In the AI era, output is cheap. Capability isn’t.
Hiring is no longer selecting for real capability —
it is selecting for those who appear capable
We’re rebuilding how capability is evaluated.
3 — Problem
Hiring is breaking
Interviews
optimized for performance or AI-assisted in the moment
Outputs
easy to generate — hard to trust
Emerging roles
no clear evaluation standard
Recruiters
rely on outdated signals
Signals no longer reflect real capability.
Hiring has always relied on signals — not capability.
Those signals used to work. Now they don't.
4 — Model
A new signal path
capability→output→week signal
output is cheap→signals break
capability→process→trusted signals
5 — Build
What we’re building
We are building a new signal layer for hiring.
Hiring has always evaluated outputs.
We evaluate process.
decisions
problem solving
iteration
AI usage
Signals become
— continuous
— verifiable
— decision-ready
6 — Flow
Work → Signal → Decision
This is not more information. This is a decision.
Candidate Profile
Alex
Decision-ready
Consistency
High
Problem Solving
Strong
Verification
Verified by manager (15)
Feedback loops: 5
Signal strength: High
AI Use
Thoughtful
Hiring confidence
High
7 — Comparison
Candidate comparison
Candidate A
— strong résumé
— no verification
Candidate B
— consistent work logs
— verified contributions
— increasing complexity
→ Recommendation: B
Risk: LowConfidence: High
This is not more information. This is a decision.
8 — Recruiter view
Scan hundreds of candidates in one view
backendverifiedhigh consistency
Candidates
0
Shortlisted
0
Recommended
0
Recruiters don’t want more data.
They want faster, lower-risk decisions.
9 — Why now
Why now
AI makes outputs cheap
Work is digital and traceable
Hiring uses outdated signals
For the first time, we can capture how work actually happens — at scale.
10 — Vision
Vision
candidates build real capability
recruiters make better decisions
managers develop talent
This becomes the default way capability is evaluated.
11 — CTA