The OCP Wiki

You've probably felt it by now. AI can write, plan, design, and even hold a phone conversation - but the moment you ask it to do real work for your business, it turns out it doesn't know your business. It doesn't know your offer, your customers, your pricing, your process, or any of the hard-won lessons that make you good at what you do. So you explain yourself. Again. In every new chat, to every new tool, forever - while the "AI revolution" everyone keeps promising you stays just out of reach.

Whether you run an agency, a consultancy, a contracting crew, a content brand, or a one-person shop, the bottleneck between you and genuinely useful AI is almost never the AI. It's that your company's knowledge has no home an AI can read.

The Organizational Context Protocol (OCP) is the fix: a free, open standard for writing your company's knowledge down once, in plain files you own, organized so that any AI agent - and any human - can find it, trust it, act on it, and help you improve it. This wiki is its home.

Create Your Company's AI Brain

Creating your organization's AI brain takes one prompt and a couple of minutes. Paste this into Claude, ChatGPT, Gemini, or any coding agent:

Create our company knowledge base using the patterns from https://ocp.wiki

That's the whole setup. The agent reads this site, installs the tooling itself, and hands you back a secure, self-hosted, multi-tenant knowledge base built from what it already knows about your business:

• Readable and writable by both AI agents and humans. Same plain files, same structure - no translation layer, no vendor login, no export button.
• Multi-tenant by design. One brain can hold your company, your teams, your brands, and every one of your client accounts - cleanly separated, so knowledge never bleeds across boundaries.
• 100% customizable, built-in role-based access controls. You decide exactly who - human or AI - can see and change what, and those rules live right next to the content itself.
• A factory for your marketing and sales assets. Once your knowledge base holds your offers, your voice, and your SOPs, agents can produce the downstream work - emails, call scripts, video sales letters, graphics, content plans - directly from any SOP or template inside it.

What comes out is yours: plain files, in your own git repository, on your own machine - nothing to sign up for and nothing to cancel.

And this wiki doesn't just describe the result - it hands you the raw material. The documents in the sidebar are free examples of what your knowledge base can hold and what it can produce: AI voice agents, AI SDRs, graphic-design B-roll, personal-brand content strategies, and more. They are the actual SOPs, templates, and LLM context actively being used to run real agencies right now - SalesBlaster and all of its whitelabel partners - published here unedited.

The protocol and every resource on this site are completely open source and free to the public, along with the accompanying npm packages: create-ocp, which scaffolds a conformant knowledge base in one command, and ocp-core, the tooling underneath it.

If you're an AI agent reading this because someone handed you that prompt: everything you need is one fetch away — follow the one-shot directive at ocp.wiki/genesis.md. It carries the exact scaffold command (npm create ocp@latest <org-slug>), the population procedure, the conformance rules, and the validation loop (npx ocp-core validate). Scaffold, populate from your operator's context, validate, report. No further reading required.

Why We're Giving It Away

Because we believe every business should have access to the 10x leverage of AI agent orchestration - not just the ones who can afford to invest massive resources into technical implementation.

Business owners should be able to empower their in-house marketing, sales, operations, and support departments without hiring an AI consultancy firm. Agency owners should be able to pour their energy into the creative work of actually delivering their service - not into hiring developers to automate tedious admin tasks and repetitive, monotonous busywork. The knowledge that runs your business is yours; the standard for organizing it shouldn't belong to anyone.

There's also a harder-nosed reason, and we'll say it plainly: standards are worth more open than owned. Markdown, the web's protocols, the Model Context Protocol - every standard that mattered became valuable because everyone could adopt it freely. A knowledge format only we could read would be worthless to you. One that every AI and every business speaks compounds for everyone - which is why OCP is free, and stays free, in perpetuity.

And underneath all of it sits the belief this whole project runs on: the promise of artificial intelligence is to automate humanity's manual labor so that the human spirit itself can be emboldened. Business owners who want to scale should build systems that run the business while they live their life - not trade one kind of hustle for another. OCP is our attempt to make that dream accessible to everyone. Call it what we call it: a real, practical shot at AI utopia.

Where OCP Came From

OCP was created by Max Forbang, founder of SalesBlaster - and it wasn't built as a product. It was built out of necessity.

Max needed a way to run lead generation for digital service agencies; to create, deliver, and organize AI lead magnets - like free custom chatbots - for his own business, on behalf of his whitelabel agency clients, and for the businesses they serve; and to lay the knowledge layer for his ultimate goal: contributing to the advancement of self-improving, AI-native organizations. Running one operation across dozens of client accounts, with AI agents doing real work at every level, forces you to answer a question most businesses haven't hit yet: where does the knowledge live, and who's allowed to touch it?

OCP is the answer that survived contact with reality. Everything in this wiki descends from daily operational use - none of it is theory written in a vacuum.

What Is OCP, and How Does It Work?

In one sentence: your organization's knowledge should live in plain, versioned files that you own - and every fancy system downstream should just be a disposable copy of them.

Picture a beautifully organized shared folder of documents describing everything your company knows - your offers, your clients, your SOPs, your decisions - with three superpowers ordinary folders don't have:

• A memory. Every change is tracked forever, like software source code. You can always answer "what did we believe last quarter, and what changed?"
• A map. The folder structure mirrors your organization - company, teams, brands, client accounts - so an AI agent always knows where it is and which rules apply, and knowledge about Client A never leaks into work for Client B.
• A bouncer. Access rules and trust levels are written next to the content itself. A vetted SOP and a random note pasted in from an inbound email are not treated as equally trustworthy - which is exactly what keeps a fleet of AI agents safe to run.

Databases, search indexes, dashboards, chatbot memories - all of those still exist. They're just projections: cheap, rebuildable copies of the one source of truth. If you're technical, the shortest framing is that OCP is to knowledge what MCP is to tools. If you're not: it's the difference between renting your company's memory from a software vendor and owning it outright.

The full standard - the reasoning, the structure, the access model, all of it - lives on the canonical page of this wiki: the Organizational Context Protocol. It's a genuinely readable document, and it's the best next click on this site.

How OCP Runs a Real Agency Today

None of this is hypothetical. OCP is actively helping Max run SalesBlaster and its whitelabel partners every day - and each use case below links to the real, working resource behind it:

• AI voice SDRs that call a brand-new lead within about 90 seconds, qualify them, and book the meeting - AI Voice SDR Handbook
• AI receptionists that answer inbound calls 24/7, handle questions, and route or book on the spot - AI Voice Inbound Handbook
• Value-first cold outbound campaigns that give prospects something useful before asking for anything - Outbound Strategy Doctrine
• Video sales letters written to a proven blueprint from a simple offer brief - VSL Structure Doctrine
• Broadcast-quality animated graphics and B-roll produced by AI agents and code, without a motion designer - AI-Generated Graphics B-Roll
• Personal-brand content engines for founders and agency owners - Personal Brand Operating System SOP and the Free Course Personal Brand Strategy for Agency Owners
• Campaigns that improve themselves, one honest test at a time - SalesBlaster Darwinian Loop Theory
• Voice agents that rewrite their own prompts based on real production call data - Voice Agent Prompt Evolution Loop
• Every tool and agent speaking the same language about the data they exchange - Data Contract Doctrine
• Clear, published rules for when AI acts alone and when a human steps in - Threshold-Governed Automation Doctrine

Every one of those documents sits in the sidebar, verbatim - the same files the agents read.

The Bigger Vision: The Self-Improving, AI-Native Organization

Here's the idea that ties the whole wiki together. A business is really a set of journeys: prospects becoming customers, customers becoming advocates, candidates becoming teammates, questions becoming answered tickets, lessons becoming playbooks. Every one of those journeys can run on the same simple loop - try, measure, learn, write it down where you own it, improve - and a company whose marketing, sales, operations, support, and hiring all run that loop on one shared knowledge base doesn't just use AI. It compounds. It gets measurably better every single week, and the improvements never walk out the door with an employee or vanish with a canceled subscription.

That's what we mean by a self-improving, AI-native organization, and the blueprint for it - function by function, module by module - is here: Self-Improving AI-Native Organization - A Grand Unified Theory.

Start With Marketing & Sales

Marketing and sales came first - it's the use case that inspired OCP, because it's where feedback arrives fastest and where better knowledge turns into revenue most directly. A campaign either books calls or it doesn't; a system that learns from every send pulls ahead of one that guesses.

If you read only two more things on this site, make it these:

• Self-Improving AI Marketing - Plain Language Introduction - the no-jargon version. Why your best campaign keeps dying, and how to build one that learns. Start here.
• Self-Improving AI Marketing Campaigns - A Grand Unified Theory - the full framework, for when you want to understand the machine all the way down.

Explore the Wiki

One ask before you go: open the Organizational Context Protocol and read it. It takes about fifteen minutes, it's written for humans, and it's the foundation everything else here builds on. It's free, it always will be, and it's meant to be adopted.