
Abhay Parasnis on Creating Moats, AI Strategy, and Selling to Enterprise
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Takeaways:
- If you can break into the top tier of the enterprise market, it’s hard to dislodge you.
- Big platforms like Microsoft, Google, and OpenAI are eager to prove their tech's power. If you position your startup as a prime showcase for their platform, you become a strategic asset.
- When selling to enterprise, understand the company's macro strategy in the market, but also know what the on-the-ground person needs to close deals.
- With the rise of agents and agentic automation, even the workflow layer isn’t safe. As these systems gain richer context, they’ll redefine automation in SaaS. Just like today’s platform vs. app debate, tomorrow’s battle will be legacy workflows vs. agents.
- Success in AI isn’t just about top-tier products—it’s about being a consultative partner to help them with change management.
- There’s a common fear about embracing a custom data training strategy — it’s expensive, complex, and feels like the domain of big players. But starting narrow and accumulating distinct data early is key. It drives real AI differentiation and builds critical internal muscle in engineering and product.
- Value-based pricing means customers are less price-sensitive because it ties directly to their top-line business, unlike commodity pricing, which faces constant cost pressure. Instead of charging per word, image, or seat—models that AI disrupts—pricing should align with outcomes, ensuring long-term sustainability.
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