Engine-native planning
+Assign work to value engines instead of inherited departments.
Systems Intelligence Model for AI-first companies
A conscious operating layer for AI-first companies.
Build your next-generation company around the Systems Intelligence Model: four value engines, four coordination drivers, and AI agents that know how the whole system is supposed to work.
Made for conscious builders, not org charts.
SimOne is the front door for testing whether SIM can become a practical agent-company interface for students, founders, and readers of the Conscious Systems book (free download).
Retrieval-first memory
+Bring in knowledge when the task needs it, not as prompt ballast.
Human meta-stewardship
+Agents operate; the builder holds coherence, intent, and judgment.
Built from the agent-company breakthrough, upgraded by SIM
Paperclip showed the pattern. SimOne changes the operating system.
Traditional agent-company demos still tend to inherit old corporate categories. SimOne starts one layer deeper: design the system first, then let agents operate inside a conscious architecture.
From Paperclip to SIM-native structure
Paperclip is an elegant base for agentic company building. SimOne changes the organizational assumption: agents are not CEO/CMO/CFO substitutes; they are stewards of Product, Customer, Cash, and Skills engines.
A shared Systems Intelligence memory
By default, agents should reason from the same SIM knowledge layer: the 26-chapter Conscious Systems playbook, the course architecture, and your venture-specific context.
Less context ballast, more task-fit retrieval
Instead of continually injecting full files and swollen memory into every agent run, SimOne is designed around retrieval-first context and human approval at engine boundaries.
Systems Intelligence Model RAG
Every agent starts from the same map of the venture.
The Systems Intelligence Model gives agents a shared language for value creation: Product, Customer, Cash, and Skills engines, coordinated by Innovation, Governance, Interaction, and Culture drivers.
Course-grounded
Agents inherit the Systems Intelligence course language instead of generic startup advice.
Venture-adaptive
Your product, customer, cash, and skills data shape the working memory of each engine.
Creator-backed
The base model is wired to SIM as taught by its creator, then adapted to the builder's real system.
simone.context = retrieve(SIM + venture + task)
// Smaller prompts. Better shared memory. Clearer human approval at engine boundaries.
The operating replacement for CEO/CMO/CFO silos
Four engines. Four drivers. One coherent company.
Product Engine
Offer, roadmap, delivery
Customer Engine
Discovery, trust, demand
Cash Engine
Pricing, revenue, runway
Skills Engine
Capability, learning, leverage
Join the first SimOne early access list.
We’ll use this list for alpha access, demo updates, and the first cohort learning loop. For the deeper framework, explore the Systems Intelligence course.