SYSTEM_ROOT/about_our_protocol

Engineers Hiring Engineers.

No keyword-matching. No junior coordinators. No recruiter playbooks. Just deep technical vetting by people who've shipped real AI systems.

about_protocol.sh
$ cat about_protocol.md

# FOUNDING_YEAR: 2024
# PHILOSOPHY: Engineers_First
# VETTING: Peer-Review_Only

STATUS: OPERATIONAL
NETWORK: 482 Engineers Deployed
RETENTION: 98.4% Client Retention
ORIGIN_STORY

Built from Frustration.

PromptlyStaffed.ai started because we lived the problem.

We've been on the hiring side — sifting through 60 resumes for a senior ML role, only to find 3 who actually understood transformers. We've wasted 2 weeks on candidates who looked good on paper and failed a basic coding screen.

Traditional staffing agencies don't understand technical roles. They keyword-match resumes and call it sourcing. We built something different.

482+

Engineers Placed

64h

Avg. Time to Shortlist

0.02%

Vetting Pass Rate

98.4%

Client Retention

CORE_PROTOCOLS

What We Believe About Hiring

01

Resumes are signals, not verdicts.

We read between the lines and validate with conversations, not ATS filters.

02

Your time is the most valuable asset you have.

If you're spending 10 hours a week on recruiting, that's 10 hours not building. We give that back.

03

A bad hire costs more than a slow hire.

Speed matters, but precision matters more. We do both by automating the noise.

04

AI hiring requires AI fluency.

We know what a RAG stack is, what fine-tuning means at scale, and what MLOps actually looks like.

TEAM_MANIFEST

Technical Founders, Technical Business.

PS

FOUNDER_01

ML Engineer → Recruiter

Ex-ML engineer. Built data teams at multiple AI-first startups. Ran technical hiring for 50+ engineers across LLM and vision stacks.

PS

FOUNDER_02

Architect → Operator

Full-stack architect. Designed engineering org structure for Series A companies. Deep in the AI tooling and MLOps ecosystem.

You work with us directly — not junior coordinators who don't know the domain.

NEGATIVE_SCOPE

What You Won't Get

  • We won't send you 30 resumes and call it "sourcing"
  • We won't pitch you someone who listed "Python" on their resume in 2019
  • We don't outsource interviews to contractors who don't know the domain
  • We don't have junior recruiter coordinators running your search
EXPERT_NETWORK // ACTIVE

Our Peer-Review Screening Network

We partner with domain-specific engineers and AI practitioners who conduct our technical screening. For ML roles, ML engineers interview. For data engineering, data architects screen.

You benefit from real peer review — not scripted HR questions or generic coding puzzles.

ML_EngineersLLM_SpecialistsMLOps_ArchitectsData_EngineersAI_Infra

Work With People Who Get It.

PROTOCOL_READY // AWAITING_INPUT