Bringing clarity
to distributed engineering performance
Companies that trust Pensero.
Key outcomes at a glance
What engineering leaders achieve with Pensero
%10
Engineering efficiency
increase across teams
20-30%
AI adoption uplift
across the prganisation
Full Objective Visibility
See who contributes value and how performance evolves over time.
Earlier Issue Detection
Catch performance drops and quality issues before they escalate.
Fair, Data-Driven Decisions
Ground performance, promotion, and coaching in real evidence.
Hidden High Performers
Identify talent beyond perception or organisational noise.
Clear AI Impact
Measure usage, output, and effectiveness across every AI tool.
Team Wellbeing Signals
Detect overwork and burnout early through objective data patterns.
For Morgan, CTO and co-founder of Smeetz, scaling engineering wasn’t just about adding more people or shipping faster. It was about understanding, with clarity, how work actually happens across a distributed team and making better decisions because of it.
With engineers spread across the US, Europe, and North Africa, and a company that had already gone through the complexity of surviving COVID, visibility wasn’t a “nice to have.” It became a prerequisite to operate effectively, fairly, and at scale.
The challenge
Limited visibility in a fast-moving, distributed team
Like many growing companies, Smeetz relied on familiar signals to understand performance. Jira, sprint completion, story points, and bug tracking gave some indication of progress. But those signals were fragmented and static, and they didn’t provide a clear picture of how work translated into real value.
Morgan describes it simply:
“It was more like a feeling… that person is good or not, but it was definitely not based on fact.”
In a fast-paced environment where everyone is multitasking and responsibilities are often blurred, this lack of clarity compounds quickly. Leadership ends up stretched across too many priorities, with little time to deeply understand individual contributions or team dynamics.
Without prior benchmarks or reference points from comparable companies, it was difficult to know whether the team was truly efficient or where improvements were needed.
“I needed a tool that could help me see where I stand… compared to other companies and how my people evolve.”
What started as a visibility gap became a broader challenge: how to move from intuition to evidence, from perception to reality.
The solution
A complete and objective view of engineering work
Pensero introduced a fundamentally different way of understanding engineering performance at Smeetz. Instead of relying on isolated metrics, it brought together all the signals generated across the development workflow and translated them into a coherent, objective view.
For Morgan, the shift was immediate.
“We really have a complete view… like if I was sitting next to all of my developers and I could really check what they were doing.”
What made the difference wasn’t just visibility, but the depth of that visibility. Pensero enabled Smeetz to understand not just how much work was being done, but how complex it was, what impact it had, and how it evolved over time. It also made it possible to detect quality issues early and trace when performance started to change.
One of the most valuable aspects for Morgan has been the ability to understand AI usage in a structured way. As AI becomes a core part of modern engineering workflows, having a clear view of adoption and impact is critical.
“I can see the percentage of code written by AI… and the value of the work, not just the number of lines.”
This allows him to go beyond assumptions and manage AI as a real lever of performance—identifying who is using it effectively, where adoption is lagging, and whether it is actually improving output.
The results
More efficiency, stronger AI adoption, and fairer decisions
With a clearer and more objective understanding of engineering work, Smeetz has started to see tangible improvements across the organization.
Efficiency has increased, with Morgan estimating around a 10% improvement driven by better visibility and the ability to quickly identify where teams are underperforming or facing challenges. Instead of reacting late, the team can now pinpoint when issues begin and address them earlier.
At the same time, AI adoption has grown significantly. By making usage visible and measurable, Pensero has helped drive a 20–30% increase in adoption across the team. More importantly, this adoption is now tied to actual output and impact, not just tool usage.
Beyond performance metrics, one of the most meaningful changes has been in how decisions are made. Visibility has introduced a level of fairness that was previously difficult to achieve.
“You ensure to motivate and keep the right people… because you know exactly who is doing the job.”
Last, but not least, it has also helped surface contributions that might otherwise go unnoticed.
“Some people that are very quiet are in the end doing a lot of the job… without data, you can make the wrong choice.”
This shift from perception to evidence is influencing everything from promotions and coaching to team structure and even wellbeing. By tracking work patterns over time, Morgan can identify when someone might be overextending and intervene before it becomes a problem.
“If someone has pushed too far… you can see it and tell them to rest.”
Unlocking a culture of continuous improvement
While adoption is still expanding across the organization, the direction is clear. The goal is not just for leadership to have visibility, but for managers and individual contributors to actively use the data to improve.
Smeetz is already pushing towards a model where engineers can reflect on their own performance, understand where they are progressing, and identify areas for growth without relying solely on top-down feedback.
“The goal is that individual contributors use the tool to challenge themselves and improve.”
This shift turns visibility into a mechanism for continuous improvement across the entire team.
