Part 6 of 14 in How to Make Your Startup Anti-Fragile: Systems Thinking, Continuous Adaptation, and AI Tools for Indian Founders← Part 5Part 7 →
This chapter explores common mental models in Indian startups and how they can be challenged to improve business resilience. It is part of the series on making startups anti-fragile.
- Mental models are unseen frameworks that influence decision-making in organizations.
- Indian startups often rely on fragile models like 'growth solves all problems' and 'India is like the US but bigger and cheaper.'
- The 'jugaad' mindset can limit scalability if not complemented with robust systems.
- AI can help founders identify and test assumptions embedded in their business strategies.
- Razorpay's proactive approach to regulation demonstrates a shift from seeing compliance as a burden to a strategic advantage.
Mental models are the lenses through which we interpret the world. They are usually invisible until something goes wrong. Senge argued that organizations improve when people learn to surface, test, and revise these models.
Common Fragile Models in Indian Startups
“Growth solves all problems.” This model justified years of cash burn in consumer internet. It worked when capital was abundant and interest rates were low. When the environment changed, companies that had not built learning systems around unit economics discovered they had optimized for the wrong variable.
“India is just like the US but bigger and cheaper.” Many hyperlocal and consumer apps imported Silicon Valley playbooks without accounting for lower ARPU, higher operational complexity, and different distribution realities (WhatsApp groups, kirana stores, cash-on-delivery). Stayzilla, several early grocery players, and others paid the price.
“Jugaad is a strategy.” Resourcefulness is valuable. Treating ad-hoc workarounds as a permanent operating system is not. Companies that scaled on jugaad hit coordination limits. The successful ones eventually built systems, Zerodha’s technology stack, Razorpay’s compliance infrastructure, while retaining the ability to move quickly.
Surfacing Models with AI
Founders can use AI to externalize mental models. Paste customer interview transcripts, support tickets, and sales notes into a model and ask: “What assumptions about the customer are embedded in our product decisions that the data does not support?” Or run red-team exercises: “Argue against our current strategy using only the evidence we already have.”
Razorpay’s response to RBI payment aggregator guidelines is instructive. Rather than treating regulation as an external threat to be minimized, the company built compliance capacity, formed an advisory board that included former RBI and SBI leaders, and treated the licensing process as a design constraint. The mental model shifted from “regulation slows us down” to “robust compliance is part of the product.” The result was not just survival but stronger positioning as regulatory requirements tightened across the sector.
Frequently asked questions
What are mental models in the context of startups?
Mental models are the frameworks through which organizations interpret and respond to the world, often remaining invisible until they cause problems.
Why is 'growth solves all problems' a fragile model for Indian startups?
This model fails when capital is scarce and interest rates rise, as it overlooks the importance of building learning systems around unit economics.
How can AI assist in challenging mental models?
AI can help founders externalize and test assumptions by analyzing customer data and running exercises to challenge current strategies.
What lesson can be learned from Razorpay's response to regulation?
Razorpay's approach shows that viewing compliance as a design constraint rather than a burden can strengthen a company's market position.