Jan Lozek, co-founder and Managing Director of Future Energy Ventures (FEV) and a former energy-infrastructure leader at RWE and E.ON, sits down with Rohit Yadav in this "AI Meets the Physical World" series episode to walk through where the energy transition actually stands today as an investment thesis. The conversation spans the shift from climate to sovereignty, the divergence between US and European energy markets, the centralized versus distributed debate, the rise of the intelligence layer, and why the durable venture returns are moving from owning assets to running the software on top of them.

FEV is one of Europe's leading energy-tech venture platforms. Founded in 2016 with a from RWE and E.ON, the firm has backed roughly 50 companies across the intelligence layer of the energy transition, including enspired, GridCare, ev.energy, and Thermondo. FEV has been compounding the same intelligence-layer thesis through an entire cycle, well before AI made grid reliability a mainstream concern.

Whether you are a founder, operator, investor, or simply curious about where physical AI and the energy transition intersect, this episode will sharpen how you think about energy as a sovereignty trade, and about where value accrues in a system where the hardware is increasingly commoditized and the intelligence layer is where the returns live.

Chapters:

00:00 Introduction: The "AI Meets the Physical World" series

00:47 What Future Energy Ventures is, and the intelligence-layer thesis

03:05 From a climate story to geopolitics to AI

06:15 Energy security and Europe's fossil-fuel dependency

07:57 Europe's self-sufficiency versus US AI-driven demand

09:28 The real difference between US and European energy markets

12:01 Centralized versus distributed, and why you need both

16:03 Where the next venture bets come from: data centers and robotics

17:19 Robotics for infrastructure and industrial decarbonization

19:07 Asset-light versus asset-heavy, and bankable assets

22:34 IPOs, exits, and the first ten-billion-euro grid company

23:30 The efficiency hiding inside the grid

25:24 How underwriting changed: team first, then market

27:53 Climate measurement versus energy sovereignty

30:34 China, manufacturing, and Europe's hardware reality

34:28 Owning assets versus privileged access to them

36:02 The future of utilities in ten years

40:01 Closing: an open invitation to founders

🔑 Key Insights You'll Walk Away With:

➡️ Why the energy transition has become a defensive sovereignty strategy rather than a climate story

➡️ Why the US and Europe face the same grid problem wrapped in two opposite narratives

➡️ Why centralized versus distributed is the wrong debate, and why the value sits in the middle

➡️ Why owning infrastructure is not a venture case, but privileged access to it is

➡️ How the same AI driving energy demand is also the tool that has to organize it

➡️ The two overlooked bets: robotics for energy infrastructure and industrial decarbonization

➡️ What China actually taught Europe about hardware, and how to respond

➡️ Why team composition is still the single biggest reason companies fail

➡️ What utilities look like in ten years, and the one thing they will never be good at

Links:

Jan Lozek: https://www.linkedin.com/in/jan-lozek/

Future Energy Ventures: https://www.fev.vc/

Rohit Yadav: https://www.linkedin.com/in/rohityadav23/

Newsletter: https://yadavrohit.substack.com/

We don't have an energy generation problem. We have a delivery problem and every year states throw away terawatt-hours of clean power they can't store. In this "AI Meets the Physical World" series episode, Anurag Kamal, co-founder and CEO of ElectricFish, joins Rohit Yadav to explain how a network of 400 kWh batteries at gas stations could decouple charging speed, and the grid's worst peaks, from the limits of the grid itself.The conversation ranges across distributed battery storage, extreme-fast EV charging, peak-load management, grid services, capital structure, China-vs-US hardware, and the coming shift toward distributed compute.ElectricFish is building a new, two-way electrical grid out of a decentralized network of community-scale batteries. Each unit is a 400 kWh system — sitting between a home battery and a utility-scale one — that packs storage, a fast charger, and control software into a single box, deployed at gas stations to deliver extreme-fast EV charging while acting as a flexible resource for the local grid. It assembles and tests systems in the Bay Area while preparing to scale manufacturing in the Midwest, and unveiled its flagship product at CES 2026 — a useful backdrop for a conversation about turning ubiquitous gas stations into "energy stations."Whether you are a founder, operator, investor, or simply curious about where physical AI and the energy transition intersect, this episode will sharpen how you think about distributed storage as the layer that decouples charging speed — and grid demand — from the limits of the grid itself.Chapters:00:00 — Introduction: the "AI Meets the Physical World" series00:35 — What ElectricFish is: a decentralized grid of 400 kWh community batteries01:35 — The grid as the rate limiter: is distributed storage the new clean-tech story?02:17 — Not a generation problem, a delivery problem — and the waste of curtailment05:35 — From "clean tech" to "energy tech," and the architecture landscape06:36 — Why mobile and co-located batteries struggle to scale09:48 — The scalability thesis in the consumer segment10:00 — "Not an EV charging company": the energy station and everything-in-one-box14:01 — Decoupling charging speed from the limits of the grid14:18 — Planning for four worst hours a year, and a trillion upgrade bill18:23 — Beyond EV charging: balancing the grid and where the moat lives19:59 — Complexity vs. revenue, and grid services as "a hedge fund of energy"24:54 — The three revenue streams, and which customers to chase26:02 — Picking a niche: autonomous fleets, depots, and gas stations27:51 — China hardware, US manufacturing, and the software edge30:24 — Capital structure: venture capital, project finance, and grants32:11 — The distributed compute bet and the "missing middle"33:58 — Closing thoughtsLinks:Anurag Kamal: https://www.linkedin.com/in/anurag-kamal/ElectricFish: https://electricfish.co/Rohit Yadav: https://www.linkedin.com/in/rohityadav23/Newsletter: https://yadavrohit.substack.com/

Jürgen Mayerhofer, co-founder and CEO of enspired and a 20-year veteran of physical energy markets, sits down with Rohit Yadav in this "AI Meets the Physical World" series episode to unpack where AI-driven energy trading and flexibility optimization actually stand today — across battery storage, the flexibility stack, data scarcity, market culture, hyperscaler and data-center demand, EVs, thermal energy storage, and the broader build-out of a more volatile, decentralized grid.

enspired is a fully automated, AI-driven power trading-as-a-service platform that monetizes flexible assets — batteries, pumped storage, CHP, demand-side flex — on short-term power markets. Founded in 2020 in Vienna, the company has grown to around 110 people and extended its Series B to over €40 million to fund global expansion, with backers including Banpu NEXT, Future Energy Ventures, and EnBW New Ventures. It optimizes some of Europe's largest battery projects — including a 103.5 MW / 238.5 MWh asset owned by ECO STOR in Germany — and is expanding beyond Europe into Japan through its partnership with Banpu NEXT. It's a useful backdrop for this conversation: enspired has been running flexibility assets fully automated for nearly seven years, well before AI-induced demand made grid volatility a mainstream concern — and it became the first and only player in its space to publish KPMG-audited monthly portfolio performance.

Chapters:

00:00 — Introduction: the "AI Meets the Physical World" series

00:31 — Jürgen's background: 20+ years in physical energy

01:10 — What enspired is, and the algo-trading DNA from day one

04:05 — Flexibility-as-a-service: how a battery actually gets monetized

05:52 — Fully automated, zero human intervention: 6–7 GW and 100,000+ trades a day

06:53 — Who enspired serves: infrastructure funds, IPPs, and asset owners

07:23 — Scaling with one platform: from Germany to 10 countries 09:38 — The AI stack: from machine learning to reinforcement learning

10:03 — The data problem: why energy is harder than it looks

11:47 — Cybersecurity as the Achilles heel of full automation

12:14 — Why a battery is a "beast" for reinforcement learning

13:17 — The biggest pain point: culture, not technology

15:52 — Why "we'll just build it in-house" almost never works

18:18 — When does trading become fully automated? It depends on the market

21:28 — Where enspired fits in the flexibility equation

22:48 — The founding thesis: more renewables, more need for flexibility

26:45 — Data centers meet the physical grid

27:19 — Real-time pricing of compute as grid optionality

30:24 — Why recurring market disruptions are a feature, not a bug

31:07 — US vs Japan: a volume game versus first-mover markets

35:08 — Flexibility tools: batteries, EVs, and thermal storage

36:17 — The EV smart-charging case: a great idea that hit reality

40:01 — Why thermal energy storage bridges power and heat

43:23 — What happens when more batteries compress the spreads?

47:22 — Walking the talk: KPMG-audited monthly performance

51:47 — Closing thoughts

Links:

Jürgen Mayerhofer: https://www.linkedin.com/in/juergenmayerhofer/

enspired: https://www.enspired-trading.com/

Rohit Yadav: https://www.linkedin.com/in/rohityadav23/

Newsletter: https://yadavrohit.substack.com/