The two problems
Static context solves repetition, not drift
Pinning your setup in a file kills the repetition — you stop re-explaining the same things every session. It does nothing about drift: the model still works from a call you settled last month and quietly changed since.
Repetition and drift look like one problem and are two. A file fixes repetition cleanly and leaves drift entirely untouched — and, quietly, leaning harder on a file can make drift worse. Unl is built for the second problem: a new decision supersedes the old one on your word, so what’s served is the call that stands, not the one you’ve moved past.
Two problems that look like one
Repetition is saying the same standing things at the start of every session. Drift is the context being subtly out of date — the model acting on a decision you’ve already revised. People reach for a file to solve repetition and quietly assume it solves both. It doesn’t, because the two have different shapes.
What a file fixes
Repetition, and it fixes it well. Your conventions, stack and voice, written once and read every session, never re-typed. That’s real value and the right tool for the job — nothing here says otherwise. A pinned setup is a genuine relief.
What a file leaves
Drift. A static file is frozen at write-time, so the moment a decision moves and you don’t edit, the model is working from the old one — confidently, because a file gives no sign a line has expired. Fixing repetition can even deepen drift: a file you rely on but rarely revise becomes a stale answer you trust more the more you lean on it.
Two problems, two shapes
Repetition wants something written once and re-read; drift wants something that retires the old call when you make a new one. A file is the first shape. A substrate that supersedes on your word is the second. This is the pincer, stated plainly: the loop-counterfactual pages describe drift from the other side — a model acting with no settled decision in reach — and static context is drift from this side, your decision frozen at a snapshot. Tuned for Claude, Claude Code, ChatGPT & Cursor at launch, extending across the AI ecosystem. Connects anywhere MCP does.
A static file removes repetition but not drift — the second needs a store that retires the old call when you settle a new one — so the answer comes back measured against what you already decided, and why.
Reads through Unl arrive with measured context — in the presence of the decisions you’ve already settled. The reach lane is live: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.
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Questions people ask
Doesn't a good context file solve everything?
It solves repetition — you stop re-typing your setup. It doesn't solve drift, where the file quietly falls behind your decisions. Those are two problems, and a frozen file only closes the first.
What's the difference between repetition and drift?
Repetition is restating the same standing context every session — annoying, but visible. Drift is the context being out of date without anyone noticing — quiet, and more costly, because the model acts on a decision you've already moved past.
How can fixing repetition make drift worse?
Because a file you lean on but rarely revise becomes a stale source you trust. The more you rely on the pinned setup, the more confidently the model runs on whatever you last wrote — including the calls you've since changed.
What actually fixes drift?
A store where a new decision supersedes the old one on your word, so the current call is the one served. Repetition wants something written once; drift wants something that retires what you've moved past. Unl is built for the second.
What this is
Think inside your AI world — you stay in command
Unlimitless (Unl to friends) holds what you've settled, reads what your tools are showing, and catches what's changed out in the world — and hands your AI whatever bears on the work, the moment it's needed, without you asking. The right thing, in front of the model, unprompted, with you in command of the call. So you keep moving toward what you set out to build, on top of everything you've already decided.
It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector. Quick to connect, in a couple of steps.
Unlimitless is open now to invited Alpha. Apply for the Beta waitlist to come in ahead of the full launch:
Alpha is invite-only · free at launch.