Co-founded Induced AI, an AI-powered browser automation platform, in 2023 at age 18 and raised $2.3M in seed funding led by Sam Altman (OpenAI CEO) and Peak XV Partners, with backing from SignalFire, SV Angel, and Daniel Gross.
Born around 2005, Aryan Sharma is an Indian-origin entrepreneur based in Silicon Valley. He was previously a founding engineer at Layer3, a web3 user acquisition platform. He co-founded Induced AI in 2023 with Ayush Pathak, building an AI-powered browser automation platform that converts plain English workflow instructions into executable code. He networked extensively in San Francisco, cold-emailing and meeting influential people including Sam Altman, eventually securing his investment. The startup raised $2.3M in seed funding in October 2023.
Working in tech since age 13; after high school, received a full scholarship from Eric Schmidt (former Google CEO) to attend any university in America but decided to continue building products independently instead of going to college.
Current position (2025)
Co-founder and CEO of Induced AI, an AI-powered browser automation platform based in Silicon Valley; previously founding engineer at Layer3, a web3 user acquisition and retention platform.
Where the conditions came from
Three sources, read side by side
Each is placed on a −1 to 3 scale from documented evidence, and the three are never added together. A combined total would rank Aryan Sharma against other people. Held apart, they explain why this path ran differently from another one—which is the only comparison this project supports.
The marble itself
What they brought
+1Tailwind
-10+1+2+3
What capability, drive, or early skill is documented in the person rather than their surroundings?
Relentless networker who cold-emailed Sam Altman and offered to work as his secretary. Prior experience as founding engineer at Layer3. Above-average ability and exceptional hustle, but no evidence of prodigy-level cognitive talent.
Where it was dropped
What they were handed
0Neither way
-10+1+2+3
What money, family standing, network, or permission was already in place before the work began?
Indian-origin entrepreneur based in Silicon Valley. No family background information found in research; no evidence of inherited wealth or domain connections.
The shape of the track
What surrounded them
+2Tailwind
-10+1+2+3
What place, timing, institution, or peer group made the next step available?
Physical proximity to Silicon Valley, Sam Altman connection through cold outreach, and the AI automation wave were key ecosystem advantages. Complementary co-founder in Ayush Pathak.
A −1 is a documented headwind, not a missing value; a 0 means the sources record nothing notable either way. Annotation confidence: Low. These are analyst readings of what the sources record, not measurements of merit, talent, or effort. The twenty-two scored dimensions remain available inside the deeper research detail.
What moved through the conditions
Perseverance and luck stay visible—not scored.
Documented perseveranceContinued building Induced AI as a lean team, with bots performing 150K+ actions for enterprises, focusing on automating repetitive back-office workflows like writing emails and shortlisting candidates.
This records repeated behaviour or recovery described by sources; it is not a grit or merit score.
Structural luckThe AI automation wave was a major structural tailwind.
This is an unchosen opening or condition in the record, not an estimate of how much luck caused the outcome.
Describes the starting position, not what the person later made of it.
Cohort percentile: 84
02 Built or converted leverage
12/25 multiplying-capacity score
Strongest observed levers: Complementary team, Started serious reps before 20, Elite ecosystem network.
Measures what was present, not whether it was inherited, earned, self-built, external, or mixed.
Cohort percentile: 78
03 Compounding trajectory
5 documented steps
The timeline below shows the sequence of work and transitions around the selected early milestone. It is evidence of a path, not proof that every step was necessary.
Milestone at age 18
04 Observed career standing
T4 · Specialist-known
Notable, but primarily known within a niche. The tier summarizes documented career recognition through the data cutoff—not Aryan Sharma's worth or future potential.
Each non-zero lever gets a best-supported origin, evidence signals, and confidence. Unresolved is the honest default when the biography cannot distinguish self-built, advantage-enabled, earned, external, or mixed.
Started serious reps before 201/1
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Early online platform (1/2)
Complementary team2/2
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
One or more documented starting advantages plausibly enabled this lever.
Adversity / constraint catalyst (1/2)
Domain proximity1/2
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Direct domain exposure (1/2)Frontier geography (2/2)
Prior reps1/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Early online platform (1/2)
Scarce skill depth1/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Early online platform (1/2)
This is a bounded inference from the current annotations—not a claim about private effort, merit, or the percentage of Aryan Sharma's outcome attributable to any origin.
Luck is not a leftover score.
Structural luck, Encounter luck, Event luck, Outcome variance can change every arrow in the path. This successful-only dataset cannot observe the near-identical paths that did not break through, so luck stays visible and unscored.
Within Founders / operators, Aryan Sharma's starting-advantage total is at the 84th percentile. Separately, their built or converted leverage total is at the 78th percentile. Other T4 profiles average 5.9 / 24 starting advantage and 10.4 / 25 leverage. Similar scores appear in other tiers, so these figures describe positioning—not a cause.
Trajectory
2018 · age 13
Started working in tech
Began working in technology at age 13, building products and learning from founders, operators, and investors around the world.
2022 · age 17
Founding engineer at Layer3
Served as founding engineer at Layer3, a web3 user acquisition and retention solution provider, gaining early startup engineering experience.
2023 · age 18
Co-founded Induced AI
Co-founded Induced AI with Ayush Pathak in early 2023 in Silicon Valley, building an AI-powered browser automation platform that spins up Chromium-based browser instances to automate workflows.
2023 · age 18
Raised $2.3M seed from Sam Altman
Raised $2.3M in seed funding led by Sam Altman (OpenAI CEO) and Peak XV Partners, with backing from SignalFire, SV Angel, Daniel Gross, Nat Friedman's AI grant, and Balaji Srinivasan.
2024 · age 19
Scaling Induced AI
Continued building Induced AI as a lean team, with bots performing 150K+ actions for enterprises, focusing on automating repetitive back-office workflows like writing emails and shortlisting candidates.
Primary leverage engine
Network / capital
Network / capital
Secondary engine
Product / domain insight
Built/converted leverage
12 / 25
evidence: Medium
Built or converted leverage
Multiplying capacity documented later in the path. Measures what was present, not whether it was inherited, earned, self-built, external, or mixed.
Started serious reps before 20
1/1
Prior reps
1/3
Scarce skill depth
1/3
Native distribution
0/3
Elite ecosystem network
2/3
Complementary team
2/2
Structural wave / timing
2/3
Concentration intensity
2/3
Capital safety
0/2
Domain proximity
1/2
Starting-advantage scores (0–2 each)
Access or conditions documented near the beginning of the path. Zero means "no clear evidence in reviewed sources," not "advantage was absent."
Family financial platform
0/2
Parent / family domain
0/2
Inherited audience / network
0/2
Elite institution pipeline
0/2
Frontier geography
2/2
Rare early tools
0/2
Dedicated mentor / coach
0/2
Exceptional peer / cofounder
2/2
Early online platform
1/2
Direct domain exposure
1/2
Prodigy / innate ability
0/2
Adversity / constraint catalyst
1/2
Family context
Indian-origin, based in Silicon Valley. Not much documented about family background. He traveled to San Francisco as a teenager to network with investors and tech leaders, suggesting some means to do so but no documented family wealth.
Parent / family domain
Not documented in reviewed sources; no evidence of parental tech or business domain expertise.
Sharma's primary advantage was his physical proximity to Silicon Valley and his relentless networking — he cold-emailed Sam Altman and other investors, offered to work as Altman's secretary to get close to OpenAI, and eventually secured his investment. His prior experience as founding engineer at Layer3 (web3) gave him some technical credibility. His complementary co-founder Ayush Pathak (previously founding engineer at Thirdweb) provided a strong technical team. The AI automation wave was a major structural tailwind. His Indian-origin background and willingness to travel to SF as a teenager suggest some adversity-driven urgency. Family background is not documented.