Investors
2 Curated Dialogues
Anish Acharya
Frontier Insights
Frontier Thesis
AI captures enterprise value not at the foundational model layer, but at the application boundary—eating into massive labor budgets rather than zero-sum IT spend.
Strategic Playbook
- Monetization: Pivot from per-seat SaaS to outcome-based pricing, selling completed answers over tools.
- Beachheads: Target high-frequency, labor-heavy workflows (e.g., vertical B2B voice, after-hours call routing).
- Moats: Build defensibility through orchestration, deep workflow integration, client context, and proprietary outcome data as underlying models commoditize.
Risks & Warnings
Coding agents compress software switching costs; lasting advantage hinges on operational guardrails, evaluations, and enterprise trust amid regulatory friction.
Key Views & Dialogues
a16z, Anish Acharya: Is SaaS Dead? Do Margins Still Matter? Why We Are Not in an AI Bubble?
AI is exposing SaaS’s switching-cost moat, not eliminating software: coding agents make SAP-to-Oracle migrations cheaper, while 75% of public SaaS companies raised prices after ChatGPT. Apps that orchestrate specialized models may retain value, but Harry says Cursor could lose half its revenue this year to Claude Code; OpenAI’s $20B topline, fully spoken-for inference supply, and rising prices support the non-bubble case.
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- Software is oversold. Anish Acharya’s answer to the public-market “SaaSacre”: IT is only 8-12% of enterprise spend, so “you have this innovation bazooka with these models — why would you point it at rebuilding payroll or ERP or CRM?” 75% of public SaaS companies have raised prices since ChatGPT (mean 8-12%, a large group at 25%+), and “price is a measure of product market fit.” The vibe-code-everything story is “flat wrong.”
- Coding agents’ real effect on enterprise software is that switching costs collapse — “some companies have hostages, not customers” (Alex Rampell), and the SAP-to-Oracle migration that used to be a multiyear, high-risk project that would probably fail and get you fired gets dramatically easier. Fewer hostages, more customers — a positive incentive for the ecosystem, not a death sentence.
- The apps layer aggregates the models: foundation models innovate “roughly in lockstep,” 80% substitutes / 20% specialists, so orchestration (Cursor across Gemini front-end and Codex back-end; creatives across Midjourney/Krea vs Ideogram) is where much of the value is — a cloud-style oligopoly, not Uber-vs-Lyft. Harry’s pushback: “there’s a chance Cursor loses half of their revenue this year” to likely Claude Code; Anish’s reply — demand isn’t fixed: “our ability to be ambitious… always grows so much faster than our means.”
- Not a bubble: OpenAI hit $20B topline by 3x-ing capacity and 3x-ing revenue — inference supply is “100% spoken for” — and customer prices are rising, not compressing. Today’s subsidy (free-trial credits) is “healthy calories” converting into power users who pay $200-300/month (likely Grok Heavy $300, ChatGPT $200, Gemini Ultra $250) versus the old $20-25 Spotify ceiling.
- The SaaS-to-labor-budget shift is already underway: voice is “the wedge into the enterprise,” and the 10x is bundling support, sales, collections, and operations under one goal like CAC improvement. Legal software is $50B; after Anish calls legal “$500 million” infrastructure for capitalism, Harry calls it a “$500 billion market” — AI’s capture lands “closer to the 500 than the 50.”
- Weird wins: these models are emotional, human technology, and Google/Apple have “a thousand committees explicitly designed to ensure there’s never any persuasion, disagreement, or sexuality” — leaving companionship and other uncomfortable categories to startups. Traditional moats otherwise hold: networks are still “the gold standard,” and live proprietary data (likely OpenEvidence) beats a frontier model without it.
- The a16z operating bar, stated flat: “I’ve never lost a deal” in six and a half years — “we’re not allowed to believe in luck… we have to see 100% of the deals in our domain and win 100% of the deals we go after.” Elastic on price (sub-$100M entry “is a little bit of a wash”), never on ownership.
- The 2026 call: unlike mobile, where the Friendsters lost to later Facebooks, the 2023-24 early leaders (Harvey, Gamma) have kept their lead — and 2026 brings new AI-native categories, with Open Claw and Moltbook “just the beginning.” Moltbook “as an individual data point is probably overhyped right now, but what it points at directionally is underhyped.”
The Top 100 GenAI Products, Ranked and Explained
The GenAI leaderboard remains volatile at the edge but durable at the center, with 16 products appearing in all four editions and 17 new web entrants in January 2025. ChatGPT’s weekly users doubled from 200 million to 400 million in six months as new capabilities expanded recurring jobs, while DeepSeek reached 10% of ChatGPT’s web scale in 10 days; retention, monetization, and product-first differentiation remain key tests.
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- The GenAI leaderboard is unstable at the edge but increasingly durable at the center. January 2025 Similarweb visits and Sensor Tower monthly active users produced 17 new web entrants, while 16 web products have appeared in all four editions. For investors, products can still “rewrite the leaderboard overnight,” yet repeated rankings show that lasting consumer brands and businesses already exist.
- Smith notes that consumer activity typically lags research by “six to nine to 12 months,” while Acharya still places many consumer-AI categories in the early-adopter phase. Current video systems make strong 3-, 5-, or 6-second clips, not complete movies, and consumer voice, browser-agent, and screen-aware products remain relatively underdeveloped at the application layer. Acharya’s deeper call is that intuitive assumptions may invert: AIs might prove “more human than humans,” or organize and delegate work to people rather than merely receive it.
- DeepSeek showed that another horizontal assistant can still acquire mass distribution almost instantly. Free reasoning at scale and a visible thought process helped it reach No. 2 on web—about 10% of ChatGPT’s scale—with only 10 January days, and No. 14 on mobile with five days; Moore said five more days would have put it at No. 2 there. Day-30 retention was 7% versus ChatGPT’s 9%, though markets where the choice is “DeepSeek versus nothing” may skew the comparison.
- ChatGPT’s growth reaccelerated as new models turned occasional experimentation into multiple recurring jobs. Web visits were essentially flat from February 2023 through February 2024, when data Moore had seen suggested students supplied 50%+ of traffic; visits have since doubled. ChatGPT’s own announcement reported weekly active users rising from 200 million to 400 million in six months—after the previous doubling took nine—as o1, GPT-4o, Advanced Voice Mode, Deep Research, Operator, and Canvas expanded utility.
- Companion products are already significant, with multimodality still underexplored. Smith noted that three companion products were in the top 10, two NSFW-oriented, and that some users treat them as interactive fan fiction. Acharya said latent demand could grow substantially once products add richer multimodality and voice.
- AI video is becoming a modular production stack rather than a winner-take-all model market. The ranking added Hailuo and Kling, both Chinese models, plus Sora. Google’s Veo 2 looked “next-level” in testing and was hoped for within three or six months. Different models excel at people, landscapes, anime, or hyperrealism, supporting aggregators such as Krea that reduce workflow seams and could consolidate 10 or 15 separate $20-a-month subscriptions.
- Vibe coding is exposing enormous creation demand before it has produced its first wave of viral downstream apps. Cursor and Bolt reached the main ranking, Lovable reached the Brink list, and Moore cited Gary Tan as saying “95% of YC companies or something” now build with such tools. Lovable’s creation site draws significantly more traffic than hosted creations, validating “personal software” and “disposable software”—and foreshadowing an App Store that “is going to be chaos.”
- Usage and monetization describe materially different consumer-AI markets. Only 40% of Sensor Tower’s mobile revenue and monthly-active-user rankings overlapped; tightly gated prosumer products can reportedly generate $50 million to $100 million of ARR from only one million or two million users. Paid acquisition can manufacture 10 million users at one-to-two-times payback, but the panel’s durable rule is product-first: without attention and retention, growth remains a “leaky bucket.”