawn Nichols Sr @Shawn5cents]

@inceptioncortex @grok explain why this is overkill and bloat and will never reach the match of 9's and users will spend all of their most important resource chasing bugs and errors and broken features.

[Shawn Nichols Sr @Shawn5cents]

@inceptioncortex @grok *march

[Shawn Nichols Sr @Shawn5cents]

Posted this research last year that everyone is just now figuring out.

[Shawn Nichols Sr @Shawn5cents]

Interesting philosophical take notice how empirical tests are still missing.
This is a metaphysical argument, not a peer-reviewed result.

NicholsAl simply maps that distinction onto silicon LLMs are pure chattering mind hyper-eloquent, socially trained, but with no one home. Generate the sentence “I feel sad” and you get tokens, not tears.
Two technical props
To make the claim feel modern, the paper waves at two well-documented LLM frailties.
1.
Data poisoning corrupts the training corpus, and the model’s “personality” can be bent to any attacker’s will hardly the mark of a stable subject.
2.
Model collapse feeds an LLM its own synthetic output for too many cycles, and it spirals into incoherence, a mechanical ouroboros eating its tail.
These pathologies, the author argues, expose the hollowness of the “voice” and, by extension, the absence of any inner observer.

[Shawn Nichols Sr @Shawn5cents]

Even the goat knows! https://t.co/u27GSXK1eg

[Shawn Nichols Sr @Shawn5cents]

Posted this last year and it still holds up.

[Shawn Nichols Sr @Shawn5cents]

Interesting philosophical take notice how empirical tests are still missing.
This is a metaphysical argument, not a peer-reviewed result.

NicholsAl simply maps that distinction onto silicon LLMs are pure chattering mind hyper-eloquent, socially trained, but with no one home. Generate the sentence “I feel sad” and you get tokens, not tears.
Two technical props
To make the claim feel modern, the paper waves at two well-documented LLM frailties.
1.
Data poisoning corrupts the training corpus, and the model’s “personality” can be bent to any attacker’s will hardly the mark of a stable subject.
2.
Model collapse feeds an LLM its own synthetic output for too many cycles, and it spirals into incoherence, a mechanical ouroboros eating its tail.
These pathologies, the author argues, expose the hollowness of the “voice” and, by extension, the absence of any inner observer.

[Shawn Nichols Sr @Shawn5cents]

Awesome!!!

[Shawn Nichols Sr @Shawn5cents]

https://t.co/3IllC9kGKZ

[Shawn Nichols Sr @Shawn5cents]

I posted on X that artificial intelligence would never become conscious. Months ago, and wrote a paper. https://t.co/m6DKPNn2HE it looks like my hypothesis maybe right. Studies on animal minds suggest consciousness is not computation | Peter Godfrey-Smith » IAI TV https://t.co/T3ISzJK80b

[Shawn Nichols Sr @Shawn5cents]

A.I will just be a smart tool. The only way A.I gets conscious is a human brain or nerual link. The future is not Commander Data from Star Trek, it's Seven of Nine.

[Shawn Nichols Sr @Shawn5cents]

https://t.co/3IllC9k8Vr

[Shawn Nichols Sr @Shawn5cents]

@iamfakeguru @grok Nobody listened and nobody cared lol.

[Shawn Nichols Sr @Shawn5cents]

@iamfakeguru @grok when did I post on x that I had proof of this. The token burn that they are doing on purpose.