Y-Combinator’s new batch doubles down on production-ready AI, Unconventional tactics for validating your startup ideas & Measuring true efficiency in Venture exits.
Fundraising size impacts your startup’s unicorn odds & What founders should really know about compensation?
👋 Hey, Sahil here — Welcome back to Venture Curator, where we explore how top investors think, how real founders build, and the strategies shaping tomorrow’s companies.
Big idea + report of the week :
Paid AI adoption hits its first slowdown, but enterprise spending keeps climbing.
Y-Combinator’s 2025 Summer batch doubles down on production-ready AI.
Why early-stage VC returns are quietly collapsing.
Frameworks & insightful posts :
What early-stage founders should really know about compensation?
How fundraising size impacts your startup’s unicorn odds.
Unconventional tactics for validating your startup ideas - from founders of Linear, Mercury and More.
Measuring true efficiency in Venture exits (RBCx’s exit velocity index)
FROM OUR PARTNER - SEMRUSH
🤝 See your competitors’ traffic secrets in real time
Want to know where your competitors’ traffic really comes from?
With Semrush’s Traffic & Market Toolkit, you can track daily and weekly site visits, uncover top-performing pages, and see which channels—search, social, or even AI assistants—are driving growth.
Benchmark against industry leaders, spot gaps in your own strategy, and react quickly with real-time data.
Trusted by 10M+ marketers, it’s the easiest way to turn competitive intelligence into more traffic and smarter decisions.
Try the Traffic & Market Toolkit free →
🤝 PARTNERSHIP WITH US
Get your product in front of over 95,000+ audience - Our newsletter is read by thousands of tech professionals, founders, investors and managers worldwide. Get in touch today.
START WITH
🧠 Big idea + report of the week
Paid AI adoption hits its first slowdown, but enterprise spending keeps climbing.
Ramp’s latest AI Index reveals that U.S. companies are entering a new phase of the AI curve, one where adoption is stabilising, but spending is intensifying.
After nearly two years of explosive growth, paid AI adoption dipped 0.7% in September, marking the second decline this year. But beneath that headline, the story is less about retreat and more about market maturity.
Here’s what’s happening:
Adoption plateaus in tech and finance. About 73% of tech firms and 58% of finance companies now pay for AI tools, but growth has slowed as most early adopters consolidate spend and refine ROI.
Retention is rising fast. Annualized retention for AI tools has climbed from <50% in 2022 to ~60% in 2023, and is forecasted to hit 80%+ in 2025. Companies are sticking around longer once they integrate AI into workflows.
Enterprise spending explodes. The average contract value jumped from $143K in 2024 to $530K in 2025, with projections near $1M in 2026. Businesses may be buying fewer new tools, but they’re spending far more per vendor.
OpenAI continues to dominate (35.6% of paid adoption), while Anthropic trails at 12.2%, and smaller players like xAI, Google, and DeepSeek are still in the single digits.
AI adoption is entering its scaling era. Companies have picked their tools, now they’re integrating them deeply, standardising workflows, and spending big to scale use cases.
Y-Combinator’s 2025 Summer batch doubles down on production-ready AI.
CB Insights’ latest breakdown of Y Combinator’s Summer 2025 batch reveals a clear shift: AI is no longer experimental, it’s enterprise-ready. The 165+ startups funded this season mark YC’s most practical, infrastructure-heavy cohort yet.
Voice AI enters regulated industries. 16 startups are targeting complex, compliance-heavy sectors like finance and insurance (Altur, Veritus Agent, Qualify.bot, Wayline). Others, like Liva AI and Panels, are building proprietary training datasets, a moat that general-purpose models can’t match.
Software development agents dominate. With 20 dev-focused startups, YC continues its bet on AI engineering tools. Companies like Stagewise (frontend agents) and Interfere (autonomous debugging) go beyond Copilot-style assistance, tackling full lifecycle automation, including testing and hardware integration.
The agent stack is maturing fast. Nearly 50% of the batch builds AI agents, and 14 focus on agent infrastructure, evaluation (AgentHub), debugging (Fulcrum Research), and monitoring (Mohi). Others like Nozomio Labs and Imprezia are building new layers for context and monetisation.
Efficiency replaces capability as the next frontier. Startups like Stellon Labs (tiny frontier models), Herdora (low-latency inference), and DeepAware AI (data centre energy optimisation) reflect a market shift toward scaling AI affordably latency, cost, and sustainability now define adoption barriers.
For founders, this batch signals a turning point: the AI story has moved from demos to deployment. YC’s next generation isn’t chasing hype, they’re building the infrastructure and vertical tools enterprises will soon depend on.
Why early-stage VC returns are quietly collapsing.
PitchBook’s latest note by Kyle Stanford, Director of US Venture Research, highlights how today’s market dynamics are tightening returns for early-stage investors from both sides, larger seed rounds and longer exit timelines.
Seed rounds are bigger and ownership is shrinking. Rising round sizes have reduced seed investors’ average stake, making it harder to build diversified portfolios or maintain meaningful ownership in breakout companies.
More startups, but thinner slices. First-time financings in 2025 are pacing 16% ahead of 2023, but investors’ share of equity in eventual $500M+ exits has fallen from 68% in 2015 to 55% in 2025.
Companies are staying private longer. The median time from first VC check to IPO is now 11.5 years, up from 7.4 years a decade ago, creating liquidity pressure across the venture stack.
Secondaries offer relief, but at a cost. Selling early in secondary markets helps recycle capital but limits the upside LPs expect from long-duration VC bets.
800+ US unicorns and counting. The growing backlog of billion-dollar private companies is delaying exits and compounding the liquidity bottleneck.
As valuations stretch and holding periods lengthen, seed investors face a return compression era, forced to balance liquidity needs against ownership dilution. The traditional “spray and pray” seed model may soon need rethinking.
TOOL FOR FOUNDERS
📑 Startup Legal Pack: VC-Ready Docs in One Place
Messy or missing legal docs slow founders down and turn off investors.
The Startup Legal Document Pack gives you everything you need to incorporate, protect equity, and raise confidently.
What’s inside:
Incorporation docs & founder agreements
SAFE notes, term sheets, cap tables
Employment, IP, and advisor agreements
NDAs, privacy policies & customer contracts
Built with startup attorneys and VC teams. Investor-ready. Easy to use.
SOMETHING MORE
🧩 Frameworks & insightful posts
What early-stage founders should really know about compensation?
Compensation advice is everywhere and most of it doesn’t apply to a five-person startup trying to make its first few hires.
Early-stage founders often overthink the rules. They benchmark against Google, overpay to win talent, or give away too much equity too soon. But as leaders from Clay, Instacart, Google, Applied Intuition, and Confluent shared, early-stage comp is less about formulas and more about philosophy.
Here’s what rules you can break, and which ones are worth keeping by Firstround.
Rules to break
1. “Give big equity to land talent.”
Don’t. Early equity is far more expensive than it looks. Kaitlyn Knopp (Pequity, ex-Instacart) says your first 10 hires should get a combined max of 10% of the total pool. Even 1% each can be aggressive.
Too many startups burn through their option pool early, then have to take equity from founders or investors to fix it later. Her advice: “Outline your comp philosophy and stick to it. You have more leverage than you think.”
Also, teach candidates what equity actually means. At Facebook, Molly Graham created a simple “Understanding Your Equity” guide to help candidates grasp future value. Transparency turns fear into trust.
2. “Pay top-of-market to attract talent.”
Qasar Younis (Applied Intuition) warns against inflating salaries just because you can.
“Founders are overpaying because they’ve raised large rounds. But high salaries at the start destroy incentives and make the business unsustainable.”
The startup playbook still holds: lower cash, higher equity, and wealth through company growth. At Applied, employees are now in the 99th percentile of comp not because of high initial salaries, but because their stock grew.
3. “Wait for review season to adjust pay.”
Varun Anand (Clay) says that’s outdated. “We don’t wait for review cycles. If someone outperforms, we raise them right away.”
Clay’s approach: reward in real time. It builds loyalty, keeps top performers motivated, and avoids resentment. The key: justify every raise with data and measurable results, not emotion.
4. “Copy what big tech does.”
Google-style pay formulas and equity bands don’t fit a seed-stage company. Knopp says: “Most founders over-engineer early comp.
Build your own system based on your stage and philosophy. Read about psychology and reward behaviour before copying anyone’s spreadsheet.”
Rules to follow
1. Define your compensation philosophy early.
Even at 10–15 employees, clarity avoids chaos later. Ask:
How do our values show up in comp?
What’s our equity vs. cash ratio?
How transparent will we be?
How do we reward top performers?
Introduce salary tiers early, too. Four levels are enough:
Junior (0–3 years)
Mid-level (4–7 years)
Senior (8–12 years)
Principal/Leader (10–15+ years)
Benchmark roles against data sources like Radford or Mercer, then decide which percentile (e.g., 50th, 75th) you’ll target.
As Instacart’s Udi Nir put it: “You won’t always have the highest offer, but the best role and mission often win.”
2. Use contract-to-hire to test fit.
Knopp says early-stage startups can’t afford bad hires or full salaries. “Some of our best engineers started as 10-hour-a-week contractors,” she says. “It let us test fit, build trust, and manage cash.”
Top talent today isn’t afraid of contract work; it’s a smart way to test mutual value before committing.
3. Be transparent. Always.
Colleen McCreary (Confluent, ex-Credit Karma) calls comp opacity a founder’s biggest time drain. “When no one understands how they’re paid, you’ll spend all your time talking about pay.”
At Credit Karma, she walked the entire company through the comp model, what benchmarks they used, what percentile they paid at, and how equity worked.
Her simple rule: clarity kills confusion. If you don’t explain, you’ll explain forever.
4. Calibrate by function, one size doesn’t fit all.
Different roles demand different incentives.
Sales: Pay for results. Competitive base, plus commissions that double once targets are hit. Only pay commissions when cash is received.
Customer Success: Reward adoption and retention, not just renewals. Tie bonuses to usage, NPS, or product adoption metrics.
Product: Add outcome-based incentives.
Tyler Hogge (ex-Divvy, Pelion) recommends linking PM comp to measurable impact, ARR growth or retention improvement. Use equity-heavy rewards to align ownership and urgency.
5. Make comp a reflection of culture.
How you pay people signals how you lead. Compensation isn’t just money, it’s communication.
Overpay too early → you lose discipline.
Underpay or hide your process → you lose trust.
Reward early and fairly → you build loyalty and speed.
Compensation at the early stage isn’t about spreadsheets. It’s about alignment. Define your philosophy, educate your team, and move fast when people earn it.
How fundraising size impacts your startup’s unicorn odds
A new study from Stanford Graduate School of Business analysed how total capital raised correlates with a startup’s chance of hitting the $1B valuation mark and the results are clear: money matters, but only up to a point.
Startups that raise small rounds rarely make it to unicorn status, but those that cross certain fundraising thresholds dramatically increase their odds.
Here’s what the data shows:
<$20M raised → 0.3% unicorn odds. Almost zero.
$20–40M → 1.2%. Triple the chance, but still low.
$40–80M → 2–4%. The early growth lift begins.
$120–160M → 5–6%. The probability accelerates.
$160–200M → 8–10%. The sweet spot.
$200M+ → 9.6%. Returns start to flatten.
Key takeaway: Raising more does increase your unicorn probability, but the relationship plateaus after ~$200M. Beyond that, capital alone doesn’t make you more likely to succeed.
For founders:
Hitting $100–200M raised signals institutional belief and maturity, this is where scaling velocity, not survival, defines outcomes.
But fundraising isn’t destiny. Execution, market timing, and compounding growth still drive whether those dollars turn into billions.
In short: Big rounds open the door to unicorn status. But what happens next depends on what you build, not just what you raise.
Unconventional tactics for validating your startup ideas - from founders of Linear, Mercury and More.
Every founder asks the same question at the start: “Is my idea any good?” But the best founders don’t look for generic validation; they run sharp, unconventional tests that expose the truth fast.
Here’s how the founders of Linear, Mercury, Maven, Crossbeam, WorkOS, and Sprig did it, shared by firstround:
1. The “Founder Discovery” Method, Crossbeam
Instead of asking customers, founder Bob Moore asked other founders: “Would you start this company?”
When multiple founders picked the same idea and started introducing him to potential customers, he knew it was real.
→ Validation trigger: founders show FOMO and help you sell it.
2. The “Minimum Viable Test”, Maven (Gagan Biyani)
Forget the MVP. Test the smallest atomic unit of your product that must work.
Example: Maven ran one paid cohort with Sam Parr before building anything, 9/10 satisfaction, $150K earned.
→ Validation trigger: people pay, rate high, and refer.
3. The “Sell It Before You Build It”, Material Security
Founders pitched 4 startup ideas using fake sales decks, no product, no mockups, just bullet points.
The winner? The one where prospects asked, “How much does it cost?” and “When can we use it?”
→ Validation trigger: prospects talk next steps, not compliments.
4. The “Undercover Research” — Linear
While still at Uber, the founders quietly asked coworkers what they hated about their dev tools.
Everyone complained but assumed it couldn’t be fixed, that insight became Linear.
→ Validation trigger: strong pain that everyone accepts as “normal.”
5. The “Cold Test” — Sprig
Ryan Glasgow refused to ask friends. He cold-emailed YC founders with mockups.
If strangers were willing to spend multiple hours co-designing with him, it meant the pain was real.
→ Validation trigger: busy strangers volunteer their time repeatedly.
6. The “Feasibility First” — Mercury (Immad Akhund)
Instead of testing demand, he tested if it was possible to build a compliant online bank.
He spoke to 90 lawyers, regulators, and fintech founders until the “impossible” looked merely hard.
→ Validation trigger: the biggest barrier becomes a solvable challenge.
7. The “Bad Idea That’s Actually Good” — WorkOS (Michael Grinich)
He looked for ideas everyone disliked but he knew were painful and unsolved. Enterprise infrastructure felt boring and that was the moat.
→ Validation trigger: smart people dismiss it, but target users are desperate.
There’s no single “right” validation playbook, but the pattern is clear:
Test before you build.
Ask the right people (not just users, but founders, sceptics, and insiders).
Look for time, money, or introductions, not compliments.
Every “billion-dollar idea” starts with one signal that can’t be faked: real people leaning in.
Measuring true efficiency in Venture exits (RBCx’s exit velocity index)
John Rikhtegar introduces the Exit Velocity Index (EVI).
Not all billion-dollar exits are equal. RBCx’s new Exit Velocity Index (EVI) ranks how efficiently startups create value, not just how big they get.
EVI = (Exit Value / Total Equity Raised) × (1 / Exit Age)
It measures how fast and capital-efficient a company built enterprise value across 3,317 North American VC-backed exits ($10M+, 2010–2025).
1. Big doesn’t mean efficient.
Mega-exits like Uber, Palantir, Instacart, and Lyft rank far lower once you factor in how much capital they burned and how long it took to exit.
→ Example: Uber’s EVI ≈ 5.3x, while Mir’s $400M exit on $2M raised in 2 years scored EVI = 100, outperforming even WhatsApp’s legendary $22B exit.
2. Time kills velocity.
Companies that took 15–20 years to exit (Yahoo, Reddit, ServiceTitan, Procore) scored among the lowest EVIs despite large outcomes.
→ Median exit age of the top 100: 10 years.
3. Capital efficiency defines winners.
Median capital efficiency: 13.9x, but only 0.8% of exits achieved EVI > 20.
That tiny group includes WhatsApp, Datadog, Coinbase, and a few under-the-radar mid-sized acquisitions.
Key takeaways
EVI reframes success: size alone is a poor measure of performance.
Efficiency and speed compound returns: shorter build times and leaner raises often beat mega-funded unicorns.
For LPs and founders: benchmark by EVI, not just valuation. It reveals who built durable value fast, not just who raised the most.
EXPLORE MORE
💡 Reports, Articles and a few interesting stuffs
The trap of weak product-market fit — lessons from Mercury’s founder.
The future of the web in the history of YouTube
Turn the first meeting into leads
Only 100 metrics matter
How Intercom built a $50MM ARR empire using strategic content marketing and SEO.
Self-driving SaaS: When software runs itself
Taste is a competitive advantage.
I’m drowning in AI features I never asked for, and I absolutely hate it.
How to figure out what customers care about.
NEWS RECAP
🗞️ This week in startups & VC
New In VC
Silicon Valley VC giant Sequoia launched its latest $950M venture fund and its sixth dedicated seed fund. (Link)
Polaris Partners, a Boston, MA-based venture capital firm, is raising $500m for its eleventh fund. (Link)
Burnt Island Ventures, a NYC-based venture capital firm dedicated exclusively to funding early-stage water innovation, closed its second fund at $50m. (Link)
New Startup Deals
Reflectiz, a Boston, MA-based provider of a web exposure management platform, closed its $22m Series B funding. (Link)
Sparrow BioAcoustics, a St. John’s, NL-based cardiac AI platform developer, closed a $10 million financing round. (Link)
Homecourt, a Los Angeles, CA-based home and personal fragrance brand, raised $8m in Series A funding. (Link)
ConductorOne, a San Francisco, CA-based AI-native identity security platform provider, raised $79M in Series B funding. (Link)
Flamingo, a Miami, FL-based provider of a platform for IT service providers, launched from stealth with $2.2m in pre-seed funding. (Link)
Valthos, a San Francisco, CA-based AI biodefense startup, raised $30 million in seed financing. (Link)
Sizable Energy, a Milan, Italy-based long-duration ocean energy storage company, raised $8 million in funding. (Link)
chCurbWaste, a NYC-based operating system for independent waste hauliers, raised $28m ina Series B funding round. (Link)
TODAY’S JOB OPPORTUNITIES
💼 Venture capital & startup jobs
All-In-One VC Interview Preparation Guide: With a leading investor group, we have created an all-in-one VC interview preparation guide for aspiring VCs. Don’t miss this. (Access Here)
VP of Fundraising - Scale Asia Venture | Japan - Apply Here
Research Analyst - Positive Sum | USA - Apply Here
Associate - Venture Capital - Artha Venture Fund | India - Apply Here
Executive Assistant - AN Venture Partner | USA - Apply Here
Analyst - Urban Partners | London - Apply Here
Operations / Program Analyst - Entrepreneur First | India - Apply Here
Venture Fellow - Commonweal Venture | NYC - Apply Here
Investor Relations - Samved VC | India - Apply Here
Interim Senior Analyst, Investments - Pivotal Ventures | USA - Apply Here
Trade Operations Lead - Manhattan Venture Partner | USA - Apply Here
AI Builder In Residence - True Venture | USA - Apply Here
VP of Fundraising - Scale Asia Venture | Japan - Apply Here
Associate - OMERSE Venture | USA - Apply Here
Trade Operations Lead - Manhattan Venture Partner | USA - Apply Here
PARTNERSHIP WITH US
Get your product in front of over 95,000+ audience - Our newsletter is read by thousands of tech professionals, founders, investors and managers worldwide. Get in touch today.
🔴 Share Venture Curator
You currently have 0 referrals, only 5 away from receiving a 🎁 gift that includes 20 different investors’ contact database lists - Venture Curator