Chetan Puttagunta is a venture capital investor at Benchmark who specializes in enterprise and developer tools, having led early investments in companies like Elastic, MongoDB, and Modern Treasury while serving as an early champion of open source business models before they became mainstream. He moved from New Enterprise Associates to bring large-platform enterprise expertise into Benchmark's focused early-stage partnership model, and is recognized for his hands-on board leadership at scaled public companies like Elastic, where he serves as chairperson.

• Champions extreme velocity and execution speed in AI startups. He frequently highlights portfolio companies that break growth records, such as praising Manus for hitting $100M ARR rapidly or commending Legora for moving from seed funding to product launch in just a few months.
• A strong thesis on the value of the application layer in artificial intelligence. While acknowledging infrastructure, he expresses conviction that tremendous value will be created by AI apps, citing his firm’s early entry into companies like HeyGen, Cursor, and Mercor.
• Supports a multi-model future where developers leverage both proprietary and open-source systems. He views the competition between OpenAI, Anthropic, and Google as a major advantage for application builders and publicly welcomed the release of open models from labs like xAI.
• Advocates for international technical talent building on US infrastructure. He specifically highlights teams based in Singapore, such as the founders of Manus and Legora, noting their ability to build world-class products using American cloud and AI technologies.
• Takes pride in early-stage conviction, specifically at the Seed and Series A stages. He often emphasizes that his firm partnered with successful companies like LangChain and Duffel long before they achieved their current scale or unicorn valuations.
• Values software that replaces legacy workflows with AI-native solutions. He points to companies like Summation and Numeral that are replacing traditional financial software and solving complex tax problems through modern AI architectures.