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/

Sean Kelly, co-founder and CEO of Amperon and a veteran power-markets trader, sits down with Rohit Yadav in this "AI Meets the Physical World" series episode to walk through where energy forecasting and grid intelligence actually stand today — across AI-driven load growth, weather volatility, the flexibility stack, hyperscaler and utility demand, and the broader grid transformation underway.

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 forecasting as the foundational infrastructure layer of a modern grid.

Chapters:00:00 — Introduction: The "AI Meets the Physical World" series00:44 — What Amperon is, and why AI was the thesis from day one01:32 — Scale and scope: 165 customers, 51 million meters, remote-first02:41 — AI as demand driver versus AI as the grid's stabilizer04:45 — A short history of forecasting: the 15-day model and the European model06:15 — Why weather got harder: one-in-100-year events every few months07:30 — Smart meters and electricity bills becoming mainstream conversation08:42 — Who Amperon serves: retailers, traders, IPPs, utilities, and data centers12:04 — What's next: becoming an end-to-end system of insight and action14:21 — Why the trading decision always stays with the customer16:39 — Grid reality: data centers, volatility, and demand response 2.019:17 — What it means for forecasting: EVs, rooftop solar, and home storage21:39 — The flexibility stack and the 50–100 hours that decide reliability23:26 — What's actually lagging: bureaucracy, interconnection queues, data, and talent25:59 — Why there will never be one global grid30:37 — Who captures the value: hyperscalers, utilities, incumbents, and startups33:01 — Amperon's superpowers: ensemble models, weather data, and AI in the workflow35:49 — Closing worldview: the problem and the solution are both AI

🔑 Key Insights You'll Walk Away With:➡️ The three structural forces reshaping how the grid operates compared to thirty years ago➡️ Why AI has to win as the grid's stabilizer over the next five years➡️ How energy forecasting evolved from a 15-day trading tool into grid-critical infrastructure➡️ Why Amperon runs six to eight models under every forecast, reweighted and retrained every hour➡️ Why flexibility is the only real alternative to blackouts — and the 50 to 100 hours that actually matter➡️ How data centers could become the new demand response, echoing the early-2000s playbook➡️ Why there will never be one global grid, and why local market expertise becomes a moat➡️ How hyperscalers and utilities operate on different clocks but represent two durable customer segments➡️ Why the same AI creating the demand problem is also the key to solving it

Links:Sean Kelly: https://www.linkedin.com/in/sean-kelly-0792626/Amperon: https://www.amperon.co/

Rohit Yadav: https://www.linkedin.com/in/rohityadav23/Newsletter: https://yadavrohit.substack.com/

While most discussions about the energy transition focus on EVs, a broader transformation is underway. Homes are adopting heat pumps and solar, factories are moving away from fossil fuels, data centers are developing their own storage, and AI is accelerating battery innovation from research to manufacturing.

Dong-Su Kim, CEO and Board Member of LG Technology Ventures, joins Rohit Yadav in this Physical AI Series episode to outline the scope of this unprecedented energy transformation across generation, storage, distribution, and consumption.

The conversation moves through the battery chemistry landscape, why so many well-funded battery startups have failed, where China still holds structural advantages, and where startups in the West can still win. It is a practical, grounded view from someone who sees the full picture, from the cell to the grid to the home.

For founders, operators, and investors trying to understand where energy and batteries are heading in the AI era, this episode is a sharp read on the physical layer that the entire digital economy now depends on.

Chapters: 

• 00:00 — Introduction

• 00:37 — Why this is a once-in-a-century transformation across the entire energy ecosystem 

• 03:04 — Beyond generation: storage, distribution, and consumption are all being transformed 

• 04:38 — The virtuous cycle between AI and energy

• 06:55 — Why short term capital is flowing to AI and what it means for energy startups 

• 08:58 — The 2035 picture: centralized and local generation will coexist 

• 12:41 — The battery chemistry landscape: lithium ion, LFP, sodium, solid state 

• 16:51 — The corporate investor landscape across China, US, and OEMs 

• 19:02 — Where startups can still win in the battery value chain 

• 22:08 — Force Nano and the niche application opportunity in defense 

• 23:24 — Critical minerals, China concentration, and the diversification path 

• 26:29 — Why so many well funded battery startups have failed 

• 31:35 — The signal that separates real breakthroughs from well funded noise 

• 34:54 — Powerline and AI for energy storage system operators 

• 35:50 — The next frontier: distributed storage in homes, appliances, and vehicles

🔑 Key Insights You'll Walk Away With:

• ➡️ Why the energy transformation is much broader than EVs and spans the entire ecosystem 

• ➡️ How AI is increasing demand for energy storage while accelerating battery development at the same time 

• ➡️ Why the short term capital crunch in energy is temporary and is already starting to reverse 

• ➡️ Why 2035 will be defined by the coexistence of centralized and local generation 

• ➡️ Why lithium ion variants will remain dominant and why sodium batteries are the one to watch next 

• ➡️ Why customers today prioritize cost, reliability, and safety over capacity 

• ➡️ Why batteries are extremely difficult to manufacture at scale with high yields

•  ➡️ Why China will continue to dominate refining and precursor manufacturing for the foreseeable future 

• ➡️ Why must have pain point and ecosystem readiness are the two filters that separate winners from noise 

• ➡️ Why distributed storage will move into homes, appliances, and vehicles over the next decade

Links:

Dong-Su Kim: https://www.linkedin.com/in/dong-su-kim-97617/ 

LG Technology Ventures: https://www.lgtechventures.com/ 

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

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

Arvin Ganesan, CEO of Fourth Power and former Head of Global Energy and Environmental Policy at Apple, sits down with Rohit Yadav in this "AI meets the Physical World" Series episode to walk through where the energy storage market actually stands today across long duration storage, lithium-ion, supply chain dynamics, hyperscaler demand, and the broader grid transformation underway.

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 long duration energy storage as a category.

Chapters:

00:00 — Introduction: The Series and the energy transition

00:46 — Why the grid is being reshaped by load growth, generation diversity, and weather05:01 — Inside Fourth Power's thermal battery technology

06:56 — Electricity versus industrial heat as a use case

07:23 — Rethinking the short duration versus long duration label

08:43 — A theory of abundance: building from petroleum coke

10:05 — Pilot project, commercial timeline, and 25 megawatt modules

10:46 — Mapping the full flexibility stack across storage technologies

13:10 — How long duration storage attributes shape end use cases

14:21 — Hyperscalers, utilities, and the two customer segments for storage

17:29 — AI, peakers, and the long term gas exposure question

20:31 — The global supply chain equation in storage

22:10 — Supply chain as a proxy for scalability and investor confidence

23:21 — Moving from pilot to commercial: lessons from the storage boom and bust

25:00 — Hardware versus software: how deep tech founders navigate the capital gap

26:47 — Where most hardware startups struggle to scale

27:43 — Closing worldview on the future of energy and storage

🔑 Key Insights You'll Walk Away With:

➡️ The three structural forces reshaping how the grid operates compared to thirty years ago

➡️ Why the short versus long duration storage debate misses the real question of grid value

➡️ How Fourth Power's thermal battery stores energy in carbon at extreme temperatures

➡️ Why building from abundant materials changes the scalability profile of a storage company

➡️ Why supply chain has become a primary signal investors and customers look at in hardware

➡️ How hyperscalers and utilities operate on different clocks but represent two durable customer segments

➡️ Why the first commercial project is the hardest capital leap for deep tech hardware founders

➡️ Why discipline on technology risk before scaling manufacturing separates survivors from casualties

➡️ Why the next decade may be a golden time for energy technologies that deliver on what they promise

Links:

Arvin Ganesan: https://www.linkedin.com/in/arvin-ganesan-40562a1/

Fourth Power: https://gofourth.com/

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

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

Gareth Evans, Founder and CEO of VECKTA and host of the Renewable Ride podcast, sits down with Rohit Yadav in this episode to break down where the energy market is actually heading — from the aging US grid and rising power costs to the rise of on-site energy systems, the prosumer model, and what climate and energy tech founders need to know in 2026.Whether you are a founder, operator, investor, or simply curious about the energy transition and the future of distributed power, this episode will sharpen how you think about energy as a category.Chapters:00:00 — Introduction: TheOnePoint Podcast and meet Gareth Evans00:37 — What is VECKTA and the on-site energy opportunity01:33 — From oil and gas to renewable energy: Gareth's journey03:18 — The changing US energy landscape03:50 — Why the US grid earned a D-plus rating05:00 — $150B in annual outage costs and the rise of on-site energy systems06:30 — Global cost comparison: Germany, China, and the competitive picture07:48 — Production vs. delivery: nuclear, gas, and the role of renewables09:30 — Why small, agile systems at the edge can move faster than mega-projects12:42 — Top three takeaways to solve the energy challenge14:12 — The state of climate and energy tech venture investing15:30 — How generalist VCs are reentering the energy market17:02 — Two hot areas in climate tech: the rise of the prosumer19:24 — Inside Gareth's fundraising journey from pre-seed to Series A23:09 — Why one word in your pitch deck can shrink your TAM25:09 — What Gareth would change about his fundraising approach25:54 — The single best fundraising tip Gareth got recently26:57 — Accelerators and competitions: what actually works28:53 — Should governments fund climate tech startups31:36 — The K2 lesson: why culture beats tools and process33:14 — Closing thoughts on the energy and venture landscape🔑 Key Insights You'll Walk Away With:➡️ Why the US grid earned a D-plus rating and what it means for businesses building for the future➡️ The shift from passive energy consumer to active prosumer who generates, stores, and trades energy➡️ Why power delivery, not generation, is the real bottleneck in the energy transition➡️ How on-site energy systems deliver resilience, lower operating costs, and stronger margins simultaneously➡️ Why small, distributed, edge-based systems can scale faster than large centralized projects➡️ Why generalist VCs are returning to climate and energy tech after years on the sidelines➡️ How one word in a pitch deck can shrink an investor's view of your total addressable market➡️ Why fundraising is a long-term relationship, not a transaction, and what changes from pre-seed to Series A➡️ The K2 lesson: why culture, behaviors, and beliefs outperform tools and processesLinks:Gareth Evans: https://www.linkedin.com/in/gareth-evans-41015726/VECKTA: https://www.veckta.com/Renewable Ride Podcast: https://veckta.com/renewable-rides-podcast/Rohit Yadav: https://www.linkedin.com/in/rohityadav23/Newsletter: https://yadavrohit.substack.com/

What does it really take to build in robotics in 2026, when 70 to 80 percent of the investment dollars are flowing into mega rounds and a handful of companies are collecting the majority of the capital? 🤖

Sanjay Aggarwal, Venture Partner at F Prime Capital and author of the 2026 State of Robotics Report, sits down with Rohit Yadav in this Physical AI Series episode to break down where the robotics market actually stands today across humanoids, autonomous vehicles, warehousing, agriculture, defense, and the broader physical AI stack.

From close to 20 billion dollars invested across the US and Europe in each of the last two years, to Waymo's 16 billion dollar round in 2026, to why a 30 second humanoid demo is very far from a robot that runs 12, 14, 18, or 24 hours a day in a real manufacturing setting, this conversation is a grounded, data-backed walkthrough of the global robotics landscape.

Whether you are a founder, operator, investor, or just trying to understand where physical AI is actually heading, this episode will sharpen how you think about robotics as an investable category.

Chapters:00:00 — Introduction: Physical AI Series and the 2026 State of Robotics Report00:46 — Why the robotics investment market is at an all time high02:00 — The mega round economy: 20 billion dollars, 40 to 50 companies, and concentration02:53 — Healthy maturity or consensus chasing? Waymo, Anduril, and humanoid foundation models05:00 — Humanoids: where the hardware is mature and where the software still is not07:37 — US vs China: who leads on hardware, who leads on software08:17 — Is there still room for early stage founders in the humanoid era10:31 — The 2025 shutdowns: the four part framework for why robotics companies fail22:04 — Autonomous vehicles: the hype cycle, the winter, and the scale up phase24:24 — Beyond robotaxis: trucking, sidewalk delivery, AMRs in warehouses26:19 — The next frontier in physical AI: defense, manufacturing, security, science30:07 — US vs China robotics: supply chain, talent, adoption speed, and IPO markets34:16 — India in robotics: Unbox Robotics, deep tech VC maturity, and the talent question36:25 — Closing thoughts on the state of the robotics ecosystem

🔑 Key Insights You'll Walk Away With:

➡️ Why 70 to 80 percent of robotics investment dollars are concentrated in mega rounds above 100 to 200 million➡️ The two parallel paths in humanoids: mature hardware versus still early software➡️ Why most useful robots in the world are not humanoids and why fit for purpose form factors still win➡️ The four part framework for building a robotics business: market, use case, technology, capital strategy➡️ Why harvesting crops failed but material movement on the farm worked at Burro➡️ Why passenger autonomous vehicles were the hardest problem to solve and what that unlocks downstream➡️ Why China leads on adoption speed: lidar in EVs, consumer robotics, and a lower IPO bar➡️ Why the US is uniquely positioned to fund billion dollar frontier model companies➡️ Why India has the talent for robotics but the deep tech VC ecosystem is still nascent

Links:Sanjay Aggarwal: https://www.linkedin.com/in/sanjaykaggarwal/ F Prime Capital: https://www.fprimecapital.com/

Rohit Yadav: https://www.linkedin.com/in/rohityadav23/Newsletter: https://yadavrohit.substack.com/

What does it really take to build a scale consumer company in a country where two players control most categories, the cost of capital is high, and a billion consumers each carry world-class aspirations on lower incomes? 🇮🇳

Vivek Gambhir, Venture Partner at Lightspeed India and Chairperson of Imagine Marketing (the parent company of boAT), sits down with Rohit Yadav in this special India Series episode to break down how the Indian consumer ecosystem actually works, what separates winning founders from the rest, and why India is not the next China.

From Lightspeed India's 2.9 billion dollar AUM, 100 plus active investments, and 15 plus unicorns including OYO, Pine Labs, Physicswallah, and Zepto, to the boAT story of becoming the number two headphones brand in the world by volume after Apple, this conversation is a grounded walkthrough of what it means to invest in and scale Indian consumer companies in 2026.

Whether you are a founder, operator, investor, or just trying to understand the Indian consumer ecosystem with depth, this episode will sharpen how you think about building in India.

Chapters:00:00 — Introduction: Lightspeed India, Imagine Marketing, and the India Series00:30 — Lightspeed India: 18 years, 2.9 billion AUM, and the one Lightspeed model03:00 — Indian startup KPIs vs US: cost of capital, CAC, and unit economics05:00 — Why the additional risk premium on India is unjustified07:00 — The currency depreciation argument and what dollar return funds should price in09:00 — How the Indian consumer is fundamentally different10:30 — The expectation income gap: world-class aspirations on lower incomes12:00 — India One vs Tier 2 vs Tier 3: why income segments matter more than geography14:00 — Why omnichannel happened faster in India than anywhere else16:00 — The boAT, Mamaearth, and Sleep Company channel mix breakdown18:00 — Storytelling vs product innovation: where Indian brands actually win20:00 — SolarSquare and the 30 year guarantee of trust23:00 — M and A in Indian consumer: Mamaearth, Honasa, and the synergistic playbook26:00 — Recalibrating LP assumptions: India is the next India, not the next China28:00 — Beyond consumer: M-Stack and the AI native chemical company opportunity30:00 — The global Indian companies emerging: Pocket FM, Zetwork, Lenskart, Innovaccer32:00 — The boAT story: four Ps, founder hustle, and the marketplace tailwind34:00 — When to diversify and when not to: lessons from the boAT wearables misstep37:00 — The talent question: 15 percent of founders are second time founders39:00 — The biggest talent gap in India: scaling up, not building41:00 — Why divergence in India creates more opportunity than convergence43:00 — Building a unicorn in India is about addressing a billion dreams

🔑 Key Insights You'll Walk Away With:

➡️ Why Indian valuations are lower at early stages but the bar to scale up is higher➡️ Why India has the highest expectation income gap in the world and what it means for product strategy➡️ Why income segments matter more than tier 1 vs tier 2 vs tier 3 geography➡️ How boAT, Mamaearth, and Sleep Company became omnichannel faster than US peers➡️ Why the top 5 percent in tier 2 cities behaves like the top 5 percent in metros➡️ Why power law dynamics that worked in China may not apply to India➡️ Why the wearables move was a strategic misstep for boAT and what every founder can learn from it➡️ The three biggest talent gaps: founder to CEO, when to professionalize, and protecting the soul➡️ Why building a unicorn in India is about addressing a billion dreams, and that creates Decacorns

Links:Vivek Gambhir: https://www.linkedin.com/in/vivekgambhirLightspeed India: https://lsvp.com/Rohit Yadav: https://www.linkedin.com/in/rohityadav23/Newsletter: https://yadavrohit.substack.com/

What happens when an IIT Delhi grad who started building software in 1998 — back when getting a phone line in India took six to eight months — co-founds Pine Labs, then GlobalLogic, and 25+ years later walks across the table to build a global venture firm investing across India, the US, and Europe?

Rajul Garg, founder and Managing Partner of Leo Capital, sits down with Rohit Yadav in this special India Series episode to break down nearly three decades of building, scaling, and now investing — from a single seat that has lived both sides of the cap table. From explaining why Pine Labs only became what it is today after a 2013–14 pivot that moved the business out from behind the banks and directly to the merchants, to why an AI startup in Bangalore raises at $15–20M while the same maturity in the Bay Area raises at $30–50M post-YC, to why India should be read as a combination of China and Israel rather than a single domestic market, this conversation is a structural look at how the Indian startup ecosystem has matured over two decades and where the next chapter is heading.

Whether you're a founder, an LP, a venture investor, or someone trying to understand why India is now firmly in the top three venture markets globally alongside the US and China, this one will reshape how you think about cross-border building, capital efficiency, and the levels of knowing required to invest in India.

🔑 Key Insights You'll Walk Away With:➡️ Why a global-first VC model is structurally different from India-only funds and from US firms that opened an India office — and what that unlocks for founders trying to scale across continents➡️ The four contributions Rajul credits for Pine Labs becoming what it is over 27 years — and the pivot from sitting behind the banks to commanding the merchant relationship that changed everything➡️ Why a Bangalore SaaS founder had nearly closed the gap to the Bay Area pre-COVID — and how the AI wave reopened a 2x valuation differential almost overnight➡️ The single biggest differentiator between founders who scale and founders who stagnate — illustrated through Pine Labs, Meesho's move from social commerce to horizontal e-commerce, and Lambda Test's pivot into AI testing➡️ Why "energy match" matters more than "skills match" when building early-stage teams in India — and the reminder Rajul gives young founders about who they should actually be hiring➡️ The two facts about Indian talent that global LPs consistently underestimate — and the "levels of knowing" framework for understanding India as an asset class➡️ Why going global from India requires buying a one-way ticket rather than maximizing a two-week calendar — and why a global co-founder beats a global trip every time➡️ Why the Indian B2B buyer is so value-conscious that the same product sells for $100K in the US and $25K in India — and what that means for which companies must go global➡️ Why the IPO market has become the most important silver lining of the last five years — and why the M&A market is still a long way behind➡️ The one-word answer Rajul gives when asked what building a unicorn in India is really about — and why 2030 will be bigger, better, faster, and more liquid

Links:Rajul Garg: https://www.linkedin.com/in/rajulgarg/Leo Capital: https://leo.capital/Rohit Yadav: https://www.linkedin.com/in/rohityadav23Newsletter: https://yadavrohit.substack.com/