Shalini Aggarwal and Andy Ratsirason, former Amazon executives, have reunited to co-found Tenfali, an AI startup focused on building Agefully, an AI companion for older adults. Their journey from Big Tech to entrepreneurship reveals critical insights about the mindset shifts required to succeed in the AI startup ecosystem.
Aggarwal, 50, spent her final nine months at Amazon working on AI-powered music recommendations before leaving in September 2024. Her inspiration came from a personal place—watching her father struggle with loneliness after retirement and her mother’s passing. She envisioned an AI companion that provides personalized recommendations and schedules activities based on daily routines for seniors. Ratsirason, 37, left Amazon in 2023 after nearly three years, choosing to pursue his entrepreneurial ambitions during the AI boom.
The co-founders identified several Big Tech habits they had to unlearn to succeed in the startup world. At Amazon, they operated with a “build-first” mindset, assuming customers would automatically appear. Their wake-up call came when “almost nobody showed up organically for a few weeks” after launch. They pivoted to prioritizing customer conversations and distribution tests before over-investing in product development.
Frugality became essential after they burned through thousands of dollars in AWS credits within two months due to over-provisioned capacity and AI testing resources left running. They implemented budget alerts, cost monitoring, and purchased a local machine for AI experiments, only using cloud services when necessary for scale.
AI tools transformed their workflow, acting as a “junior engineer” for coding and eliminating the need for certain roles like UI designers. They use AI to scan content, surface relevant ideas, and summarize research, freeing time for customer interviews and attending industry events. Ratsirason notes that launching their product would have required “significantly more capital and head count” just a few years ago—now they need “just two engineers and subscriptions.”
Their Amazon background proved both advantageous and limiting. While they understand scalable processes, they initially struggled with the assumption that “tools and infrastructure are readily available.” The hardest lesson was overcoming the fear of shipping imperfect products, learning that “the real risk isn’t rough edges, it’s building something people don’t need.”
Key Quotes
At Amazon, I didn’t really think about why we were building a product or if people would use it. The ‘build-first’ mindset meant focusing solely on building a good product, knowing the customer was already there.
Andy Ratsirason explains the fundamental difference between Big Tech and startup product development, highlighting how Amazon’s guaranteed customer base created a mindset that proved detrimental when launching their AI startup without existing demand.
A few years ago, launching a usable version of our product, Agefully, would have required significantly more capital and head count. We just need two engineers and subscriptions. I’m grateful to be part of this AI era.
Ratsirason emphasizes how AI tools have dramatically reduced the barriers to entry for startups, enabling a lean team to accomplish what previously required substantial resources and larger teams.
AI acts as a junior engineer, handling a lot of the coding for us with the requirements we set up… I know I don’t need to hire a user interface designer. If I understand the requirements of something, I can quickly draft it with the help of AI.
The co-founders describe how AI tools have eliminated the need for certain traditional startup roles, allowing them to maintain an extremely lean operation while still delivering a functional product.
Coming from Big Tech, we were accustomed to high-polish expectations and assumed anything less would turn users away. We learned that in early-stage startups, the real risk isn’t rough edges, it’s building something people don’t need.
Ratsirason captures the critical mindset shift required when transitioning from Big Tech to startups, emphasizing that perfectionism can be more dangerous than shipping imperfect products that solve real customer problems.
Our Take
This case study represents a microcosm of the broader AI startup revolution currently reshaping Silicon Valley. The co-founders’ journey validates the thesis that AI is fundamentally changing the economics of startup creation, compressing timelines and reducing capital requirements in ways that seemed impossible just years ago. Their struggle with the “build-first” mentality reveals a deeper truth: Big Tech’s resource abundance can actually handicap entrepreneurial instincts. The most striking insight is how AI tools now substitute for junior-level roles, suggesting we’re entering an era where small, AI-augmented teams can compete with much larger organizations. However, their costly AWS mistakes demonstrate that AI infrastructure management remains a critical skill gap for many founders. Their focus on AI companions for seniors is particularly prescient, targeting an underserved demographic as loneliness and aging populations become global challenges. This story should serve as both inspiration and cautionary tale for the wave of Big Tech employees considering AI entrepreneurship.
Why This Matters
This story illuminates the fundamental differences between building AI products in Big Tech versus startups, offering valuable lessons for the growing number of executives leaving established companies to launch AI ventures. As the AI boom accelerates, understanding these mindset shifts becomes critical for success.
The co-founders’ experience highlights how AI democratizes startup creation, dramatically reducing capital and headcount requirements. What once required large teams can now be accomplished with AI tools acting as junior engineers and designers. This trend could reshape the startup landscape, making entrepreneurship more accessible while intensifying competition.
Their emphasis on customer-first development over build-first mentality challenges the product-centric culture of Big Tech, suggesting that AI startups must prioritize market validation earlier. The cost management lessons around cloud resources and AI testing are particularly relevant as more founders navigate expensive AI infrastructure. Their focus on AI companions for seniors also addresses a growing market need as populations age globally, demonstrating how personal experiences can drive meaningful AI innovation.
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Source: https://www.businessinsider.com/left-amazon-to-launch-startup-things-we-had-to-unlearn-2025-12