Nahom Mekonen.

Founder turned product leader. I've built two companies from zero, leading product, marketing, and operations across both.

Nahom Mekonen

Beyond the bullet points.

I grew up between worlds. Ethiopian roots. American hustle. Early lesson: technology should serve people who aren't already winning.

That belief led me to co-found Kabba Transport in Addis Ababa. I spent weeks riding informal minibuses as a passenger before writing a single requirement. You can't build for users you've never been.

Before that, I built Radium Media from nothing. $30M in sales. No outside funding. The insight was simple: build brands backward. Start with the audience, not the product. Most founders build what they want to sell. I built what people already wanted to buy.

Both companies taught me the same thing in different languages: the gap between a good idea and a product people actually use is almost never about the idea. It's about the decisions. What you prioritize, who you listen to, and what you choose not to build. I want to bring that instinct to a team that's past zero, with real users and a real problem worth getting right.

Outside work, I'm drawn to the same kinds of problems: cities, transit systems, how infrastructure shapes behavior long before anyone thinks to measure it. I read obsessively. Behavioral economics, urbanism, AI. Right now AI has most of my attention. Not because of the hype, but because the gap between what the technology can do and what's actually being built with it is still enormous. Same instinct that made me ride the minibus before I wrote the spec.

Recognition

Nominated · Africa Startup of the Year

Recognized for innovation in urban mobility and transportation technology in East Africa.

Leadership

Management Leadership for Tomorrow (MLT) — business case studies and leadership modules focused on product strategy and cross-functional collaboration.

Location & Availability

📍 Minneapolis, MN Open to Relocate Open to Hybrid & Remote

Education

B.S. Computer Science & Cybersecurity
Metro State University · Dean's List

The work.

Two companies, two industries, two continents. Here's what I built, the decisions behind it, and what I'd do differently.

Kabba Transport
Kabba Transport
Co-Founder & Product Lead · May 2021 – Present · Addis Ababa, Ethiopia & Remote
Transportation Technology Urban Mobility Mass Transit Product Strategy API Integration

Kabba Transport is a shared mass transit platform I co-founded and led product for in Addis Ababa — built from first principles to solve a real infrastructure gap, not to copy a model from somewhere else. Not a ride-hailing app. Not a taxi with a logo change. A fundamentally different product category: fixed-route, subscription-based commuter infrastructure for a city of 5 million daily commuters with no reliable transit system built for them.

The Problem Worth Solving

Before writing a single requirement, I spent weeks riding the informal minibuses as a commuter — not a researcher with a clipboard, but someone living the problem. I was doing jobs-to-be-done research before I had a name for it. The insight that changed everything: the job isn't "get a ride." It's "start work on time, every day, without the anxiety of not knowing whether you'll get there." That distinction changes every product decision that follows.

Ride-hailing companies had arrived. They solved reliability — but priced themselves out of the working professional's daily reality. Built for the middle class, not for the commuter taking the same route every day. Meanwhile, the informal minibus system had affordability but no structure, no predictability, no trust. No one had built the thing in the middle: mass transit infrastructure that was affordable, predictable, and designed to scale.

"Ride-hailing solved the wrong problem for the wrong price. Addis didn't need a better taxi — it needed the transit system that was never built."

The Strategic Insight

The informal system had product-market fit for affordability. Ride-hailing had PMF for the upper segment. The mass transit category had no validated PMF at all — that was the opening. Kabba was designed as structured commuting infrastructure: fixed routes, subscription models, predictable pricing. Built like transit, not like a gig economy workaround. Emerging markets don't need ride-hailing at scale. They need the kind of system working professionals in developed markets take for granted — and nobody had built it.

Kabba Transport Van
1M+
Trips Served
400%
Year-over-Year Growth
95%
Platform Retention
35%
Fleet Efficiency Gain
80%
Reduction in Manual Reconciliation

How I Worked

I owned the full product surface — from first-principles discovery to specs engineering could execute without return trips for clarification. Three concurrent workstreams, competing priorities, one roadmap. Here's what that looked like in practice:

  • Led product strategy and roadmap across rider, driver, and operator surfaces — used RICE scoring to force sequencing decisions when engineering bandwidth and operational urgency collided
  • Ran structured discovery with commuters, drivers, and corporate HR stakeholders — uncovering that drivers' real job was social routing (predictable income, not navigation), which rebuilt the driver interface from scratch
  • Journey-mapped the full operator workflow end-to-end — identified financial reconciliation as the highest-friction bottleneck, invisible from the outside but fatal to scaling; made it the top backlog item before any fleet expansion
  • Specified and owned payment gateway and government API integrations — managed external stakeholder relationships across technical and compliance requirements from brief to go-live
  • Built the B2B corporate tier from user stories up — discovery with HR directors revealed their real job wasn't transportation, it was liability removal; that reframe made it our highest-margin product
  • Set OKRs and ran bi-weekly sprint reviews across all three product surfaces — surfacing blockers before they became delays and keeping three stakeholder groups aligned without creating gridlock
  • Built the analytics layer that enabled real-time operational decisions — used it to run directional experiments on route performance and pricing before committing to full rollout

What I'd Do Differently

Instrument earlier, decide later. I was making product decisions directionally when we had enough usage to be precise. Directional is fine pre-PMF. Past PMF, it's an excuse. I'd set up proper event tracking from the first week of real usage.
Run B2B discovery in month 2, not month 18. Corporate HR stakeholders turned out to be our most rational, highest-value buyers. I should have run that discovery far earlier — it would have changed the roadmap significantly.
Build the driver feedback loop as a formal channel, not a one-off. Driver sessions kept surfacing critical product insights. I treated them as discoveries. They should have been a standing input channel from the start.
Radium Media
Radium Media
Founder & Product Operations Lead · July 2019 – December 2023 · Remote
Creator Commerce Audience-Led Growth Brand Strategy Product Discovery E-Commerce

Radium Media was a creator commerce company I founded and ran — built on a single insight: creator audiences are among the most loyal, high-intent buyers in e-commerce, and almost no one was building brands specifically for them. I didn't treat creators as a distribution channel. I built brands backward, starting with the audience and using the creator as proof that the market already existed.

$30M+
Total Sales in 3 Years
200K+
Customers Served
0
Outside Funding Raised

The Insight

Most companies treated creator audiences as an advertising channel. I saw it as a product brief — an audience telling you exactly who they are and what they want, if you're willing to listen. A mid-tier creator with 200,000 engaged followers has something most brands spend millions trying to manufacture: genuine trust. Their audience doesn't just consume their content. They buy what the creator recommends and instantly reject anything that feels inauthentic.

The model was disciplined from the start. For each partnership, I built detailed audience personas before touching product — purchasing behavior, identity signals, content categories that drove the highest trust. Most importantly, I mapped the jobs-to-be-done: what was the audience actually hiring this creator to do for them? What emotional job did the content fulfill? Then I built brands designed to fulfill that same promise. Not brands looking for an audience. Audiences finally getting a brand built for them.

How I Worked

Mid-tier creators were the right bet — not because they were cheaper than mega-influencers, but because their audiences had the engagement depth that mass-reach partnerships can't replicate. I validated PMF with each audience before every launch, A/B testing messaging and positioning before committing a dollar to scale. The creator-audience relationship was the product. My job was to make sure the brand deserved to be inside it.

  • Built detailed audience personas per creator — purchasing behavior, identity signals, and the specific jobs-to-be-done that drove trust in that creator's recommendations before touching any product decisions
  • Validated product-market fit before every launch — A/B tested messaging, positioning, and offer framing with each audience to confirm brand fit before scaling ad spend
  • Mapped the full customer journey from content discovery through first purchase to repeat buy — identified drop-off points and built the brand experience around closing them
  • Managed creator relationships end-to-end — stakeholder alignment, launch sequencing, and performance feedback loops that fed directly into the next partnership brief
  • Built and scaled a repeatable discovery and launch framework — the same playbook that worked for the first partnership worked for the fifth, with each cycle refining the inputs and compounding the results
  • Owned all marketing, operations, and product decisions — no outside funding, no team to delegate to; every dollar spent and every channel tested was a deliberate call

What I'd Do Differently

Instrument the customer journey earlier. We had strong intuitions about where drop-off was happening. We were usually right, but we were slower to act than we should have been because the data wasn't structured enough to escalate urgency internally.
Systematize creator discovery sooner. The early partnerships were found through relationships and instinct. It worked, but building a repeatable sourcing framework from the start would have let us scale the model faster without quality dropping.
Invest in retention mechanics from day one. We optimized hard for acquisition. The brands that performed best long-term were the ones where we'd built a real repeat-purchase loop — and we learned that too late in the first few partnerships.

An AI project I built to run Kabba.

Running a startup generates a lot of data and a lot of noise. I built this to cut through both — saving me 1–2 hours a day on reporting, analysis, and context switching.

Live — running daily
Personal Project · 2026

Nahom's HQ — Personal Operations & Business Intelligence Dashboard

I was running Kabba from five different places at once. Google Sheets for business data, Gmail for everything else, a separate calendar, AI tools in another tab. Every morning started with 20 minutes of opening tabs and trying to remember where things stood. That's not how a CEO should start their day. So I built one screen that shows me everything.

What it does

Business Intelligence

Pulls weekly KPIs directly from our Google Sheet and shows me Kabba's health in seconds — passengers, MRR, margin, open seat rate, complaints, driver churn. Includes a "Default Alive / Default Dead" indicator (a Y Combinator framework) and a Peacetime / Wartime mode that flags whether we're in a crisis or a growth phase.

AI Agents

Two AI agents — Blen (CEO & Operations) and Leul (Finance) — read the weekly data and write structured reports with strategic recommendations. They have persistent memory across weeks, so they can say "open seat rate has been above 8% for three consecutive weeks" rather than treating every week in isolation.

Personal Layer

Top inbox emails and today's calendar — all on the same screen as the business data. No tab switching. No context loss. The morning brief is one screen.

Selam AI

A personal assistant built on Claude that drafts email replies in my voice, manages calendar events, and has full context of my inbox and schedule. I give it a task in plain English and it handles the output.

The time it saved

5–7 hrs

saved every week

5 tabs

replaced by one screen

100%

of weekly reporting automated

Next.js 15 TypeScript Tailwind CSS Claude API Google Sheets API Gmail API Google Calendar API Recharts
View on GitHub

What I bring to the table.

Product Management

Product Roadmapping & Backlog Prioritization
User Stories, PRDs & Acceptance Criteria
OKRs & Metrics Frameworks
Product Discovery & User Research
Agile / Scrum Methodology
Prioritization Frameworks (RICE, MoSCoW)
A/B Testing & Experimentation

Business & Strategy

Founder Experience (0 to Scale, Bootstrapped)
Stakeholder Management & Alignment
Cross-functional Leadership
Competitive & Market Analysis
Business Case Development
Go-to-Market Coordination
B2B & B2C Product Strategy
Executive Communication

Technology

REST APIs & OAuth Integration
SQL & Python
AWS Cloud Services
ERP Systems (NetSuite, Sage Intacct, Oracle)
Power BI & Tableau
Jira & Project Tracking
EDI Standards

Domain Expertise

Transportation & Urban Mobility
Supply Chain & Logistics Operations
E-Commerce & Fulfillment Technology
Fleet Management Systems
Payment Systems & Gateway Integration
Emerging Markets Product Strategy
SaaS Platform Architecture

Looking for my next role.

I am actively exploring new opportunities. If you are looking for someone who has built from zero and knows how to get things done, I would love to connect.