The Laavod Method

There is a growing class of people who are genuinely good at working with AI. They know which model to use for which task. They know how to write instructions that produce consistent results. They know how to connect knowledge, tools, and context so an agent actually does what it is supposed to do. They know how to build workflows that run reliably at scale.

This is not prompt engineering. That term undersells it. This is a craft. And like every craft before it, it is about to become an economy.

Writers had Substack. Video creators had YouTube. Developers had GitHub. AI creators had nothing. They built in ChatGPT and it stayed in their chat history. They shared on Twitter as screenshots. They sold through Gumroad with no way for buyers to actually run the thing.

We think that is about to change. And we built the place where it changes.

Every major AI platform today is locked to a single foundation model provider. ChatGPT is OpenAI. Claude is Anthropic. Copilot is OpenAI via Microsoft. Gemini is Google. Each of them has an economic incentive to keep you on their model, regardless of whether it is the best one for what you are doing.

We think that is broken.

Laavod does not sell AI models. We do not have a foundation model. We do not have an economic reason to prefer one provider over another. Our economics work when you use the best model for the task, switch freely, and bring your own keys if you want.

This is not idealism. It is architecture. We built the platform so that model-agnosticism is structural, not optional. 247+ models from every major provider, switchable per task, per agent, per workflow. Bring your own API keys and pay zero markup. Export everything in open formats.

The reason no incumbent can copy this is simple: they would have to sell their competitors' models. Their business model prevents it. Ours requires it.

Most AI platforms think of their users as consumers. People who type questions and read answers. Passive. Transactional.

We think of ours as creators. People who build things. People who have expertise, package it as AI work, and share it with an audience that pays for it.

This is not a semantic difference. It changes everything about how we build.

When you think of people as consumers, you optimize for engagement. You make the chat sticky. You add features that keep people inside the product. You measure DAU.

When you think of people as creators, you optimize for output. You make the work publishable. You give every asset a URL. You give every creator a profile. You build a marketplace. You measure what people make and what they earn.

Most enterprise software starts with the organization. You join a company, you get an account, you exist inside the company's workspace. When you leave, your work stays behind.

We think the individual comes first.

On Laavod, every person has a profile. laavod.com/yourname. Your prompts, your agents, your workflows, your subscribers, your earnings. They are yours. When you join an organization, your personal work does not merge into the company. The organization is a layer on top of your identity, not a replacement for it.

This is the GitHub model, not the Notion model. Your contributions are yours. Organizations can use them, share them, govern them. But the creator is the atomic unit, not the workspace.

We built the data model this way from day one. Personal assets have no organization attached. They belong to you and you alone.

There is a difference between complying with EU regulations from a US headquarters and being built in Europe from the start.

Laavod is a German company. Our data lives in Frankfurt. Our backups stay in the EU. Our AI inference routes through EU endpoints. We do not transfer data outside the European Union.

This is not a compliance checkbox. It is a design decision. We believe the next generation of AI platforms should not all be headquartered in San Francisco. The EU has the regulation, the talent, and the market to build something distinct. We intend to prove that.

GDPR is not something we patched in. It is something we built on.

The core technical decision behind Laavod is that every piece of AI work is treated as an asset. A chat, a prompt, a skill, an agent, a workflow, a knowledge base, a use case, a pack. Same parent model. Same versioning. Same publishing. Same marketplace. Same social layer.

This is not how most platforms work. Most platforms treat each feature as its own thing with its own data model, its own sharing mechanism, its own lifecycle. Chats live in one place. Prompts live in another. Agents are something else entirely.

We made everything polymorphic from day one. One asset model that expresses every type of AI work. The reason is simple: if you cannot publish it, version it, price it, and sell it the same way regardless of what it is, you do not have a marketplace. You have a collection of disconnected features.

This decision cost us months of architecture work. It is the reason the marketplace will work when it launches.

A prompt becomes part of a skill. A skill gets used by an agent. The agent becomes a step in a workflow. The workflow becomes a use case. The use case gets bundled into a pack.

Each layer adds value. Each layer is independently publishable, sellable, and forkable. A creator can sell a prompt. Another creator can build an agent that uses that prompt. A third creator can compose a workflow that uses that agent.

This is the composition thesis. AI work is not a single artifact. It is a stack of reusable building blocks that compound in value when combined. The more blocks exist on the platform, the more valuable each individual block becomes.

We designed the product around this from the beginning. Not because it was easy, but because it is the only way to build a real creator economy around AI work. Individual assets are products. Composed assets are businesses.

We will never train a foundation model. That is not our job.

Our job is to build the best workspace, the best publishing layer, and the best marketplace for the people who use those models. Let OpenAI, Anthropic, Google, and Mistral compete on model quality. Let us compete on what happens after the model generates a response.

This is a deliberate strategic choice. Companies that build both the model and the platform have a conflict of interest. They want you on their model. We want you on the best model for what you are doing. Those are different incentives.

We connect to every major provider through a single gateway. 247+ models today, more tomorrow. When a new provider launches something better, it shows up on Laavod. When an existing provider raises prices, you switch. That is how it should work.

We make money three ways.

First, subscriptions. Four individual tiers and two team tiers. You pay for the features you need.

Second, credits. Every AI action costs credits. You pick how many you need. Top up when you run out. Or bring your own provider keys and pay zero markup. We earn margin on the credits, not on locking you in.

Third, the marketplace. When creators sell their work, we take 5%. They keep 95%. Most platforms take 10% or more. We keep it low because the first two revenue lines already work. The marketplace fee should attract creators, not extract from them.

There are no ads. We do not sell user data. We do not train on your content. These are not features. They are commitments.