Every year, our tech community gathers for two days to learn, share knowledge, and connect. Over 200 tech talents, all in the same room, presenting their work, celebrating wins, and learning from each other through talks that showcase what’s being done across trivago’s tech landscape.
Over 200 tech talents. 88 presenters. 2 days. One theme running through all of it: Frictionless.
Before tech, we focus on people
This year’s event kicked off with our Chief Technology Officer Ioannis doing something unexpected: putting down the slides and asking everyone to stand up.
”Find a person you don’t know — or at least someone you haven’t spoken to in the last six months. You have two minutes.”
The room filled with noise almost immediately. One person bumped into a colleague who had been at trivago for many years, and they’d never actually spoken. That moment, Ioannis said, was exactly the point.
”That’s why it’s called Tech Get Together. Connection is one of the most important things we want to achieve here. When people connect, they build trust — and trust is what makes us better as a tech organization.”
Why Frictionless?
The theme “Frictionless” wasn’t chosen at random. Ioannis described it simply:
“A process, experience, or movement that happens smoothly, easily, and without any obstacles, delays, or resistance.”
For trivago, that maps directly onto two areas: the experience users have with our product, and the experience engineers have building it, from coding to prototyping to deployment. Both matter, and both of them were core to the agenda.
By the end of the two days, the goal was for everyone to leave with three things: stronger cross-team connections, a clearer end-to-end picture of the trivago tech ecosystem, and at least one concrete thing to take back into their day-to-day work.
The AI arc: from AI-assisted to AI-powered
AI was the main storyline of this event.
Ioannis traced the arc of how the conversation at Tech Get Together has shifted over the years. In 2024, the question was whether AI was just a hype. Last year, the message was “we’re experimenting and actively trying things out”. This year? Around half the talks were about how teams are actively applying AI — improving codebases, rethinking infrastructure, and scaling workflows in ways that would have seemed ambitious two years ago. The growth in adoption has been exponential, and it shows.
All of this is in service of an ambitious vision: our 600+ tech talents making the impact of 6,000 — with AI as the multiplier that gets us there.
We’re moving from AI that assists to AI that executes. From using AI as a productivity tool to orchestrating a fleet of agents that do the work we want, scaling our impact. We’re moving away from execution and into orchestration — and the roles in tech are evolving alongside it.
Gene Kim: vibe coding, product, and lessons learned
The keynote came from Gene Kim, author, researcher, and one of the people who helped define the DevOps movement. He drew a direct parallel to the shift DevOps created: just as moving from yearly deployments to deploying multiple times a day transformed how high-performing tech organisations worked, AI-assisted development (“vibe coding”) is poised to do the same, just bigger and faster.
His central point: when coding becomes fast and cheap, every other delay becomes the bottleneck.
”It’s like going to Disneyland where the rides are over instantly — all you’re left with is the queue. The job of leaders becomes: how do you make sure no one is waiting?”
The implication isn’t just about individual productivity. Gene’s argument is that AI changes the communication topology of entire organisations: which teams need to coordinate, which dependencies disappear, and where the real friction lives. That’s a leadership challenge as much as a technical one, and one that touches everyone in the value stream.
He was also clear that teams seeing real transformation aren’t just using better tools. They’re changing how they work. Low double-digit productivity gains are a sign you’re looking in the wrong place. The 10x gains come from rethinking the way work flows.
”This is going to be the greatest leadership challenge of the last 100 years for any organisation that relies on software.”
Inside the agenda
The talks from our own teams showed what this transformation looks like from the inside.
Engineering workflows being rebuilt around AI-generated code that meets the quality bar for production. Infrastructure being rethought to scale alongside agentic systems. The sessions weren’t theoretical; they were talents sharing what they’d actually shipped and what they’d learned.
The agenda went deep across the diverse tech landscape. Talents brought their audiences inside different parts of how trivago works, with deep dives into data engineering, backend, frontend, and beyond. Sessions covered everything from managing a codebase at scale to how teams have woven AI into their day-to-day workflows. Practical, specific, and grounded in real experience.
Not all sessions were about wins, either. The Fuck Up Hour, a Tech Get Together staple, gave talents the floor to share what went wrong and what they learned from it. Honest, lighthearted, and a reminder that how we handle mistakes matters just as much as the successes.
Beyond the sessions
Of course, Tech Get Together isn’t only about the talks.
This year’s venue, Skihalle Neuss, added something a little different to the mix. Between sessions, talents got the chance to hit the slopes, with skiing and snowboarding right on site, and fun team winter games. There’s no better way to reset after a day packed with presentations than a run in the snow with your colleagues.
And as any Tech Get Together regular will know, the second evening wouldn’t be complete without the TGT Quiz, a beloved tradition that’s been part of the event for years. Competitive, chaotic, and a perfect note to end two intense days on.
The culture underneath it
What keeps Tech Get Together meaningful, beyond the content, is what it reveals about how trivago’s tech community operates.
Ioannis described it this way: “We’re agile, open to change. People are open. I see real curiosity and a genuine drive to adopt and improve. There’s good trust between people. They approach each other, discuss challenges openly, address opportunities directly.”
That’s not a given in a 600-person tech organisation. Building it takes deliberate effort, and events like this one are part of how it gets maintained.
The format reflects that. This isn’t a conference where a handful of leaders broadcast to the rest. 88 people from across the company got up to share their projects, their experiments, their findings. The agenda was carried by the talents for talents.
”Explore” was then. Now it’s adopt and master
Our Chief Product Officer Andrej brought the two days to a close with a reflection on how far trivago has come with AI — and a clear framing for where we go next: the theme used to be explore. Now it’s adopt and master.
He closed with a thank you to everyone who made it happen: over 88 contributors and presenters who carried the agenda, our keynote speaker Gene Kim and invited guests, Florian Schürfeld, Information Systems Lead and organiser of the event from the tech side, and our Events team who brought it all together. Tech Get Together, he said, is the cornerstone of how we learn from each other at trivago — and this edition showed just how much knowledge there is to build on.
What we’re taking into the rest of the year
Ioannis opened with a call to connect and share. Andrej closed with a call to build on what we learned.
That’s the arc Tech Get Together 2026 traced — and it points clearly to where we’re heading. AI adoption at trivago is growing exponentially, and with it, the nature of our work is shifting in a fundamental way. We’re moving away from routine execution and towards orchestration: directing AI, shaping outcomes, and making decisions that only humans can make. Engineers, data people, product folks — everyone in the tech organisation is evolving into a new kind of role.
That shift is what makes our vision feel real: 600+ talents with the impact of 6,000. Not by working harder, but by working differently — with AI as the multiplier and frictionless workflows as the foundation.
Nobody has all the answers yet. But after two days of honest conversations, shared learnings, and a room full of people genuinely excited about what’s ahead — we have everything we need to figure it out together.
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