LastPass has a rich history as a leading password management company, securing billions of credentials for millions of customers. Today, the company is rapidly expanding into secure access essentials, helping organizations discover unmanaged apps and AI tools, control access across every user, and simplify secure sign-ins – all within the browser.
To support this massive, cloud-based footprint, Chief Technology Officer Jason Rasmussen leads an engineering organization of roughly 200 people. Structured to allow engineers to take ideas from inception all the way to the customer, LastPass requires deep visibility into what it actually takes to ship software on time.
Here is how LastPass leverages Jellyfish to manage unplanned work, benchmark their progress, and measure the impact of their AI transformation.
Replacing the “Divining Rod” with Data
Before Jellyfish, Rasmussen noted a universal truth across the industry: engineering planning was notoriously difficult to measure. Historically, the best managers relied on a “gut sense” to know if a project was on track.
“It always felt like the holy grail,” explains Rasmussen. “I have all these different tools that I need to pull together and they have all these different signals. How do I actually match that up to understand what’s going on? Jellyfish changed the game. I don’t have to spend a bunch of time trying to use a divining rod or interpret the auguries of what’s going on. I can actually go and have a tool that does this for me and spend time interpreting what this means for my business.”
LastPass chose Jellyfish for its “fire and forget” ease of use. By simply plugging in their API keys for Jira, Confluence and GitLab, LastPass gained an immediate, daily reflection of their operations without requiring engineers to manually double-check or input data.
Translating Tech to the Business
For a CTO, bridging the gap between technical execution and executive strategy is critical. Other C-suite executives don’t operate in a world of sprints, pull requests, or story points. They care about business outcomes and roadmap capacity.
Jellyfish serves as the objective source of truth to answer these questions, particularly when it comes to unplanned work. When sales or support teams pull engineers into side tasks, it can quietly derail major initiatives.
“The biggest thing is setting expectations with those outside of engineering as to where engineers’ time is going,” says Rasmussen. “Minimizing the unplanned work and seeing where we’re spending 4-5% of our time helps us minimize that. We can bridge that gap between being deep down in the technical weeds and what it means to the business on the other side.”
Measuring an “Industrial Revolution” in Software
LastPass is currently navigating what Rasmussen describes as an “industrial revolution” in software engineering, one happening over 80 months rather than 80 years.
When LastPass decided to standardize its AI tooling on Claude, they used Jellyfish to measure the rollout. They started with a small group of early adopters and used Jellyfish to prove the success: faster code reviews and a higher volume of pull requests. Once rolled out to the entire organization, Jellyfish tracked the company to 100% adoption.
The results have been staggering. “We have a baseline of before AI came into play,” says Rasmussen. “We can really see the inflection point – the lifecycle of an issue from beginning to end started to shorten. In our case, 30-40% is what we’ve already seen, and our best teams are two to three times faster.”
Crucially, Jellyfish also helps LastPass monitor cognitive load. By tracking how fast teams are moving, leadership can actively ensure that the massive productivity gains from AI don’t result in engineer burnout.
Fostering a Culture of Trust
Rolling out an engineering management platform often comes with hesitation. Early on, LastPass managers and engineers worried Jellyfish might be used as a “Big Brother” productivity policing tool.
Leadership was intentional about educating the team that Jellyfish is used strictly for team and organizational trends – not individual performance tracking. By using the data to remove blockers, reorganize teams efficiently, and highlight the incredible speed gains from AI, the culture completely shifted.
“Now the questions are, ‘Hey, what’s Jellyfish telling us?’” Rasmussen shares. “You have individual engineers asking what the data is showing. They realize the value in it and that it’s meant to be additive and useful for them as well.”
For engineering leaders hesitating to adopt data-driven visibility, Rasmussen offers a clear piece of advice: “There’s no wrong time to start. As we speed up software development and engineers start to free up their time, rather than manufacturing screws, they start to manufacture engines and cars. You can build more complex things. Just start, and ideally, you’re starting with Jellyfish.”
Before Jellyfish:
- Gut-Driven Planning: Forecasting and planning relied heavily on the inherent intuition of experienced managers interpreting the “auguries” rather than looking at hard, objective data.
- Scattered Signals: Tool sprawl across Jira, Confluence, GitLab, and Monday.com made it difficult to pull together a unified picture of engineering health and progress.
- Hidden Unplanned Work: Invisible, out-of-band requests pulled focus away from the roadmap, making it difficult to explain to business stakeholders why certain teams lacked capacity.
With Jellyfish:
- Seamless Visibility: Leveraged a “fire and forget” integration model that aggregated data automatically from existing tools, providing an immediate, daily source of truth.
- Measured AI ROI: Tracked the rollout of Claude to 100% of engineering team, proving a 30-40% reduction in the delivery lifecycle, with top teams moving two to three times faster.
- Executive Translation: Successfully bridged the gap between deep technical metrics (like story points and tech debt) and business outcomes (like roadmap allocation and capacity planning).
- Culture of Trust: Overcame initial fears of “Big Brother” policing, fostering an environment where individual engineers actively ask leadership, “What is Jellyfish telling us?”
To learn more about how Jellyfish can benefit your engineering organization, take a product tour or schedule a demo here.
