Pathways
Pathways
Pathways
Timeline
2023 - 3 month
Team
3 Engineers, PM, Learning Experience
Outcome
From learning chaos into progression.
Context
Context
Context
Uhubs is a B2B SaaS platform that helps revenue leaders build more productive teams that hit revenue targets. It works by taking performance and people data from Pulse, a 360 competency assessment tool, to diagnose skill gaps that are holding back individual contributors.
Once gaps are identified, revenue leaders can plug them through tailored development plans - structured learning experiences designed to close those gaps and unlock performance.
Uhubs is a B2B SaaS platform that helps revenue leaders build more productive teams that hit revenue targets. It works by taking performance and people data from Pulse, a 360 competency assessment tool, to diagnose skill gaps that are holding back individual contributors.
Once gaps are identified, revenue leaders can plug them through tailored development plans - structured learning experiences designed to close those gaps and unlock performance.
The problem
The problem
The problem
The concept worked in principle: diagnose gaps through Pulse, create development plans, plug those gaps through learning. But as users scaled their teams, employee development and upskilling became a nightmare.
Managers were responsible for onboarding new hires, upskilling existing team members, and supporting multiple roles across their organisations. The platform had hundreds of learning modules scattered everywhere (originally called "Buckets") - all the necessary content existed, but it was fragmented and disorganised.
The result: managers couldn't easily create structured learning experiences. Employees had no idea what to focus on next. Onboarding was inconsistent. New reps took longer to ramp. Both managers and employees were drowning in cognitive load, trying to make sense of a chaotic library of content.
Every morning, reps started from scratch.
They’d spend the first part of their day explaining who they’re looking for: criteria, company size, industry, role. Then they’d scour the data. Then they’d research each prospect individually. They’d jump to LinkedIn to verify freshness. They’d check the company website to confirm technologies.
They’d map the buying committee. Then they’d draft the outreach.
This entire cycle happened every single day. By the time they were ready to reach out, they’d already context-switched five times and lost focus.
Every morning, reps started from scratch.
They’d spend the first part of their day explaining who they’re looking for: criteria, company size, industry, role. Then they’d scour the data. Then they’d research each prospect individually. They’d jump to LinkedIn to verify freshness. They’d check the company website to confirm technologies.
They’d map the buying committee. Then they’d draft the outreach.
This entire cycle happened every single day. By the time they were ready to reach out, they’d already context-switched five times and lost focus.
What we learned
What we learned
What we learned
Through user interviews, heatmap analyses, and CS feedback, patterns emerged:
We started with a full discovery phase.
We ran a big round of user interviews to understand the actual workflow of reps when they were searching for leads, prospecting, and qualifying prospects.
We weren’t looking for solutions, at this point. We were looking for pain points.
Where did the time actually go? Where did they get stuck?
We started with a full discovery phase.
We ran a big round of user interviews to understand the actual workflow of reps when they were searching for leads, prospecting, and qualifying prospects.
We weren’t looking for solutions, at this point. We were looking for pain points.
Where did the time actually go? Where did they get stuck?
01
01
Managers need structure, not just content.
Hundreds of scattered modules meant managers had to manually assemble learning paths from scratch. But without a starting point, many never even started - the blank slate was paralysing.
02
Employees had no clarity on what to learn or why.
Without a defined progression tied to their role, people didn't know what came next or how it connected to their job. Completion rates tanked because the learning felt random, not intentional.
Reps had plenty of leads. The problem was noise. They spent hours manually filtering and prioritising just to disqualify prospects that didn’t fit.
03
Consistency broke down as teams scaled.
Manual assembly meant onboarding and development quality varied wildly by manager. Some reps got thoughtful progression. Others got whatever was thrown together last minute. There was no way to ensure the same standard across the organization.
How we thought about it
How we thought about it
How we thought about it
The sales industry has a brutal rhythm. New reps get three months to hit target. Miss it, and you're out. Very little onboarding happens upfront. Instead, reps get thrown into the deep end, and if they can't swim, they get replaced rather than trained.
We realized the problem wasn't just fragmented content or bad interfaces. It was a fundamental mindset: hiring was treated as a test, not an investment. Development was an afterthought, not a system.
But here's what we also noticed: managers weren't the villains in this story. They were caught in the same cycle. Most of them had never received proper coaching or mentoring training. Sales roles move fast and hard - there's no time built in for managers to learn how to develop people. So they defaulted to what they knew: hire, push, replace.
We decided to reframe the entire problem. Instead of thinking about "content management," we started thinking about "learning journeys" - the full cycle from when a rep joins all the way through onboarding, ramp, and ongoing upskilling.
That reframe changed everything. It meant Pathways wasn't just organizing modules. It was saying: development is ongoing, not a one-time event. Managers need support and structure, not just content. And the company's job is to invest in people, not just test them.
The system needed three layers to solve these problems at once.
A data layer that ingests behavioural and buying signals from LinkedIn and the CRM. What reps search for. Who they add. Which deals they’re working. This data becomes the foundation for everything else. It answers Learning 01 because it’s verifiable. Real data from real sources.
An ML layer that learns patterns from that user history. Over time, it understands which prospects matter to each rep, which buying signals correlate with deals, what a good lead actually looks like for them specifically. This is how we solve Learning 02. Not by showing everything. By learning what matters and prioritising ruthlessly.
An AI layer that sits on top and adds context. Why this account? How to engage? What’s the right message? This is the layer that brings it all together and solves Learning 03. Instead of reps jumping between tools to answer these questions, the AI surfaces the answers directly.
The system needed three layers to solve these problems at once.
A data layer that ingests behavioural and buying signals from LinkedIn and the CRM. What reps search for. Who they add. Which deals they’re working. This data becomes the foundation for everything else. It answers Learning 01 because it’s verifiable. Real data from real sources.
An ML layer that learns patterns from that user history. Over time, it understands which prospects matter to each rep, which buying signals correlate with deals, what a good lead actually looks like for them specifically. This is how we solve Learning 02. Not by showing everything. By learning what matters and prioritising ruthlessly.
An AI layer that sits on top and adds context. Why this account? How to engage? What’s the right message? This is the layer that brings it all together and solves Learning 03. Instead of reps jumping between tools to answer these questions, the AI surfaces the answers directly.
What we built
What we built
What we built
Pathways.
Pathways are a learning progression system that organised buckets into role-based journeys. Instead of managers manually assembling paths from hundreds of scattered modules, they select a role and Pathways assembles a structured, sequenced learning path.
It solved three things at once: gave managers a starting point (no blank slate), gave employees clarity on progression, and ensured consistency across the organisation as teams scaled.
Horizon.
Horizon is an AI engine that learns a rep’s ideal customer profile (ICP) through both manual input and behavioural analysis. It watches what they search for, who they add to their CRM, which deals they’re working. The machine learning layer learns their pattern without them having to describe it every single time.
But Horizon isn’t just a recommendation engine. It’s designed to solve the three problems we found in discovery.
Horizon.
Horizon is an AI engine that learns a rep’s ideal customer profile (ICP) through both manual input and behavioural analysis. It watches what they search for, who they add to their CRM, which deals they’re working. The machine learning layer learns their pattern without them having to describe it every single time.
But Horizon isn’t just a recommendation engine. It’s designed to solve the three problems we found in discovery.
01
01
For managers
Pre-built role templates (SDR, AE, Manager, etc.) based on Pulse competency data
Layered bucket architecture (sourced, duplicated, linked) for structure and consistency
Guided customisation - adapt templates rather than build from scratch
Progress tracking dashboard with learning-to-performance correlation
02
02
For employees
Role-specific progression sequenced from fundamentals to advanced
Clear context for why each module matters to their job
Visibility into what's completed and what's next
Clear expectations and accountability
We don’t show reps every possible lead. We surface the prioritized few. Each prospect comes with buying signals explaining why they matter right now. We rank recommendations based on buyer readiness and ICP fit. Reps spend their time on real prospects, not filtering noise.
The outcome
The outcome
The outcome
Pathways quickly became one of Uhubs' most adopted learning features. Within one year:
Usage of learning buckets increased 11x
1,000+ pathways created by customers
Faster, consistent ramps: New hires onboarded more reliably and quickly
Higher completion rates: Learning felt intentional, not random
Pathways quickly became one of Uhubs' most adopted learning features. Within one year:
Usage of learning buckets increased 11x
1,000+ pathways created by customers
Faster, consistent ramps: New hires onboarded more reliably and quickly
Higher completion rates: Learning felt intentional, not random
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Let’s have a conversation.
hello@nasrien.com
© 2026 Designed by Nasrien
•
Made with Figma and Framer.
Let’s have a conversation.
hello@nasrien.com
© 2026 Designed by Nasrien
•
Made with Figma and Framer.