Try for free
Up On Foil
Up On Foil

Pump Foiling Theory explained by @foilien

31 August 2026 1:02:58 Matthias Kaufmann

Listen to episode

About this episode

Look - we all know - Pump foiling is difficult. We all have our tipps, tricks and ideas on how to pump better, longer or more efficiently. Lucien wasn't happy with the chatter on the docks and wanted to get to the bottom of it. He introduced the Pumpfoil Physics Simulator and the Dynamic Pumpfoil and Wave Riding Simulator.

In this episode, we get to know Lucien (@foilien on Instagram), we learn about the simulators, and you might get one or the other idea how to improve your pump foiling.

Thanks to Jens of the Foilsessions App for supporting the show.

Get your Foiling App here: https://foilsessions.app

Thanks to the team around SurfEars for their commitment.

Get yours here: https://6cZKVD.short.gy/surfears

Thanks to the newest sponsor of the Podcast:

www.vaikobi.com - You’ll find great watersports apparel here!

Thank you for helping me out and get some hidden episodes: patreon.com/UpOnFoil

Check out my Website: www.uponfoil.com

Chapters

00:00 Introduction and Understanding Foiling Mechanics and Physics

07:47 Insights from Personal Experience and Anecdotes

11:57 The Role of Weight and Technique in Pump Foiling

15:58 Using the Simulator for Performance Analysis

20:07 The Importance of Water Temperature and Viscosity

27:55 Lift vs Drag: Understanding Foil Profiles

32:15 Adjusting Parameters for Optimal Performance

35:11 Normalized Power and Efficiency in Pumping

40:55 The Impact of Weight and Setup on Performance

45:15 Diverse Pumping Techniques and Wing Dynamics

51:26 AI in Pumping Simulation and Rider Dynamics

55:00 Neural Networks and Learning to Pump

59:47 Community Feedback and Future Developments

More AI podcast episodes

Browse all →

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Up On Foil. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support