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// Knowledge Base for Sentient Systems

Insights & Frameworks
for Real-World AI

Field manuals, safety protocols, and design frameworks for teams deploying AI into production. No hype decks—only systems thinking and patterns that actually ship.

AI Safety
Design Patterns
Enterprise Copilot
Filter
New guides are added as experiments graduate from the lab.
Field Guide
~15 min read

Master the Machine, Secure the Future

Enterprise AI Usage Guide

A practical, non-fluffy playbook for rolling out AI across a firm without leaking client data, violating policy, or getting blindsided by hallucinations.

  • Color-coded “Green / Yellow / Red” usage rules for staff.
  • Real incidents (Samsung, Amazon) translated into simple protocols.
  • Clear rationale for paying for Enterprise Copilot versus “free” tools.
Framework
~10 min read

THICC Foundations for the Sentient Future

Total Holistic Infrastructure, Code & Cloud

Before you chase AGI copilots and embodied agents, you need an unbreakable base. THICC is the TinManDev way of designing the world your AI lives in—so it can scale without breaking everything around it.

  • Why infrastructure must evolve before intelligence.
  • Infra, code, and cloud patterns that assume AI-level risk and load.
  • Practical playbook to move your org toward a THICC foundation.
Framework
~12 min read

Neural Stack: Designing AI Entities, Not Agents

Persona · Knowledge · Skills · Governance

Neural Stack Theory upgrades “agents” into persistent entities with identity, memory, and governed skills. This piece walks through the core stack and shows how to grow an AI collaborator over time instead of re-prompting from zero every day.

  • Breakdown of Persona, Knowledge, and Skills layers.
  • Extended layers for intent, contracts, provenance, and safety.
  • A minimal file-based blueprint you can implement today.
Coming Soon
Playbook

Red Teaming Your AI Before the Internet Does

Internal drills for prompts, jailbreaks, and misuse.

A lightweight protocol any team can run monthly to stress-test their AI assistants, catch risky behaviors early, and update guardrails before incidents happen.

  • Scenario templates for legal, ops, and engineering.
  • Scorecards and risk levels that leadership actually understands.
  • How to feed findings back into prompts, policies, and code.