if you're integrating AI into an existing company, learn from the people actually doing it software - @sarahmsachs (head of AI at notion) - @fergal_reid (chief AI officer intercom, building fin) - @fnthawar (VP head of eng shopify, AI-first engineering) - @dharmesh (co-founder/CTO hubspot, publishes simple.ai) - @karrisaarinen (ceo linear, automation loops inside the product org) - @levie (ceo box, enterprise AI adoption) - @cramforce (CTO vercel) - @briansolis (head of global innovation servicenow) - @robdthomas (SVP ibm) fintech - @emilygsands (head of data & AI at stripe) - @rahulgs (CTO ramp, agentic systems in production) - @geoffintech (CPO ramp, wrote the company-wide AI adoption playbook) - @daschreiber (ceo lemonade, AI in insurance) data & defense - @ssankar (CTO palantir) - @2112Power (founder hadrian, automated factories for defense & space) mobility - @praveenTweets (SVP CTO uber, 70%+ of PRs now from agents) - @aelluswamy (leading AI at tesla) - @dmitri_dolgov (co-ceo waymo, physical AI at scale) - @qasar (ceo applied intuition) who else should i add?

one of the most valuable and easiest content formats for VCs to produce: when you're considering investing in a startup, you already spend a ton of time researching the market, talking to industry experts, understanding the competition, and figuring out where the real opportunities are by the end, you have a pretty solid understanding of the space. you know the biggest problems, how people are solving them, what's changing, and where the market might be heading then you make a decision: invest or pass and that's what makes the research especially interesting. you've done enough work to make an actual investment decision, so there's real conviction behind your conclusions so why not turn that research into content? basically, an anonymized investment memo without the numbers, focused on the market and product category rather than a specific startup. if you passed on the deal, you could also share more specific feedback privately with the founders, including the reasons behind your decision it's valuable for everyone: - founders, especially those just entering the space, get a much better understanding of the market - other investors can use it to get up to speed and know what questions to ask when a similar startup approaches them - agencies and service providers can better understand the industry's challenges and tailor their offerings to potential clients you're already doing the hard part. might as well turn it into something useful for others

the best fundraising strategy is to ask investors for advice tell them you've been working on something and have a hypothesis you'd love their thoughts on. they've seen hundreds of startups, so you want to know if you're thinking about the market the right way use the conversation to show how well you understand the problem, the market, and what you're building if you're onto something genuinely interesting, they'll probably ask if you're raising anyway. that's literally their job, finding great companies to invest in and if they're not interested, you still win. you'll hear their concerns, get a chance to address those concerns, and be better prepared when you talk to other VCs

facts that were true in 2020 > the average founder of a top 0.1% startup was 45 > 50-year-old founders were 2x more likely to succeed than 30-year-olds > founders in their early 20s had the lowest chances of a successful exit > even in tech, the average founder was around 40 > 3+ years of industry experience doubled your odds of building a top startup > founders who successfully exited were 46.7 on average facts that are true in 2026 > average AI unicorn founder age dropped from 40 in 2020 to 29 in 2024 > AI startups reach unicorn status in 4.7 years vs ~7 years historically > outside AI, unicorn founders are still getting older > health and biotech unicorn founders are older than those in other sectors > 40% of unicorn founders are repeat entrepreneurs > 25% of unicorn founders are immigrants

don't have ambitious people around you? build your circle online here are some of the best young builders on X to learn from and connect with - @gajesh (18, engineer eigenlabs, building darkbloomai) - @richardzphotoz (19, media & brand a16z) - @zach_yadegari (19, sold cal ai, building yourpersona) - @DeRonin_ (20, ceo arcane, angel investor) - @jia_seed (22, co-founder jam, ex-big tech) - @im_roy_lee (ceo cluely, raised $15m from a16z) - @sandylikesfrogs (Stanford, experiments with AI agents running businesses) - @0xSigil (Thiel Fellow, founder underdogai, backed by a16z) - @ansonyuu (hardware normalfactoryco, AI + manufacturing) - @mathurahravi (design engineer netflix, runs rabbitholeathon) - @AnnieLiao_2000 (founder solaris_ai, grew buildclub to 70k+) - @_rajanagarwal (AI research openai, ex-Amazon AGI) - @aditabrm (built r-1, reducto's document parsing model) - @schisofrenia (co-host MTSlive, AI interviews) - @hannahsgao (math/CS stanford, ex-openai) who else should i add?

if you're 15–19, these are some of the best programs you can apply to in 2026 1. Hack Club (free clubs + hackathons, ages 13–18) 2. Emergent Ventures (grants, ages 13+, rolling) 3. +EV ($1k–$50k grants, no equity) 4. Z Fellows (1 week, any age, optional $10k investment) 5. MIT THINK (up to $1k + MIT trip, deadline ~Jan 1) 6. Thiel Fellowship ($250k, no equity, must drop out) 7. RSI (free MIT/Stanford research, deadline Dec 11) 8. MIT PRIMES (free math research, deadline Nov 2) 9. Simons Summer Research (lab research, US juniors 16+) 10. MITES Summer (free 6 weeks at MIT, US juniors) 11. Beaver Works Summer Institute (4 weeks, AI + engineering) 12. Summer Science Program (5-week research, juniors only) 13. PROMYS (6-week math program, ages 14–18) 14. Canada/USA Mathcamp (5 weeks, ages 13–18) 15. Ross Mathematics Program (6-week math, ages 15–18) 16. SUMaC (Stanford math, grades 10–11) 17. Davidson Fellows ($25k–$100k scholarships, US) 18. Breakthrough Junior Challenge ($250k, video competition) 19. Neo Scholars (CS undergrads, optional $40k + residency) 20. Interact (2 fully funded retreats, ages 18+) 21. Dorm Room Fund ($40k investment for student founders) 22. MLH Fellowship (12 weeks remote + stipend, ages 18+)

one bad agreement can cost you the company you've spent years building and most founders don't fully understand what they're signing until something goes wrong so I built an open-source AI skill that reviews investment agreements and helps you spot the risks before you sign it works with term sheets, SAFEs, SAFTs, convertible notes, and full document sets it checks the terms against frameworks like YC, NVCA, and BVCA, flags risky clauses, explains what they actually mean, and helps you figure out what to negotiate one of my favorite features is that it can also model different exit scenarios and calculate exactly how much each shareholder would receive almost nobody does this properly, even though your liquidation preferences, dilution, and other terms can make the difference between walking away with millions or literally nothing to test it, I uploaded an old SAFT from our first startup we were 19, had lawyers involved, and thought the agreement was perfectly normal within 6 minutes, it found a bunch of things we should've questioned: personal guarantees, investor protections that heavily favored the other side, restrictions on how we could price our tokens, and even a reference to a separate agreement we'd never seen knowing all this beforehand would've completely changed how we approached that deal of course, AI won't replace a good lawyer, but it can help you understand what matters, ask better questions, and catch expensive mistakes before signing it's completely free and open-source just send this to Claude Code, Codex, or any other AI agent with terminal access: run npx skills add paulklayvc/skills --skill vc-terms-review and set it up for this agent

the exact same principles that apply to poker also apply to venture capital 1. the right decision can still lose going all-in with pocket aces is usually the right move, even if your opponent ends up hitting the card they need. investing in a great company can also be the right decision, even if it eventually gets written off you always need to think long-term. if you're consistently making bets with positive expected value, you should come out ahead over enough repetitions but you can still lose money in the short term, and that doesn't make you a bad investor 2. trust your intuition only when you've seen the same situation a hundred times intuition should work like a trained neural network. with enough training data, it performs well in familiar situations. but when it encounters something completely new, it's much more likely to get things wrong that's why decisions in unfamiliar territory deserve more time and careful thinking 3. discipline starts with your deal funnel we see dozens, sometimes hundreds, of pitches every day, but we've invested in just over 28 companies you need real conviction before making an investment. there's no reason to deploy capital just for the sake of deploying it at the same time, you can't afford to move slowly when a great deal comes along the trick is knowing how to wait patiently and act fast when it matters 4. remember what founders promised you one of the most useful habits I've developed is writing down the promises and milestones founders give you, then comparing them with what actually happens this works for companies you've invested in, companies you might invest in later, or even just to test your own judgment and with AI, tracking all of this has become incredibly easy if the actual numbers are even remotely close to what the founder projected, that's already a great sign even better if they managed to pivot and achieve much better results in my experience, 95% of the time, the results look completely different 5. know when you're going to fold before the hand starts you should have a clear plan for when to walk away before you even play the hand in venture, this becomes especially important when a portfolio company asks for a bridge round I think the best approach is to evaluate the opportunity as if you were seeing the company for the first time would you invest in this company today, knowing everything you know now? if the answer is no, you probably shouldn't put more money in the fact that you've already invested isn't a good enough reason to invest again 6. be honest with yourself you're going to make mistakes in both poker and investing. the important part is learning from them and constantly improving your judgment one of the GPs at Begin Capital always says something I really like: after your first 100 deals, you love everything. after 2,000, you think everything is terrible. only after that does your radar finally become calibrated, and you start making good investment decisions and there are some great examples of people who went from professional poker to successful careers in VC: @hosseeb, @pratyushbuddiga, @seanlippel, @gametheorizing, @JeffGrossPoker, @phil_hellmuth, @zachcoelius

top 6 mistakes founders make when dealing with VCs (all based on real cases) 1. conflicts of interest even if VCs tell you it doesn't matter and they'll support all their portfolio companies equally, conflicts of interest can get complicated very quickly just look at the public dispute involving Factory AI's @matanSF and @vkhosla investors often have access to your roadmap, customer data, financials, and internal discussions. when the same investor backs your closest competitor, it's reasonable to question how that information is handled before accepting an investment, find out which other companies the fund has backed in your space and whether they plan to invest in direct competitors if there's an overlap, make sure the information-sharing boundaries are clear and reflected in your agreements, especially if the investor wants a board or observer seat 2. investor rights you don't fully understand I've seen founders spend weeks negotiating valuations while paying surprisingly little attention to the investor rights agreement the dispute involving @isaiah_p_taylor and @mashadrokova is a good example of how complicated pro-rata rights and waivers can become the parties disagree about what happened, but it raises an important issue: some rights can be temporarily waived and later restored, while others can be amended with approval from a majority of investors, depending on the agreement that means an investor's rights can sometimes change without their individual consent it's worth going through these scenarios with your lawyer before closing. understand which rights can be amended, who has the authority to do it, and how those changes could affect future rounds 3. giving third parties access to your cap table your cap table contains some of the most sensitive information about your company, including ownership, investment history, and shareholder details @karrisaarinen discovered that @cartainc's secondaries team had contacted Linear shareholders about buying their shares without the company's authorization Carta said an employee had violated internal procedures and subsequently exited the secondaries business @ItzSuds later raised a related concern about how much control companies actually have over their data on Carta both are worth keeping in mind when choosing any platform that handles sensitive company information I'd pay particular attention to how the company uses shareholder data, which teams have access to it, whether that information can be used for other commercial purposes, and how easily you can export it if you decide to leave 4. losing control of your own company owning the largest individual stake in a company doesn't necessarily mean you control it Benchmark was an early investor in Uber, and @bgurley sat on its board for years. after he stepped off, Benchmark's relationship with @travisk escalated into a legal dispute over board seats and governance whatever your opinion of that conflict, it's a good example of how much influence investors can have through board structures the important thing to understand is who can appoint and remove directors, what decisions require board approval, and which decisions can be made without the founder's support also consider how that structure might change after another two or three funding rounds a board arrangement that seems perfectly reasonable at seed can become a serious problem later 5. liquidation preferences and who actually gets paid in an exit @naval co-founded Epinions, which raised $45M from VCs. when DealTime acquired the company, more than 6 million common shares were valued at zero, while preferred investors received equity in the combined company Shopping com, the combined company, went public in 2004 and was worth around $750M by the end of its first day of trading. Naval and other former founders sued, alleging they'd been misled about Epinions' real value the lesson is pretty simple: your ownership percentage means very little if you don't understand who gets paid first and how your shares are valued in an exit before raising, model what happens if your company sells below its last valuation, especially after multiple funding rounds with different liquidation preferences sometimes a lower valuation with cleaner terms is a much better deal 6. terms that give investors all the upside and leave founders with the risk @JosephJacks_ recently shared allegations about a fund offering terms that included a 5x return requirement, full anti-dilution protection plus additional equity, and the right to remove founders if the 5x wasn't achieved within three years I haven't independently verified those terms, but the combination illustrates something founders should be very careful about investors already receive certain protections through preferred shares and investment agreements when those protections become excessive, you can end up in a situation where the investor has significantly reduced their downside while retaining most of the upside and if the agreement also gives them the ability to remove you from the company, the consequences can extend far beyond dilution worth understanding how these provisions work together, rather than evaluating each one separately one more thing I'd strongly recommend is doing reference calls with founders whose companies didn't work out it's relatively easy to find founders who speak highly of their investors when everything is going well the more interesting questions are about what happens when a company misses targets, struggles to raise its next round, or has to shut down how did the investor behave? did they continue supporting the founder? how did they handle difficult decisions? those conversations can tell you much more about the people you're about to spend the next 5-10 years working with

the whole idea behind late-stage investing is that it's supposed to be less risky but what's interesting is that this is becoming less and less true in today's market businesses and business models used to be much more stable if a company had $5M in revenue and 40% margins, you could reasonably expect those numbers to stay relatively stable. they weren't going to change dramatically in a matter of days now that can happen all the time margins can change overnight, customers can quickly switch to a better solution, and an entire business model can become much less attractive in a very short period of time and there's another thing I think a lot of people are overlooking we're now entering a world of trillion-dollar companies but the number of investors who can actually participate in rounds at those valuations is much smaller think about it if you invest at seed and want to exit at Series B, there are plenty of funds that can participate in that round and potentially buy your stake but if you invest at a valuation of several hundred billion dollars and the company eventually reaches $1T, who are you going to sell to? there are very few investors capable of writing checks that large at that point, an IPO might be your only realistic exit opportunity, and the company might have plenty of reasons to stay private so you could end up taking on significant risk at a late stage, while also having far fewer options to exit which makes the traditional idea that later-stage investing is automatically safer a lot less obvious than it used to be

you could probably outperform 90% of VCs just by being less conservative and moving faster most funds are so locked into their thesis that they'll pass on an incredible deal simply because it doesn't fit the stage or sector they originally raised money for even if they have a chance to invest a significant amount and even when they do find a great opportunity, most VCs are incredibly slow by the time they finish their meetings, internal discussions, and due diligence, the round is already closed the best deals don't wait around. if you want to get into exceptional companies, you need to make decisions fast and there's another problem with being too conservative the market is changing so quickly that a thesis that made perfect sense 2 years ago might be completely irrelevant today even the idea that staying a small fund is always a great strategy is starting to change that's why I think flexibility and speed are two of the biggest advantages a VC can have of course, it's much easier said than done you need a really deep understanding of the market to know when to stick to your thesis, when to rethink it, and when an opportunity is worth moving fast for

one of the best things you can do as a VC is give founders honest feedback when you pass on a deal here’s why: 1. don't burn bridges if you pass on a company and it ends up taking off, you might want to get into the next round but why would the founder let you in if you couldn't even explain why you passed the first time? 2. good feedback is valuable on its own good founders appreciate thoughtful feedback, especially when it comes from someone who actually understands their market sharing your real reasons for passing shows that you've done your homework, have your own opinion, and aren't just following the crowd and even without investing, you've already given the founder something useful so there's really no point in making up some polite excuse to avoid an uncomfortable conversation just tell them what you actually think

where to find great people for your team look for people who contribute to open source or build their own open source projects why? they’ve already shown you two important things: - they’re willing to spend their own time building something and sharing it for free. a pretty good sign they genuinely love what they do and are motivated by more than just money - you can actually see their code, contributions, and how good they are at what they do surprisingly few people recruit this way, so there’s a real opportunity to find amazing talent before everyone else does

full list of tools to turn influencers and clients into distribution without paying them upfront equity, rev share, referrals, exclusive access, case studies you can set up the whole system for almost nothing 1. vet people before giving them anything - @Favikon_ (free). creator rankings by niche and country, calculators. useful for checking someone before offering equity or upside - @SocialBlade (free). growth history across YouTube, TikTok, Instagram, Twitch, and Facebook. quickly shows whether an audience has been growing organically 2. give them equity - @founding (free). Founder Institute FAST Agreement. standard advisor equity framework and agreement - @cartainc (free up to 25 stakeholders / $1M raised). issue equity, manage SAFEs, cap table, and 83(b)s 3. run referral and rev share deals - @useAffonso by @zilvestro ($15–19/mo, 14-day trial). best for starting out. affiliate tracking, payouts, and campaigns. up to $1k/mo in partner revenue - @getRewardful ($49/mo). affiliate and referral tracking. up to $7.5k/mo in partner revenue - @ToltHQ ($69/mo). affiliate tracking for SaaS. up to $10k/mo in partner revenue start with Affonso, then move up once partner revenue grows 4. create exclusive access and invite codes - @getwaitlist ($15/mo, 7-day trial). waitlists, invite codes, referral leaderboards, position tracking, who referred whom 5. track every partnership - @attio (free for 3 seats). CRM for influencer and client relationships with live contact syncing and up to 50k records 6. turn good partnerships into proof - @SenjaHQ by @helloitsolly (free for up to 15 testimonials). collect testimonials, embed them anywhere, and turn them into case studies. one strong name makes the next partnership much easier to close

stop paying for customer acquisition before you try this give an agent your business and acquisition budget it’ll find people who already have access to your customers, figure out how to partner with them, and build the whole channel for you just open-sourced the skill for free here’s what it did for an AI implementation agency with only $500/month to spend on acquisition: - $3k per implementation - 2 clients so far - room for 2 more a month $500 isn’t much if you’re trying to compete for paid traffic but this business only needs 2 more clients a month so instead of going after customers directly, the skill started with a much better question: who already has access to them? it mapped out 7 groups: business coaches, fractional CFOs, peer advisory groups, agency consultants, trade coaches, law and accounting advisors, and tech partners then sent 7 research agents out in parallel 45 potential partners came back it narrowed those down to the best 30 based on customer overlap, incentives, competition, and how realistic the partnership actually was then the useful part started for every partner, it found a public contact route and explained why they were a fit the best opportunities were ranked, with the top 5 picked to start with then it worked out what to offer them the whole point is to avoid paying upfront, so it looks at what the business already has that could be valuable to a partner revenue share, reciprocal referrals, custom work, access, upside, or something else that makes sense for both sides from there, it wrote personalized outreach for the top 5 and worked out the economics behind each partnership then it turned the whole thing into a 60-day pilot with clear targets and a point where you stop if it isn’t working so you don’t end up with another AI-generated spreadsheet full of names you get: who already has your customers -> who to partner with -> what to offer -> how to reach them -> whether the economics work -> what to test first all built around a $500/month budget the skill is open source and free send this to Claude Code, Codex, or any other agent with terminal access: run npx skills add paulklayvc/skills --skill bootstrap-growth and set it up for this agent

best free tools I use to get a 70% reply rate from cold outreach read the article first, then steal this stack: 1. finding the right person @boardyai. tell it what you’re building and it’ll find someone relevant from 240k+ people it has talked to. if you can get a warm intro, take it @TheOrgCom. free org charts with reporting lines, titles, and team sizes. really useful when you know the company but have no idea who you should actually message 2. searching X X advanced search. completely free and still insanely underused. use operators like min_faves:500, since: and from: to find people already talking about the problem you solve. also great for researching someone before reaching out 3. finding contacts @useapolloio. 900 credits a year, granted monthly @prospeo_io. 100 credits a month. searches are free, you only use a credit when you reveal a contact both are enough if you’re doing targeted outreach instead of blasting thousands of people 4. finding the email @EmailHunter. 50 credits a month. domain search helps find the company’s email pattern, then you can verify the address before sending anything 5. making sure your emails actually land CanISendThis by @jessethanley. send it an email and it checks SPF, DKIM, DMARC, unsubscribe headers, and deliverability across Google, Yahoo, and Outlook. takes around 30 seconds and can save you from wondering why nobody is replying when your emails are just going to spam 6. researching the person @clay. 500 actions a month. Claygent can research someone across the web and pull together the useful context F5Bot. free alerts whenever someone or something you’re tracking gets mentioned on Reddit or Hacker News Google News RSS. add /rss to a Google News search and you’ve got a free live feed for that person or company. fundraises, launches, new hires, interviews. basically all the context that can give you a natural reason to reach out 7. finding where they’ll actually reply @whatsmynameproj. put in one username and it checks 700+ platforms. people reuse usernames everywhere. sometimes finding someone’s X, Telegram, or another personal account is much more useful than sending another. email to an inbox with 500 unread messages 8. writing the message no tool. seriously. use AI for research. use it to critique your draft. use it to find things you missed but write the final message yourself. people are getting very good at recognizing AI outreach the tools can find the right person and give you all the context. you still need to think