Navin Chaddha

Venture Capitalist at Mayfield focused on the AI sector.

Claims

As speaker

Mentioned in

Key positions and views

The current AI wave is a '100x' supercycle, fundamentally larger and more impactful than previous tech shifts like web, mobile, and cloud.

The economics of software are being inverted by AI, shifting from high-margin SaaS to low-margin, consumption-based models due to the high and persistent cost of inference.

Despite the massive long-term opportunity, the current market is in a dangerous valuation bubble, with incomprehensible seed rounds and a high probability of failure for the vast majority of hyped companies.

Venture capital is rapidly consolidating around AI-native companies, to the point where non-AI companies will soon be effectively locked out of funding.

The most immediate and sustainable hyper-growth is in the AI infrastructure layer (hardware, models), with AI coding assistants being a rare example of a successful 'killer app' so far.

Podcast consensus on Chaddha

Points of consensus

▶Navin Chaddha consistently frames the current AI era as a '100x' market opportunity, significantly larger than previous technology waves like web, mobile, and cloud, predicting it will create numerous companies valued over $100 billion.Apr 2026

▶He repeatedly emphasizes a fundamental shift in software business models, moving away from high-margin, per-user SaaS subscriptions towards lower-margin, consumption-based or outcome-based pricing driven by high AI inference costs.Apr 2026

▶Chaddha consistently points to the AI infrastructure layer—including hardware, optical interconnects, and foundation models—as the current locus of value and hyper-growth, while applications struggle with profitability.Apr 2026

▶Across his analysis, he highlights a dramatic bifurcation in the venture capital market, where AI-native companies receive the vast majority of funding, while non-AI companies will soon face extreme difficulty in raising capital.Apr 2026

Points of debate

▶Chaddha expresses a significant tension between his long-term bullishness on AI's $3-6 trillion potential and his short-term bearishness on the market, citing incomprehensible valuations, inflated founder expectations, and predicting only 1-3% of hyped companies will succeed.Apr 2026

▶He champions the transformative power of AI to create millions of new entrepreneurs and programmers, yet simultaneously points out that the application layer, where these new creators would operate, currently suffers from unsustainable economics and negative gross margins.

▶Chaddha highlights the extraordinary revenue growth of select portfolio companies (e.g., $0 to $3B in 14 months) as proof of the AI supercycle, yet also warns that 95% of enterprise AI projects fail, suggesting a conflict between top-line infrastructure spend and real-world value creation.Apr 2026

▶He forecasts that value will eventually move 'up the stack' to AI applications, but his current market analysis states that only infrastructure and a few niche apps like coding assistants are experiencing hyper-growth, leaving the path for broader application success unclear.Apr 2026

Key themes

▶The AI Supercycle ThesisApr 2026

Chaddha posits that AI represents a '100x' market opportunity, an order of magnitude greater than prior tech waves. He quantifies this as a $3 to $6 trillion market created by automating 10-20% of the $30 trillion spent on knowledge workers, which will spawn multiple $100 billion companies.

Investors should view the AI market not as an incremental change but as a fundamental economic shift, justifying investment in core infrastructure despite high valuations, as this is where the initial value of the supercycle is being captured.

▶The New Economics of AI SoftwareApr 2026

Chaddha details the inversion of the traditional SaaS model. Due to high inference costs and dependency on third-party models, AI application companies, particularly coding assistants, operate on razor-thin or negative gross margins (15-20%) compared to the 70-90% margins of the past. This necessitates a shift to consumption or outcome-based pricing.

Analysts must re-evaluate software companies using new metrics; traditional SaaS benchmarks for profitability and gross margin are irrelevant for most AI application companies, and long-term viability will depend on driving down inference costs or demonstrating immense, outcome-based value.

▶Venture Capital Market BifurcationApr 2026

Chaddha observes a dramatic consolidation of venture capital, with 67% of funds already flowing to AI companies and a prediction it will hit 90% within a year. He forecasts that non-AI native companies will soon find it 10 times harder to raise capital, effectively starving them of oxygen.

The concentration of capital creates a high-stakes environment where startups must be 'AI-native' to be considered viable, potentially stifling innovation in non-AI sectors and creating a feedback loop that further inflates the AI bubble.

▶Valuation Hype vs. RealityApr 2026

While bullish on the long-term, Chaddha is deeply concerned about the current market froth. He finds billion-dollar seed rounds 'incomprehensible,' notes founders are disappointed by $300 million valuations, and predicts that only 1-3% of the currently hyped AI companies will survive and sustain their valuations.

This perspective suggests a major market correction is inevitable. Prudent investors should be highly selective, focusing on companies with defensible technology and a clear path to positive unit economics, rather than chasing momentum in a market Chaddha believes is largely unsustainable.

Source episodes

Timeline

Pre-AI Era

Chaddha characterizes this period by the dominance of the SaaS model with high gross margins (70-90%) and per-user-per-month pricing.

Current Period

Describes the market as being in a transitional supercycle. 67% of VC dollars are flowing into AI, but the application layer suffers from low margins due to high inference costs, while infrastructure and foundation models see hyper-growth. A valuation bubble is forming, with 'incomprehensible' seed rounds.

Next 1 Year

Predicts an acceleration of capital concentration, with 90% of all VC investment flowing to AI companies. Non-AI native companies will find it 10 times more difficult to secure funding.

Next 5-7 Years

Forecasts the materialization of a $3 to $6 trillion market as AI addresses a significant portion of knowledge worker tasks. He expects value to begin migrating up the stack from infrastructure to intelligent applications.

Next 15-20 Years

Believes Artificial General Intelligence (AGI) is likely to emerge within this timeframe, representing the culmination of the current AI wave.

Suggested prompts

How does Navin Chaddha reconcile his prediction of a '100x opportunity' with his observation that 95% of enterprise AI projects fail and most AI app companies have negative margins? &nearr;What specific market signals would validate Chaddha's prediction that value will shift from AI infrastructure to 'AI teammates and intelligent applications'? &nearr;Given Chaddha's concern about billion-dollar seed rounds, what alternative funding or valuation models does he imply would be healthier for the AI ecosystem? &nearr;Chaddha predicts a massive expansion of programmers and entrepreneurs due to AI tools; what are the potential second-order effects on labor markets and economic inequality that his analysis does not address? &nearr;

Key concepts

AI Market Opportunity 3 ep Venture Capital Strategy 4 ep AI Company Valuations 3 ep AI Business Models 3 ep AI Infrastructure 4 ep Revenue Growth Expectations 1 ep Future of Work 2 ep Artificial General Intelligence (AGI) 1 ep Enterprise AI Adoption 1 ep

Notable quotes

“And then the AI, I think those eras were a 10x opportunity. This is a 100x opportunity.”

Navin Chaddha · AI Valuations & the Supercycle | Navin Chaddha, Mayfield

“The spend on knowledge workers globally is 30 trillion. And AI will do 10 to 20% of that. It's a three to six trillion dollar opportunity over the next five to seven years.”

Navin Chaddha · AI Valuations & the Supercycle | Navin Chaddha, Mayfield

“SaaS companies have 70, 80, 90% gross margin. But a lot of these coding companies, they have either negative margins... or 15, 20% gross margin.”

Navin Chaddha · AI Valuations & the Supercycle | Navin Chaddha, Mayfield

“I think now it's one, 10, 50. for even the normal companies, the equivalent of SaaS, that's expected of you.”

Navin Chaddha · AI Valuations & the Supercycle | Navin Chaddha, Mayfield

Report last updated: Apr 21, 2026

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