Why we teach frameworks that carry across ChatGPT, Claude, Gemini, and Copilot

Locked to one tool

You're stuck with one approved tool that doesn't do the job well. In regulated settings it is a familiar story: IT approved the tool, compliance signed off on it, and the team is left choosing between the tool that is allowed and the tool that works.

The opposite problem is real too. A team picks the tool a power user loves, builds everything around its features, and then finds that the features changed, the pricing changed, or a different tool got better. Everything the team learned was about the tool. None of it carried.

Capability that lives in your team

B43 is tool-agnostic. We teach frameworks that carry across ChatGPT, Claude, Gemini, and Copilot, and whatever comes next, so your team's capability lives with them and is never locked to one vendor. That is a belief we hold to, not a compatibility list: capability should live in your team, not in one vendor's features.

The distinction matters because a vendor's features are the vendor's to change. What your team learns is not. A framework is the way a person on your team breaks down a task they already repeat, decides what good output looks like, checks the result, and hands the whole thing to a colleague as something they can run the same way. The tool underneath is interchangeable. The judgment is not.

You are never locked to one vendor, or to us.

What a framework looks like in practice

It is concrete. The training session in the sprint covers how to choose the right tool for the task, how to structure inputs, and how to evaluate outputs. None of those skills belongs to one vendor.

The same goes for turning a task you already repeat into a reusable skill, one decision at a time: what goes in, what comes out, who it is for, what has to be true before it leaves your hands. Those decisions are the skill. The prompt is just where they are written down.

The Weekly Priorities Skill on this site is one small example. It is a single skill, packaged once, and it loads into Claude or ChatGPT with the same three steps. The working rules, the output templates, and the rubric it checks itself against do not care which model is running them. Get the skill →

The same held in our work with real estate agents: we taught on Claude, and the frameworks carried to ChatGPT, Gemini, and Copilot. Recipes go stale. Knowing why the recipe works doesn't.

What doesn't expire when the models change

Models change. Tools change. Workflows left alone quietly stop working. That is true whichever vendor you chose, and it is why the program does not stop at the sprint. After it, Unlimited FDE keeps refining the workflows your team built as needs, tools, or models change. FDE stands for Forward-Deployed Engineer: a hands-on AI implementation partner who works alongside your team. Once things stabilize, Maintenance covers reasonable updates, troubleshooting, and adjustments to what was built.

What does not need updating is the capability. The frameworks are built to carry across any tool, so what your team learns does not expire when the models change. A team that understands how these tools think, where they fail, and how to encode its own process into them can move to a new model without starting over. A team that memorized one tool's menus cannot.

What this means if you have one approved tool

It means you can start. The frameworks work inside the tool you are allowed to use today, and they are the thing you keep if that tool changes tomorrow. For teams in legal, insurance, and healthcare, it is how you move forward without risking client data or compliance, and get more than your one approved tool can give.

It is also where the building happens. Unlimited FDE is delivered inside your approved AI platforms, such as ChatGPT, Claude, and Microsoft Copilot, using their native capabilities: Skills, GPTs, agents, Projects, prompts, instructions, knowledge, and approved connectors. The work stays inside the tools you already approved.

And you are never locked to us. The capability is your team's, and the point of the training is that it stays with them.