Jimmy E. Chan

Winning early GTM via founder led sales is an essential step in building a consequential start up. 🎯 But, while there are countless conferences focused on scaling GTM once you've hit a couple million in revenue, to date there hasn't been a conference focused on FOUNDER LED SALES and nailing the earliest days of GTM. 👀 😅 That ends now. 🙌 Pear VC has helped 100+ founders learn how to sell, how to build their 0-to-1 sales engine, how to get from $0 ARR to $1M ARR -- and now we're introducing the first ever GTM CONFERENCE for EARLY STAGE FOUNDERS. ⭐ "Zero to $1M: Winning Early GTM" will be held in San Francisco, CA this September 5th! ⭐ If you're at the idea 💡, pre-seed 🌰 , or seed stage 🌱 , this is the GTM conference for YOU. Come hear from Pear veterans, industry leaders, and successful repeat founders like Sanjit Biswas (Samsara and Cisco Meraki Co-founder and CEO), and leave with actionable guidance to supercharge your startup’s revenue from day 1. ​ ➡ APPLY NOW! Space is limited, and the early application deadline is July 15th. Pepe Agell and I will review applications on a rolling basis. 🚀 CANNOT WAIT TO SEE YOU THERE! 🚀 #earlystageGTM #zeroto1M #founderledsales

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New!! How to Think About Product-Led Growth, Bootstrapping vs VC, and Early Exits with SaaStr CEO and Founder Jason Lemkin: Jason Lemkin, SaaStr CEO and Founder took questions from founders on everything from product-led growth to knowing when to sell your company. The post How to Think About Product-Led Growth, Bootstrapping vs VC, and Early Exits with SaaStr CEO and Founder Jason Lemkin appeared first on SaaStr.

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Venture Capital Contact Compilation. Explore a detailed list of 1,250+ VC firms, 7,400+ professionals in the VC space (including partners and principals), and 6,400 email contacts. https://payhip.com/b/cs7UQ #startup #startups #vc #venturecapital #investmentbanking #privateequity #managementconsulting #b2b #founders #entrepreneurs

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Going from Zero to Product Market Fit is like getting out of a Bermuda Triangle For every direction that works out, an equal and opposite direction works too It is shocking how few get to product market fit Only 15 out of 100 SaaS companies get to a million dollars in revenue When you have PMF, it is an awesome feeling Everything is going smoothly for you It also feels scary and out of control You push one unit, and ten units of progress happen But when you don’t have it…. You push ten units of effort, and not even a unit of progress happens It feels like a Sisyphean punishment Moving a boulder up the mountain In the GenAI age, I hear arguments that go “The focus should be on the core functionality. Like how musicians concentrate on the music itself” This is clearly a faulty analogy Businesses providing playback formats (cassette tapes, CDs) are obsolete today Gen AI brings AI below the API No more does one need to stand up a team in ML Spend a few million dollars to “translate languages” or “transcribe accurately” GenAI now assures that Getting to PMF boils down to the basics - Do you understand the problem deeply - Can you build a 10x better solution - Can you execute & iterate faster - Don’t die in the process (cash) What has worked for you to get out of the Bermuda triangle?

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Y Combinator’s journey began by backing startups with just $6K checks per founder. Today, they write $500K checks and have a portfolio worth over $600 billion. Our latest edition of the "Founders' Journey" series dives into YC's path through innovation, scaling startups, and building a global ecosystem that empowers visionary founders. Fun fact: Sam Altman and Reddit were part of YC’s very first cohort of 8 companies in the summer of 2005. 🔗 Link in comments for the full story #ycombinator #startups #venturecapital #AI #coffeespace

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Organizing an intimate meetup for high-growth founders building dev tool / Infra / b2b SaaS, together with Bain Capital Ventures this Friday in SF. If you've either: - Raised at least $2M or achieved at least $250k ARR for your current company - Or, you’re a repeat founder who has raised at least $10M or achieved at least $1M ARR in a previous company - Or, had a previous exit for at least $5M Please comment/DM to get tickets - 5 more spots left

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Rolling into another day of the Primary Summit. Hit me up if we should connect onsite. Kudos to the Primary Ventures team so far, as yesterday’s Pre-Seed Summit was on point. Mar Hershenson, Benjamin Sun, Chris Douvos, Zach Weinberg, and Graham Pingree all dropping helpful nuggets for fund managers. Some paraphrased highlights: - Chris Douvos (AHOY Capital) - Most fund decks are terrible. Start with your people (not your strategy) and know you have about 6 slides of his attention. - Zach Weinberg (Curie.Bio ) - beleives SF’s AI talent is a significant advantage over NY, wouldn’t build AI in NY. Also questions if VC exits can keep up with VC expansion (generally hilarious and smart Twitter follow) - Mar Hershenson (Pear VC) - VC is so much more competitive now. It’s not enough to be an ex-founder with a great network and domain expertise. Have a better “why you are different” or do something else! - Benjamin Sun (Primary Venture Partners)- still sees arbitrage in going long NY venture (vs. SF). Do the work to keep various influential networking nodes aware of what you’re doing and how you think.

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The journey from $1 to $10M in ARR is typically an exercise in finding your first channel-market fit as a GTM/Marketing leader and/or founder. After prioritizing the top 1-3 channels you believe are most likely to be a fit for your product, finding channel-market fit is typically an exercise in experiments and iterations. If you’re flying blind bc you don’t have the systems, processes, and data hygiene setup to measure and test quickly inside a framework, it’s going to be a difficult journey. Check out the podcast I did with the team at Evron for more mistakes to avoid on your journey from $1M to $10M ARR.

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I've invested in over 300 startups over the last 5 years, and there is one common trait that nearly all failed early stage startups share - they don't run a proper customer discovery process. You can read about the importance of customer discovery all over the internet, but that practical application of it among first time founders is still extremely low. We look at over 10,000 deals each year Forum Ventures and I see firsthand just how few founders actually excel in this process. One subset of founders simply doesn't do it at all. It's a classic archetype - build product in a vacuum without running any validation cycles. Typically the founder profile here skews more technical/product where founder-led sales feels out of character and not an area they enjoy spending time. Often founders think they can "product their way" to initial customers, but more often than not that new feature set they are excited about fails to generate user demand, simply because they never asked anybody if they care about what they were building. There is a classic startup'ism - first time founders focus on product, second time founders focus on distribution - and it rings very true within this subset. The second group of founders actually understands the importance of running discovery and leans into it early in their build process. While they have the best intentions, ultimately they come up short because in practice they don't actually know how to run an unbiased process. Discovery that focuses around a feature/solution set will skew toward lukewarm positive responses from potential customers, "sounds interesting, let me know when the beta is ready". The reality is no one is going to tell you that your baby, in this case your product, is ugly when it's far easier to just smile and nod. Founders often take this false signal as validation and race to ship a product that ultimately falls flat on its face. There is an art to soliciting feedback from a potential customer. The process emphasizes questions on their existing workflows, bottlenecks they experience in their day to day, understanding what motivates them and how they measure success in their role. This is a critical area we emphasize when evaluating investment opportunities, and a process we are very hands on in assisting our portfolio companies. Having a strong network is a massive advantage when launching a startup but close network relationships have the potential to give false signals across a customer discovery process. There are ways to combat this by being very deliberate when once solicits feedback from their network, but there are definitely bonus points for net-new out of network customer validation.

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On the surface you may think that this advice given by Sam Altman and Y Combinator may only apply to consumer products, but it also applies to products like SDKs. Let me explain! At Velt (YC W22) we make an SDK that enables developers to quickly build amazing collaborative experiences like you get in Figma, Google Sheets, Slack, Loom, etc. When you make an SDK that empowers developers to easily integrate high quality features that users want into their products, then those developers will tell other developers about it. On top of that, more and more products are starting to add collaborative commenting to their products to the point that it is going to become an expectation from users. Velt SDK is the SDK that developers will be recommending as this trend continues, and more products look to build their own collaborative features.

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We continue to see a thaw in the "VC winter" and good news from Carta showing that VC fundraising is up 17% YoY (US data), although early stage lags later stage. This may be ok however, as previously late stage was stuck and there needs to be a balance. You can't shovel money into early stage companies if they cannot raise later stage capital. Increasing later stage capital means rising confidence in exits which is great news. In order to return to normalcy we will need to see exits that return capital to VC LPs and let them recycle that capital into fresh investments. Too much potential liquidity is now stuck in older funds. Will 2025 be the year?

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⭐ At defy.vc we've been exploring the evolution of pricing in an AI-first world. 🚀 AI-first companies are shifting away from traditional SaaS models and embracing more dynamic, transactional pricing strategies to capture larger market opportunities—especially those tied to labor spend. 🔑 Why the Shift? With AI automating workflows and replacing manual labor, businesses are exploring new ways to price based on input or output rather than the typical subscription model. The goal? Align with customers' specific ROI and cost structures while tapping into industries where labor is a significant cost. 💡 Key Pricing Models for AI-First Products: 1. Fixed Cost (SaaS) – Ideal for daily-use cases, like AI generated marketing collateral or compliance checks. 2. Input-Based – Charges by consumption (e.g., data processed or queries made). Think of AI-powered discovery tools for law firms. 3. Output-Based – Pay for specific outcomes (e.g., automating administrative tasks in healthcare). 4. Hybrid Models – A mix of subscription and usage, giving flexibility without sacrificing predictability. 💬 When to Choose Which? It all comes down to how often your customers use the product, their existing budget for labor vs software, and how aligned your pricing is with the value they perceive. As the AI market grows, so does the opportunity to experiment with pricing that reflects real-world savings and efficiency improvements. The right model could unlock new revenue streams—and new value for your customers. Curious how to navigate this shift? Dive deeper into the pros, cons, and use cases of each pricing model. 🌟 Link to the full post in the comments. Thanks to Ximei Li for the collaboration and thought partnership! #AI #PricingStrategy #TechInnovation #SaaS #AIProducts #StartupStrategy #BusinessModel

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I've recently heard two different stories that illustrate the stark differences in how AI is affecting the job market: - One startup founder said he laid off two junior engineers. Now, he's involved in coding himself (he has a background in software engineering) and uses GPT/Copilot. He mentioned that product development is much faster now compared to when he had the two junior engineers. - Out of this year’s graduates from a top 50 computer science master’s program, only one person received a job offer upon graduation. One student applied to 60 companies and received zero interview requests—not zero job offers, but zero interviews. It seems like AI is making experienced, senior professionals more effective at their jobs, reducing the need for junior employees. But if no one hires juniors, how can anyone become senior? The job market continues to be very challenging. I hope this is just a short-term, interim phenomenon as we figure out how to integrate AI into the workforce. In the meantime, we might also see the rise of tiny companies, including one-person businesses or small (less than 3 people) startups.

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I analyzed over 100 AI products. What if **neither** AI powered SAAS startups nor incumbent AI enhancements are where the most value creation will happen? Substack about this: https://lnkd.in/gyM2YQQ8 #AI #productmanagement #genai #SAAS #enterprise #startups

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A recent conversation with a founder: His company developed a B2B SaaS product. They showed some initial promise but ultimately couldn’t achieve meaningful growth. They didn’t reach product/market fit. Then they kept developing more features. And some more features. All of a sudden, they had a product with 12 different main features, none of which was a killer differentiator. The product surface area was so large that the engineering team was always busy just maintaining the codebase. As founders, we all know this isn’t the best way to go. But avoiding this trap is easier said than done — it's just how human psychology works. We get backed into a corner, and our instinct is to work harder and do more things. Occasionally, in the history of products, there have been those that were stuck but finally achieved breakthrough growth with that one key feature. We feel we have to keep the team busy; we can’t have them idle. The list goes on. That’s why, when stuck, sometimes the team needs to slow down at least a little bit and use their brains more than their bodies (i.e., building more features). Startups don’t have abundant resources, so the only edge they can have is to do one thing (which will turn out to be the game changer) really well. It’s about finding that one game-changing thing, not doing more things.

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When user acquisition teams optimize for average acquisition costs, they often engage in volatility washing—smoothing out high-variance acquisition metrics to achieve a static target without accounting for the fact that some proportion of their spend has been wasted. While this can't necessarily be controlled with automated tools like PMax and Advantage+ -- which I've written about extensively -- it's often completely ignored on other channels when only the average CPA over a period of time is considered with respect to performance. However, marginal CPA is more relevant than average CPA, especially over an extended timeline (e.g., monthly), and teams neglect it at their peril. An interesting thought experiment: if you knew that every dollar spent on user acquisition for the remainder of the month would be unprofitable given that marginal CPA exceeds product LTV, but the month would nonetheless appear profitable on an average basis, would you continue to invest in user acquisition?

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