Proof-of-work hiring for AI-native teams

Hire the top‑1% GTM operators

Candidates solve real cases on mock data with AI, and you see every decision they make.

Book a demo See how it works → Get the report →
01The problem

There's no method for evaluating AI-native roles.

Candidate
Clay
HubSpot
Python
n8n
Claude Code
Can they build?
A. Rivera
✓
✓
✓
✓
✓
???
J. Okafor
✓
✓
✓
✓
✓
???
S. Park
✓
✓
✓
✓
✓
???
D. Klein
✓
✓
✓
✓
✓
???
312 applications · all identical on paper The last column is the whole job →
312

applications per opening — most of them AI-generated slop you can't tell apart.

$112K

salary spread for the same title. The expensive mistakes hide in the tier you can't see.

0

résumé bullets that prove someone can actually build with AI.

Brayden Vexler — Résumé
Brayden Vexler
GTM Engineer · Growth & Revenue Operations
San Francisco, CA · [email protected] · linkedin.com/in/braydenvexler · Open to remote
Summary

Results-driven, AI-native GTM Engineer passionate about building scalable, data-driven revenue systems. Proven track record of leveraging automation and AI to accelerate growth across the funnel.

Experience
Account Executive, Tideline (seed-stage SaaS)2023 – Present
  • Leveraged Clay and HubSpot to automate enrichment, scoring, and routing across the inbound funnel.
  • Spearheaded AI-assisted outbound, implementing Claude- and Apollo-powered sequences across the sales motion.
  • Drove a 40% increase in qualified pipeline through cross-functional collaboration and process optimization.
Sales Development Rep, Northwind Labs2021 – 2023
  • Hit 120% of outbound meeting quota across four consecutive quarters.
  • Maintained CRM data hygiene and built funnel reporting dashboards.
Skills
ClayHubSpotSalesforcePythonn8nMakeZapierClaude CodeCursorApolloOutreachSQLdbtSnowflake+6 more
EM
Elena Marsh · CMO
10:41 AM
Reads AI-generated.
EM
Elena Marsh · CMO
10:43 AM
Is account executive the right background for a GTM engineer?
ML
Marcus Lee · Talent
To be honest, I'm not sure.
EM
Elena Marsh · CMO
10:46 AM
Everyone's using Claude now. No idea how to actually interpret this — did they build anything?
ML
Marcus Lee · Talent
We'd have to interview them to find out.
02The role

What the top‑1% actually looks like.

We assessed the best GTM engineers, leaders, and fractional talent. The top-1% combine customer understanding, technical chops, and the judgment to navigate challenges across teams.

01~$30–90K
Operator Runs no-code flows inside the tool. Clay-only
02~$135K
Engineer Works in code, building internal tools and pipelines. Builds with AI
01 · Handoffs

They understand how sales actually works

Handoffs run across the whole sales org — marketing→SDR, SDR→AE, AE→CS. Architects grasp these interdependencies and design each handoff to carry the context the next team needs, with feedback looping back. BDR→AE is just one link in the chain.

Marketing → SDR → AE → CS
↩ feedback loops at every handoff
02 · Enrichment

They dig into the data by niche

Enrichment varies by industry. Architects find differentiated sources that fit the niche — then dig into how that data gets used.

OperatorClay defaultApollotrust output
Architectniche datasetsproduct signalsverified vs. closed-won
03 · Systems

They think in systems

Architects build a system that sustains itself — it runs and compounds while they move to the next problem.

Build → Run → Compound ↻ self-sustaining
03How it works

Applicants build in the sandbox. Real case studies. Mock data.

Step 01

We provision the sandbox

A live virtual workstation, pre-wired with the real GTM stack — the same environment, identical for every applicant. No setup, no excuses.

ClayClaude Coden8nLLM APICRM+100 more
Step 02

We hand over the case — and the mess

A real case study for your niche, plus deliberately messy data: a dirty CRM export, duplicate accounts, broken firmographics. The clock starts. They have the window to ship.

Step 03

Everything is recorded

Every prompt, tool call, script, query and dead end — timestamped. We keep the whole path to the answer, not just the final artifact.

PromptsTool callsScriptsTokens
Inside the sandbox
04The analysis

Find the outliers in 100s of applications.

We analyze hundreds of recorded exercises so you don't have to — surfacing the outliers and the candidates that actually fit your business.

Cohort.app — Inbound Routing Case
142 applicants·118 completed·24 in progress·2 advanced
X axis
Tools used
Min Motif score
0+
Motif score low–high shown now
time spent → Motif score →
Get the full report — out July →
05What we score

Finding the Architects.

Tool breadth is table stakes and easy to fake. We score the thing operators tell us actually predicts performance: how someone reasons through a real, ambiguous problem.

01

Conceptual understanding

Do they actually grasp the motion — ICP, funnel, why a lead routes where it does — or just push buttons?

02

Data & CRM enrichment

Do they find differentiated sources for the niche and reconcile against closed-won — or trust Clay's defaults?

03

Architect score · builds systems

A pile of one-off workflows, or a self-sustaining system that compounds across the whole GTM org?

04

Handoff facilitation

Handoffs span the whole org — not just BDR→AE. Do they understand the interdependencies that make a sales org work, and design each handoff and feedback loop to carry what the next team needs?

05

Outbound & inbound craft

Outbound that earns the reply, inbound that converts the intent — not templated spray-and-pray.

06

Agentic & tool fluency

Do they actually drive Clay, Claude Code and n8n with judgment — or name-drop tools they can't wield?

Stop reading résumés.
Start reading real work.

Book a demo See the cohort analysis