Attending the 17th German American Conference at Harvard
The German-American relationship is at a crossroads. That was the theme of the 17th German American Conference (GAC) at Harvard's Kennedy School, and the message came through clearly across three days of panels, keynotes, and conversations. 1000+ students, founders, researchers, and policymakers from the U.S. and Germany gathered to discuss what comes next - for deep-tech innovation, defense policy, autonomy, and the broader transatlantic partnership.
The Conference Framework
GAC brought together perspectives you don't usually find in the same room. Policy experts debating defense strategy. Deep-tech founders discussing hardware manufacturing. Researchers exploring AI ethics. Students asking the questions that forced everyone else to sharpen their answers.
The structure worked: morning keynotes set the agenda, afternoon panels explored specific topics, and evenings opened space for conversation. Three days compressed what would normally take months of scattered readings and random encounters into focused exchange.
What stood out was the openness. People came ready to share ideas, not defend positions. The format encouraged it - small group discussions, accessible speakers, and enough unstructured time to let conversations develop naturally.
Reinventing Innovation
Michael Brigl's[1] talk on "Reinventing 'Made in Germany' for the Next Decade" hit hard. The premise: Germany's industrial success was built on precision manufacturing and engineering excellence, but the next decade demands different fundamentals. Future technologies, long-term investments, and a willingness to bet on emerging sectors before they're proven.
The panel on deep-tech innovation reinforced this. Hardware is hard. Manufacturing at scale is harder. But the U.S. and Germany both have strengths - research institutions, capital, talent - that could matter more if coordinated properly.
Hans Uszkoreit's[2] session on AI's future framed the technical challenges in terms of policy decisions. Where do we draw lines on autonomy? How do we regulate systems that outpace our ability to audit them? What does international cooperation look like when AI development is increasingly a competitive advantage?
These weren't theoretical questions. The people in the room were building the systems, writing the policies, and funding the research.
MIT and the Hardware Reality
The MIT campus tour was a highlight. We visited hardware labs, welding spaces, and design studios - the physical infrastructure where ideas become prototypes. Watching students debug a robotics project in real-time, seeing the iteration marks on workshop equipment, hearing about the timeline from concept to working hardware - it grounded the conference's broader discussions in tangible reality.
Deep-tech isn't just about breakthrough research. It's about access to the tools, the expertise, and the iteration cycles that let you fail fast and learn faster. MIT's campus shows what happens when you invest in that infrastructure consistently over decades.
What Made It Possible
Our participation was enabled by the HPI Engine and the Flow Factory at the University of Münster. Special thanks to Thomas Haskamp[3], Frank Pawlitschek[4], and David Hahn[5] for making it happen. And to Kai Krautter[6] and the team behind GAC - organizing a conference this size with this level of quality is no small feat.
What I valued most was the people. Fresh perspectives, genuine curiosity, and a shared sense that the problems we discussed matter. It's easy to talk about policy in the abstract. Harder to do it in a room full of people actively shaping outcomes.
Takeaways
International collaboration requires more than good intentions. The panels made clear: coordination across borders takes infrastructure - shared research programs, exchange networks, and people willing to bridge cultural and bureaucratic gaps.
Hardware innovation demands patient capital. Deep-tech timelines don't align with typical venture cycles. Germany and the U.S. need funding models that support long development curves.
AI policy is being written now. Not in theoretical frameworks, but in deployment decisions, regulatory choices, and research priorities. The people shaping those decisions are the ones in the room.
Access matters. MIT's campus tour showed what sustained investment in physical infrastructure enables. Students need more than lectures - they need labs, tools, and time to build.
The conference reinforced something simple: progress happens when people from different backgrounds show up, share what they know, and commit to figuring out what comes next together. GAC delivered on that premise.