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Recently, a16z General Partner Anish Acharya joined Ollie Forsyth on NEW ECONOMIES. They talked about why consumer tech is surging again, how AI is enabling 100M-user products at unprecedented speed, ...
Anish Acharya, a16z General Partner, discusses why consumer tech is experiencing a renaissance driven by AI, with unprecedented opportunities for founders. He reveals how AI is enabling products to reach 100M users faster than ever, explains why voice and AI-native software creation are transformative primitives, and shares tactical advice on fundraising, avoiding founder psychology traps, and building in the fastest product cycle tech has ever seen. Key insight: we're in the best time to build consumer startups in over a decade, with organic distribution replacing paid acquisition.
Acharya explains a16z's foundational philosophy that founders make the best long-term CEOs, which was controversial 15 years ago. The firm's entire structure—500 people organized into specialized teams—is designed to provide founders with the networks and knowledge they need to lead their companies forever, replicating the original small-team model across multiple specialized funds.
Discussion of why VCs need to provide 'power' beyond capital—including distribution, credibility, and brand presence. Acharya explains how startups can borrow their investor's platform to build credibility they don't yet have, and why a16z launched a media vertical to help founders with distribution at scale.
Acharya breaks down why AI represents the fastest product cycle ever seen in tech. Unlike mobile (which had 6M iPhones when App Store launched), ChatGPT's Apps SDK has 850M potential users. The key difference: no central designer controls what gets built—models have emergent properties that create wider innovation diffusion than previous platform shifts.
Acharya identifies common psychological traps that derail founders: feeling too late, believing VCs won't fund anyone, obsessing over competition. He shares his own experience in 2009 when TechCrunch declared 'the end of venture capital' and emphasizes the importance of first-principles thinking over noise.
Acharya's consistent mistake: underestimating market size in AI. He argues these aren't markets with single winners—they're entire industries. AI code will have 30-50 winners, AI legal will be as big as all legal tech. The mistake founders make is underestimating opportunity size and thinking they're too late when massive TAM remains.
Acharya challenges the narrative that AI is replacing jobs, arguing it automates tasks instead. Enterprise AI companies report full task automation but not role elimination. Example: Happy Robot's freight broker customers moved workers from low-level support to relationship management—AI handles minutiae, humans become more human.
Consumer tech is hyper-cyclical with long dead periods followed by explosive windows. We're in a magical moment driven by three factors: new technology (AI), new consumer behaviors (willingness to share data/pay), and emerging distribution channels (Apps SDK, mini apps, group chats coming in 2026). This mirrors post-iPhone era that created Uber, Airbnb, WhatsApp.
The most important consumer trend: everyday people creating software, not just consuming it. Just as YouTube transformed video from home cameras to $550B enterprise, software creation will follow. Wabi (like YouTube in 2006) enables personal software and mini apps. The ratio of 20M programmers to 6B software users will shift dramatically.
Consumer founders 2014-2023 spent days on marketing and customer acquisition. Today: no marketing problems, only product problems. Business model quality is high—consumers pay $200-300/month (Gemini Ultra $250, ChatGPT $200, Grok $300). New consumption revenue model means users can pay far beyond fixed subscriptions based on usage.
Three major distribution channels emerging for 2026: (1) ChatGPT Apps SDK with 850M users and app discovery, (2) Mini apps with Apple reducing take rate from 30% to 15%, (3) Group chat integrations starting in ChatGPT. These mirror Facebook APIs (2005-2006) and App Store (2009). Result: multiple consumer companies will hit 100M users in 2026.
Voice is not a market or primitive—it's an industry-level change. It's the insertion point for AI into enterprise because every business already does phone calls. Voice agents (outbound calls) working better than scribes (note-taking) at scale. Humans form emotional connections despite knowing it's AI, making voice effective for negotiation, persuasion, and relationship building.
Voice is primarily an enterprise story so far but expanding to consumer. Examples: Gmail for voice (responding to emails while running/driving), handling medical appointments, airline refunds. Voice becoming second interface to models after text. Enterprise will be redesigned around AI capabilities rather than human constraints—support and sales might merge into single agents.
Creators are digital entrepreneurs—'wanting to be a YouTuber' means wanting to be an entrepreneur. Previously limited to content creation, creators now have two new tools: software (via platforms like Wabi) and models (fine-tuned models on Civit). Software compounds value over time unlike content which plateaus. YouTube is a $550B enterprise showing creator potential.
Early films looked like stage plays until film developed its own grammar (method acting came later). AI content will follow similar path—not just 'AI movies' but entirely new formats. Microfilms (5-15 minutes) can be disposable at low cost. Creators can execute ambitious visions without Hollywood gatekeepers. All stories will finally be told.
Acharya doesn't worry about AI wrapper risk for three reasons: (1) Multi-model products (Cursor, Cria) can't be replicated by single-model labs, (2) Models aren't products—building full productivity suites is hard prioritization for OpenAI, (3) Fine-tuning with feedback creates defensible moats. Startups can be weird and ambitious in ways Big Tech promo committees won't allow.
Next social networks won't look like Instagram++. AI-native networks will focus on new status games: creating coolest software (Wabi) instead of coolest content. Media from last generation (photos, video) won't define next generation. We're at 2011 in mobile timeline—before Airbnb, Uber, WhatsApp scaled. New networks will emerge around software and model creation.
Why not raise all money on day zero? Because founders spread scarce talent across too many efforts when over-funded. Right amount of capital forces concentration and focus. Current magic: Lead with product, not marketing dollars. 2021's 'raise $100M to spend on Google/Facebook' is over. Raise for 24 months at best terms, but not so high it makes next round difficult.
When you need trust, it's too late to build it. Meet potential investors quarterly over a year before fundraising. When ready to raise, plan to get nothing else done for two weeks—full sprint. Lukewarm reception in first 2-3 meetings is critical signal. Torture investors for real talk—most useful thing they can do besides giving money is honest feedback.
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