A situation we handle
When your AI's edits deform the voice you've already established
Your AI's edits deform the voice you've already established. A fresh session only sees the conversation in front of it, not the decision you already settled. Unlimitless holds that decision, with its reasoning, and hands it back the moment it bears on the work — so your AI acts on the call you made.
When your AI's edits deform the voice you've already established — and it's not that the model is weak; in a fresh session it just can't see the decision you already settled. Unlimitless (Unl) holds each decision you make with its reasoning and hands the relevant one back the moment it bears on the work, so your AI works from the call you already made. It's just-in-time context; the human stays in command. Works across Claude, Claude Code, ChatGPT and Cursor over MCP. Free at launch.
Here's a polished version: "In today's fast-paced landscape, organisations must leverage innovative solutions to stay ahead. Our approach empowers teams to unlock their full potential and drive meaningful results."
The settled decision isn't in view, so the model works from its own defaults.
Working from the voice you set — plain, no marketing gloss: "Most teams already know what to do. They lose the time to hidden friction, not missing ideas. This cuts the friction."
Your settled voice: plain, direct, no marketing gloss is right there when it's relevant — so the model works straight from it.
Same request, two outcomes. Unl doesn't make the model smarter — it hands back the call you already made, so the work stays on it.
Why this matters
The decision didn't have to be remembered. It had to be there — at the moment it bore on the next step.
You make a real call — an approach, a constraint, a convention you settled and why — and it lives in a conversation that's since scrolled away. A capable model, working only from what's in front of it, has no way to see it. Hand that decision back at the right moment and the work stays on track: the model reasons forward from your call instead of re-deriving it.
That's the difference Unl makes. It's just-in-time context: the settled decision, with its reasoning attached, arrives when it's relevant — and you stay in command of the call.
Questions people ask
Why does my AI drift back to its own defaults instead of the choices I settled?
A fresh session only has the conversation in front of it, so a call you settled earlier isn't in view — it's not that the model is weak, it just can't see it. Unl holds your settled decisions, each with its reasoning, and hands the relevant one back the moment it bears on the work — so the model works from the call you made. It works across Claude, Claude Code, ChatGPT and Cursor.
How is this different from my AI recalling past chats?
Recall surfaces what was said when you go looking for it. Unl hands a settled decision back unprompted — it arrives because it's relevant to what the model is about to do, with the reasoning attached. The unit is the decision and its why, in front of the model when it matters, not a transcript to search.
Which AI tools does this work with?
Unl is one connection over MCP, so it hands your settled decisions to Claude, Claude Code, ChatGPT and Cursor alike. The call you settle on one surface is inherited on the others.
What this is
Think inside your AI world — you stay in command
Save the thoughts, decisions and targets worth keeping, each with its reasoning, carried into every AI session the moment they matter. A new unit of exchange between you and your AI: the Settled Why with standing that travels. Unprompted.
Your whole AI world. What you decided at the epicentre. It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector — quick to connect, in a couple of steps.
MCP native·Human settled·Model agnostic·Your data
Measured Context
Connect Unl to bring the right information into the moment.
Your sources, read against the criteria you set.
The full product, open. Free at launch.