Training investors to build conviction in deeptech across research, validation, and scale.
Cohort starts from 15th March
About Deeptech Track
The Deeptech Track under The VC Fellowship is designed for investors who want to build real conviction in this future. Through rigorous frameworks, real investment cases, and close mentorship from experienced deeptech investors from premier VC firms, the track helps participants understand how deeptech companies are evaluated, where value is created or lost across long innovation cycles, and how to invest with clarity and confidence in technologies that will define the next decade.
Hosting Mentors who are driving investments at
Developing Deep Tech Core Capabilities
Mapping the DeepTech universe
Real segmentation of DeepTech sectors AI infra robotics semiconductors biotech climate space
Why calling everything DeepTech is lazy and misleading
Where real value accrues across the stack
How different sub sectors behave very differently
Value creation cycles in DeepTech
Research breakthroughs vs engineering breakthroughs
Platform shifts vs incremental innovation
Role of timing in DeepTech success
Compute cost curves regulation and geopolitics as value drivers
Reading DeepTech technically without being a researcher
How to read technical papers without a PhD
What to look for in architectures specs and benchmarks
What is provable vs theoretical vs marketing
Common technical red flags in founder pitches
From lab to market commercialization reality
How lab born ideas move to pilots and production
Why pilots often lie about demand
Who actually pays first in DeepTech
Pricing when there are no benchmarks
Manufacturing scale and hardware truth
Prototype vs mass manufacturing challenges
Yield problems cost overruns and timelines
Supply chain and vendor dependency risks
Why contract manufacturing fails in DeepTech
DeepTech case studies winners pivots failures
End to end journeys of 3 to 4 DeepTech startups
Key technical and commercial inflection points
Funding decisions that changed outcomes
What most post mortems miss
DeepTech failures post mortems
Great tech wrong timing
Strong pilots no real adoption
Capital mismatch and premature scaling
Patterns behind silent failures
Founder psychology and team design
Scientist founders vs business leaders
When and how to bring in execution talent
Incentivizing researchers and engineers
Founder investor misalignment and burnout
DeepTech and geopolitics regulation
Export controls and compute restrictions
Defense space energy regulation impacts
Country of origin and jurisdiction risk
How policy quietly picks winners
DeepTech capital stack and best funds
Global and Indian DeepTech focused funds
How grants strategic capital and government money work
How DeepTech fund structures differ
Why traditional VC logic breaks here
Evaluating DeepTech startups as an investor
Breaking risk into tech market and execution
Assessing defensibility patents IP moats
Team credibility beyond resumes
Capital intensity and timeline realism
Investment memo and IC simulation
Deep dive into a real DeepTech startup
Writing an investment memo with uncertainty
IC style debate and pushback
Building conviction without false certainty
Note: This is a high-level overview of the concepts that will be covered in the program. It is not a session-by-session curriculum. The actual program may differ, as some concepts may be covered through additional resources, and new topics may be introduced during live sessions based on learner’s requests and needs.
FAQ's
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