Think inside your AI world.

A hire, against a gap you flagged

A company’s jobs board is a stream of roles, most of it routine backfill: replacements, generalists, teams that tell you nothing. What you actually need is the hire that lands on a gap you flagged — the capability you said a rival would have to build to come at you — and that is a line the feed cannot hold, because the read is yours.

Read a company’s hiring through Unl and the whole jobs stream arrives measured against the read you settled — so instead of a list of postings to scan, you get the single hire that lands on a gap you flagged, with the reason it crosses. The one, not the thousand.

What a company’s public jobs board publishes

A company’s hiring is public and legible, and there is a lot of it:

  • Roles posted across every team, most of them backfill and routine growth
  • Every opening at once, the telling one beside the dozen that are not
  • Titles and teams, almost none of which signal a move against you
  • No idea which hire lands on a gap you flagged — that context is not in the posting

The line the feed can't hold

Say you flagged a gap and named its meaning: they cannot attack our position without the capability they lack today; the day they start hiring for exactly that, they have decided to build it. That read is a decision you made; it is not a field the jobs board models.

The reason the line is yours is the whole point. A hiring-signal feed can list every opening; it cannot know the gap you flagged, or that a specific role is the tell you decided marks the intent, or that ten backfill postings are noise to you while the one senior hire into the capability they lacked is the whole signal.

The frame judges the data it is given; it does not verify the source’s accuracy.

The one that crosses

So when a company opens the exact role that fills the gap you flagged, it crosses — and the other forty postings do not. Through Unl the answer arrives as a verdict: they just started hiring for the capability you said they would need to come at you, so the gap you flagged is closing on purpose — here is the role, read against your analysis. Same public board; a decision instead of a digest.

You didn't ask — it was already there

You did not ask for it. The gap you flagged was already recorded, so the next time you open Claude the crossing is already in the window — read against the capability you said would signal intent, with the reason it cleared it — rather than waiting for you to check their careers page. You author the read once; the read applies it every time they post.

The answer comes back measured against what you already decided, and why.

The lane is live and open to this tool today: 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.

Questions people ask

How is this different from a hiring-tracker alert or a jobs feed?

An alert fires on the source’s rule — a role posted, a title matched. This fires on YOUR rule: the specific gap you flagged, the role that signals they are closing it, with the reasoning attached. The feed shows you every posting; the measured read shows you the one that acts on a gap you actually flagged, and why.

Do I get pinged the moment they post a role?

The capability is that the crossing arrives measured against your analysis the next time you are working — it is already in the window, read against the gap you flagged, rather than a stream you monitor. A scheduled push is a separate delivery; what the read guarantees is that when a hire lands on the gap you flagged, it surfaces as a verdict against your read, not as one more job posting.

Does Unl change anything on the jobs board or in my analysis?

Unl reads through the company’s public postings, and can write back on your explicit gesture — it never acts as a side effect of a read. The posting is a public listing; the gap you flagged lives in Unl; the read joins them and returns a verdict, altering neither.

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.