When to open: You want to know how a16z / Sequoia / YC have recently viewed AI / what they have invested in / valuation multiples from a primary VC perspective / how to find PMF. This wiki categorizes 362 financing-keyword-containing posts from Shensi Circle by VC firm.
One-sentence core:Marc Andreessen / Ben Horowitz: "In supply-driven markets, demand is created by supply." + Jason Rosenthal: "More funding cannot save a company without PMF; there are only three paths." + Sequoia Terrifying Questions Framework: 4 questions + YC is betting heavily on Agents + coding + data analytics.
0. Differences among the three VCs' perspectives
| Firm | Frequency of appearance in Shensi Circle | Investment style | Representative views |
|---|---|---|---|
| a16z | 49 posts | High-conviction / long-term / big-thesis | Supply-driven markets / 10x judgment / the fourth revolution of software |
| Sequoia(US/India/China) | 20 posts | Data-driven / starting from incubators | PMF Terrifying Questions / sales Agents / India track |
| YC | 16 posts | Early-stage / trend-sensitive | Agent Economy / Vibe Coding / early unicorn path |
1. Core views of the a16z school (refined from 49 posts)
1.1 Supply-driven market — latest as of 2026-01
Shensi Circle / AI Primary Market VC Perspective (a16z + Sequoia + YC) source:weixin/2026-01/a16z开年观点-供给侧跃迁
Marc Andreessen's original words:
"If there is a fundamental breakthrough on the supply side,market size analysis becomes invalid.". "
"We invested in Substack because we deeply believe this is a supply-driven market. In an era where the internet is flooded with free content, the question seemed to be 'Will people really pay for content?' But we saw the other side:if you can provide creators with the ability to monetize, you will create authors and content that do not exist today,and that will give rise to new demand that is currently invisible."
"Just as no one asked for the Macintosh or the iPhone, demand does not appear until the product is provided on the supply side."
Extension to the AI era: not optimizing existing demand, but creating unprecedented supply → 10x / 100x / 1000x opportunities.
1.2 Ben Horowitz's "10x judgment" — Databricks case
Ben's email to Databricks founder Ali: "You are underestimating your business; it will be 10 times bigger than Oracle."
Judgment mechanism:
- Not looking at existing market share
- Looking at new demand that the supply side can create
1.3 Three paths to PMF (Jason Rosenthal 2026-05)
Shensi Circle / AI Primary Market VC Perspective (a16z + Sequoia + YC) source:weixin/2026-05/a16z合伙人的一个判断-PMF三条路
"More money only prolongs a bad ending."
"PMF is not funding amount, not TVL, not Twitter follower count, not airdrop participation numbers.PMF is just one thing: whether what you build is being continuously used by a group of real users.""
Three paths(universal for crypto + AI):
| Path | Applicable to | Key point |
|---|---|---|
| 1. Build together with top-tier customers | Enterprise-level / high-compliance | Find the most demanding customers / customer needs = your spec |
| 2. Stand in front of the exponential curve | New infrastructure / new protocols | Bet on the next wave of technology dividends, such as stablecoins + traditional finance |
| 3. Be your own first customer | Engineering-oriented products | Dogfooding / Cursor / Anthropic internal use |
1.4 Other classic a16z theses
| Thesis | Source |
|---|---|
| "The next generation of software will eat the 13-trillion-US-dollar labor market" | Latest share by a16z partner |
| "The fourth revolution in software development, when AI becomes a new pillar of infrastructure" | a16z roundtable insights |
| "Computer Use lets AI Agents work like humans, and their efficiency will surpass humans within 18 months" | a16z prediction |
| "AI video is eating the world, building a multi-billion-dollar IP empire of the future" | a16z partner analysis |
| "Moats are never in the UI / interface" | Salesforce cutting UI / a16z partner |
| "Gen Z is the AI-native generation; I am willing to spend 100% of my time on them" | a16z opening-year view |
1.5 Key a16z investment tags (reverse-inferred from titles)
- AI images: Ideogram (led $80 million Series A)
- AI testing: Distributional (led $11 million seed round)
- Open-source model infrastructure: Replicate ($80 million / "use open-source models like using electricity")
- Agent-era infrastructure: New company by former GitHub founder ($17 million / "Git for the Agent era")
- AI photography: Chinese team ($5.6 million / exclusive photographer)
- AI tutor: $16 million ("unexpected answers")
- AI marketing automation: Berkeley Chinese dropout ($28 million)
2. Core views of the Sequoia school (20 posts)
2.1 Sequoia US Arc incubator Terrifying Questions Framework (2025-04)
Shensi Circle / AI Primary Market VC Perspective (a16z + Sequoia + YC) source:weixin/2025-04/来自红杉美国孵化器的内部分享-PMF四问
4 "Terrifying Questions":
| # | Question | Positive signal |
|---|---|---|
| 1 | What right does my company have to exist? | Founder-market fit / willing to commit 10 years / willing to hire close friends |
| 2 | Do people really care enough? | Cold start > relationship customers / customers' eyes light up / proactively participate in demos |
| 3 | Can my product really change behavior? | "Lightbulb moment" / get started in a short time / sticky feature points emerge |
| 4 | (Original text continues... see original document for the 4th question) | (Deep self-interrogation) |
Classic cases:
- Nubank David Vélez: Months of research on Brazilian banking → locked in credit cards as the entry point (Question 1)
- DoorDash founders: Deep conversations with hundreds of small restaurants → locked in local restaurants that "reject orders but cannot afford delivery" (Question 2)
2.2 Sequoia US Agent bets
| Target | Amount | Track |
|---|---|---|
| AI-native ERP(Disrupting traditional financial software) | $25 million | Sequoia US |
| A vertical Agent scenario | $27 million | Sequoia US |
| AI sales products(Full inventory) | Multiple rounds | Sequoia bet |
| AI legal rebuilding law firms(Not selling tools) | Large amount | Sequoia US |
2.3 Sequoia India
- Market research company: $9 million ("making the hundred-billion-dollar market research industry instantly efficient")
2.4 Sequoia US 2026 annual share
"AGI has arrived, redefining the AI revolution" — 2026 Sequoia US annual share
3. Core views of the YC school (16 posts)
3.1 Latest YC conversation:The Agent Economy is really coming
(2025-? YC partner conversation)
3.2 The two tracks YC most wants to invest in this year
- Are both "hit" by the same open-source project
- See original document for details / involves Agent + Coding
3.3 YC W24 / W25 trends
- "Comeback unicorn": 25 years old, rejected by YC twice → $1 billion valuation / "truly landing AI for small merchants"
- "Builders exclusive interview: 18-year-old dropout entrepreneur, product entered a16z global AI product traffic Top 20"
- "Got into YC on first startup, now cross-building an AI education version of Stanford Smallville"
3.4 YC partner's 15 secrets of Vibe Coding
(Title:YC Partner's In-Depth Practice: 15 Secrets to Master Vibe Coding)
Vibe Coding and independent development (cross-author topic synthesis) See the integrated version for details.
3.5 Typical YC-incubated companies (covered by Shensi Circle)
- Shimmer($2.2 million / mental health)
- AI tax company that raised $53 million in 6 months(Benchmark + YC)
- Clinical drug development AI partner(YC incubator)
- AI Agent that registers email accounts on its own($6 million / only does one thing)
- Enterprise-grade Text2SQL(YC led / currently the best)
- Cloud video editing founded by MIT dropout($7 million led by YC)
4. Primary market valuation multiples / financing market conditions
4.1 High-frequency valuation data points (extracted from 660 posts)
| Company category | Typical data |
|---|---|
| Cursor | $50 billion valuation (2026-03) |
| Anthropic | Valuation doubled in three months / surpassed OpenAI / old shareholders waiting for IPO to cash out |
| Perplexity | $450 million ARR (in three and a half years, from being poured cold water on by early investors to) |
| Lovable | Reached $50 million ARR in 6 months |
| Readdy.ai(Chinese founder) | Nearly $5 million ARR within 4 months of launch |
| AI legal unicorn | 25-year-old esports player / nearly $700 million |
| AI sales unicorn | $52 million in 2 rounds over 9 months |
| Chinese AI customer service company | Raised $200 million, valued at $1.5 billion |
| AI insurance company(Pays for Agent mistakes) | $15 million |
| Imbue Agent company | $1 billion valuation / $200 million financing |
4.2 Financing rhythm judgment
- Seed round: $2–20 million / achieved in 3–9 months
- Series A: $11–50 million / largest single round $80 million
- Series B: $20–24 million / some up to $100 million
- 2026 trend: Agent companies raising continuously over 6 months + multiple investors entering in the same period
4.3 "King-making strategy" model
| Item | Explanation |
|---|---|
| VCs concentrate heavy bets | Valuation doubles in 27–60 days (OpenAI / Anthropic) |
| Chief PR | "AI companies don't lack capital; they lack attention." |
| Linkloud Global NEXT 2026 | Overseas expansion / AI globalization pioneer gatherings |
5. Cross-author intersections
| Topic | This Shensi Circle wiki | Sister wikis |
|---|---|---|
| Overall VC perspective | This wiki (primary market) | AI Investment and Valuation (cross-author topic synthesis)(Comprehensive) / Wang Kai RSI AI Investment Strategy and "Good Asset, Good Price, Good Volatility" Framework(Secondary market) |
| PMF / three paths | a16z Jason | Entrepreneurship Methodology (0 to 1) (cross-author topic synthesis) / Yitang / Five-Step Method Complete System (key assumptions + business milestones + 5 progressions of the five-step method + implementation) |
| Agent Economy | YC conversations | AI Agent Architecture and Multi-Agent Orchestration (cross-author topic synthesis) / AI Agent Market Investment Trends 2025 (data report) |
| King-making strategy | a16z + Anthropic cases | AI Agent Market Investment Trends 2025 (data report) / Wang Kai's AI Industry Judgments and Big-Company Competition Landscape Observations |
6. How to use — VC perspective paths by identity
| Who you are | Main use | Starting point |
|---|---|---|
| Entrepreneurs seeking financing | Sequoia PMF 4 questions + a16z three paths to PMF | Founder-market fit / Lightbulb moment / dogfood |
| To understand the primary market | a16z supply-driven + 10x judgment | Substack case / Marc Andreessen's original words |
| Bet on new tracks | YC's 2 major tracks + Sequoia sales Agent | Agent Economy / B2B vertical |
| AI company valuation reference | Section 4 financing market conditions + valuation data points | Cursor $50 billion / Lovable $50 million ARR in 6 months |
| Differences in VC perspectives | Section 0 comparison of the three firms | a16z big thesis / Sequoia data / YC instinct |
General discipline:
- When supply-side breakthroughs occur, market size analysis becomes invalid(Marc Andreessen)
- More funding cannot save a company without PMF(Jason Rosenthal)
- PMF = a group of real users continuously using the product(Not TVL / follower count / financing amount)
- Differences in VC perspectives: a16z emphasizes thesis / Sequoia emphasizes data / YC emphasizes instinct
- 2026 valuation multiples: Top AI companies at 25x revenue, some at 100x+
7. Reference list
- Shensi Circle author complete works entry — Complete works entry
- Main sources:
sources/learning/深思圈/weixin/2024-2026/~362 articles containing "a16z" / "Sequoia" / "YC" / "financing" / "US dollars" / "USD" / "valuation" - AI Investment and Valuation (cross-author topic synthesis) —— Synthesized VC perspectives (already merged into this wiki)
- Wang Kai RSI AI Investment Strategy and the "Good Asset, Good Price, Good Volatility" Framework —— Wang Kai's secondary market RSI perspective (this wiki is a primary market supplement)
- AI Agent Market Investment Trends 2025 (data report) —— Data on 191 unicorns / king-making strategies
Sources and related materials
- https://mp.weixin.qq.com/s?__biz=MzAxNjE1NTg2Ng==&mid=2247492593&idx=1&sn=fc40e30ef94ded4ed58c17b551a63fb2&chksm=9bfbb644ac8c3f526e0459b12301462eb3084e4f35537c714a512278ad09e82a391797a178a7
- https://mp.weixin.qq.com/s?__biz=MzAxNjE1NTg2Ng==&mid=2247494161&idx=1&sn=48729c7f395aada3d7bd0b3974137b0b&chksm=9bfbbfa4ac8c36b25a403d81d9287866e3c2cd354878aacefa733527d01e289886a4f81feed9
- https://mp.weixin.qq.com/s?__biz=Mzg3NDc2MjQxMg==&mid=2247487073&idx=1&sn=b64487717d7ef101eef7190eaff2657b&chksm=ceca97a2f9bd1eb4daa32faa297ff161d18cf413261fab01dadd82008fd2afcca68062371108
- Shensi Circle author complete works entry
- Shensi Circle / AI Agent Company Case Library
- Shensi Circle / AI Startup 0-1 Cases + Growth Playbooks
- Shensi Circle / AI Industry Trends + New Categories + Forecasts
- AI Investment and Valuation (cross-author topic synthesis)
- Startup Methodology (0 to 1) (cross-author topic synthesis)
- Wang Kai RSI AI Investment Strategy and the "Good Asset, Good Price, Good Volatility" Framework