Case Study · 2024 to Present

Kirro: AI Job Search Assistant

An AI job search platform used across 5+ countries — built on a deliberately unfashionable bet: humans before automation.

Role
Co-Founder & CPO
Timeline
2024 to Present
Markets
US, UK, Canada +
Focus
Tech Professionals
5+
Countries: US, UK, Canada and more
16.5%
Interview rate vs 2–3% industry avg
19.8h
Hours saved per user per month
200+
Jobs applied per user monthly

Job hunting hadn't changed in a decade. We rebuilt it around one thing: hours saved.

Tech professionals were losing 10–15 hours a week to applications: tailoring resumes by hand, re-entering the same fields on every platform, tracking it all in spreadsheets, with almost no signal on what was working. Kirro replaces that grind. Upload a resume once, and the platform matches, tailors, applies, and tracks every application for you.

Before Kirro
10–15h/week on applications · Manual tailoring per role · Spreadsheet tracking · 2–3% interview rate
After Kirro
200+ applications monthly, automated · AI-tailored resumes · Full tracking dashboard · 16.5% interview rate

Co-founder and CPO. I own product end to end.

I co-founded Kirro with Emmanuel Abang, a colleague from Meta. He runs business and commercial strategy. I run product: strategy, research, UX, operations, and technical direction.

What I own
Product strategy · UX and design · User research · Operations model · Roadmap · Growth · Technical direction
What Emmanuel owns
Business development · Commercial strategy · Partnerships · Investor relations · Revenue operations
The Kirro dashboard: personalised job search command centre
Kirro dashboard showing personalized job matches and auto-apply status
79 applications tracked, AI job matches with fit scores, auto-apply active

We launched with humans, not AI. On purpose.

Research with 1,400 job seekers across the US, UK and Canada pointed to one answer: launch with humans, not automation.

01
Volume was the problem, not discovery
Users could find jobs. The repetitive act of applying was what drained them.
02
Trust was the barrier to automation
Users feared bad, automated applications more than they wanted speed — a human-in-the-loop model came first.
03
Tech roles were the clearest beachhead
Highest application volume, most consistent formats, a community that refers itself.

"We used humans to learn what the automation should eventually do. We weren't being slow. We were being precise."

That hybrid model — a team applying on each user's behalf, guided by AI — paid for itself from day one while teaching us every edge case the automation needed to learn.

The product evolution: from manual to AI-native
PHASE 1 Manual DEP Model Humans apply on behalf of users validate PHASE 2 AI + Human Hybrid AI recommends, humans verify automate PHASE 3 · NOW AI-Native Platform Automated matching and application at scale

5x the industry's interview rate, at scale.

Kirro now runs across 5+ countries for tech professionals in product, engineering, design and data — applying to 200+ jobs a month per user, automatically.

16.5%
Interview rate, vs 2–3% industry average
19.8h
Hours saved per user, monthly
81–87%
AI match score before auto-apply triggers
Applied Jobs: the full tracking dashboard
Kirro applied jobs screen showing 79 applications, 13 interviews, 19.8 hours saved
79 applications, 13 interviews landed (16.5%), 19.8 hours saved — one user account
Building now

From automating applications to an agentic career partner.

The next phase of Kirro moves past automating applications. We're building a fully agentic job search assistant — AI that reasons and acts across a candidate's entire job search, from sourcing and tailoring to interview prep and offer negotiation, with a human always able to step in. That's what we're building right now.