Our team at Pear is thrilled to announce an incredible new resource for our Healthcare and Biotech founders.Today, we are officially unveiling Pear’s Healthcare and Biotech Industry Advisory Councils!
At Pear, we feel privileged to work closely with our founders at the earliest stages of company development, specializing in seed and getting founders to product market fit. We also aim to provide them with best-in-class platform support across talent, go-to-market, fundraising, and PR & communications.
We recognize, however, that our founders building in Biotech and Healthcare have specialized needs. Over the past few months, our Biotech Partner, Eddie and our Healthcare Partner, Vivien have been hard at work carefully crafting and recruiting a “dream team” of leading founder-CEOs, operators, executives and academics. We’re so honored to be partnering with this esteemed group and are grateful for their generosity to support the next generation of founders.
Introducing Pear’s Biotech and Healthcare Industry Advisory Councils:
In Biotech, we often back stellar scientists and engineers starting companies based on innovative platform technologies with multiple applications. They are leaders within their domains of technical expertise, but they understandably need help in areas such as selecting a lead indication, developing a partnering strategy, negotiating an IP license, or refining a program budget and timeline.
In Healthcare, we are looking for multidisciplinary teams with clinical, technical, and go-to-market DNA. Technology can only make a difference if health systems providers, payers, and pharma are willing to adopt these solutions and we believe our advisory council helps refine customer strategy and supercharge our founders’ customer adoption, along with our hands on GTM support at Pear.
Learn about how we invest in Healthcare and Biotech:
We have created landing pages on our website for our Healthcare and Biotech investing practices which share more details about our investment scope, approach to working with founders, and current Industry Advisory Councils.
We’ve already been impressed by the impact these advisors have made on our founders and their companies, and we can’t wait to see what’s next!
If you’re a Healthcare or Biotech founder and interested in partnering with Pear VC or getting to know our advisors, please reach out at email@example.com and firstname.lastname@example.org.
Founders often ask us what kind of AI company they should start and how to start something long lasting?
Our thesis on AI and ML at Pear is grounded in the belief that advances in these fields are game-changing, paralleling the advent of the web in the late ’90s. We foresee that AI and ML will revolutionize both enterprise software and consumer applications. A particular area of interest is generative AI, which we believe holds the potential to increase productivity across many verticals by five to ten times. Pear has been investing in AI/ML for many years, and in generative AI more recently. That said, there’s still a lot of noise in this space, which is part of the reason we host a “Perspectives in AI” technical fireside series to cut through the hype, and connect the dots between research and product.
Much of the progress in Generative AI began with the breakthrough invention of the transformer in 2017 by researchers at Google. This innovation combined with the at-scale availability of GPUs in public clouds paved the way for large language models and neural networks to be trained on massive datasets. When these models reach a size of 6 billion parameters or more, they exhibit emergent behavior, performing seemingly intelligent tasks. Coupled with training on mixed domain data such as the pile dataset, these models become general-purpose, capable of various tasks including code generation, summarization, and other text-based functions. These are still statistical models with non zero rates of error or hallucination but they are nevertheless a breakthrough in the emergence of intelligent output.
Another related advancement is the ability to employ these large foundational models and customize them through transfer learning to suit specific tasks. Many different techniques are employed here, but one that is particularly efficient and relevant to commercial applications is fine tuning using Low Rank Adaptation. LoRA enables the creation of multiple smaller fine tuned models that can be optimized for a particular purpose or character, and function in conjunction with the larger model to provide a more effective and efficient output. Finally one of the most important recent innovations that allowed the broad public release of LLMs has been RLHF and RLAIF to create models that are aligned with company-specific values or use-case-specific needs. Collectively these breakthroughs have catalyzed the capabilities we’re observing today, signifying a rapid acceleration in the field.
Text is, of course, the most prevalent domain for AI models, but significant progress has been made in areas like video, image, vision, and even biological systems. This year, in particular, marks substantial advancements in generative AI, including speech and multimodal models. The interplay between open-source models (represented in white in the figure below) and commercial closed models is worth noting. Open-source models are becoming as capable as their closed counterparts, and the cost of training these models is decreasing.
Our thesis on AI breaks down into three parts: 1. applications along with foundation / fine tuned models, 2. data, tooling and orchestration and 3. infrastructure which includes cloud services software and hardware. At the top layer we believe the applications that will win in the generative AI ecosystem will be architected using ensembles of task specific models that are fine tuned using proprietary data (specific to each vertical, use case, and user experience),along with retrieval augmentation. OrbyAI is an early innovation leader in this area of AI driven workflow automation. It is extremely relevant and useful for enterprises.We also believe that tooling for integrating, orchestrating, evaluating/testing, securing and continuously deploying model based applications is a separate investment category. Nightfall understands this problem well and is focused on tooling for data privacy and security of composite AI applications. Finally, we see great opportunity in infrastructure advances at the software, hardware and cloud services layer for efficient training and inference at larger scales across different device form factors. There are many diverse areas within infrastructure from specialized AI chips to high bandwidth networking to novel model architectures. Quadric is a Pear portfolio company working in this space.
Successful entrepreneurs will focus on using a mixture of specialized models fine tuned using proprietary or personal data, to a specific workflow along with retrieval augmentation and prompt engineering techniques to build reliable, intelligent applications that automate previously cumbersome processes. For most enterprise use cases the models will be augmented by a retrieval system to ensure a fact basis as well as explainability of results. We discuss open source models in this context because these are more widely accessible for sophisticated fine tuning, and they can be used in private environments for access to proprietary data. Also they are often available in many sizes enabling applications with more local and edge based form factors. Open source models are becoming progressively more capable with new releases such as Llama2 and the cost of running these models is also going down.
When we talk about moats, we think it’s extremely important that founders have compelling insight regarding the specific problem they are solving and experience with go-to market for their use case. This is important for any start up, but in AI access to proprietary data and skilled human expertise are even more important for building a moat. Per our thesis, fine tuning models for specific use cases using proprietary data and knowledge is key for building a moat. Startups that solve major open problems in AI such as providing scalable mechanisms for data integration, data privacy, improved accuracy, safety, and compliance for composite AI applications can also have an inherent moat.
A high level architecture or “Anatomy of a modern AI application” often involves preprocessing data, chunking it and then using an embedding model, putting those embeddings into a database, creating an index or multiple indices and then at runtime, creating embeddings out of the input and then essentially searching against the index with appropriate curation and ranking of results. AI applications pull in other sources of information and data as needed using traditional APIs and databases, for example for real time or point in time information, referenceable facts or to take actions. This is referred to as RAG or retrieval augmented generation. Most applications require prompt engineering for many purposes including formatting the model input/output, adding specific instructions, templates, and providing examples to the LLM. The retrieved information combined with prompt engineering is fed to an LLM or a set of LLMs/ mixture of large language models, and the synthesized output is communicated back to the user. Input and output validation, rate limiting and other privacy and security mechanisms are inserted at the input and output of LLMs. I’ve bolded the Embedding model, and the LLMs, because those benefit from fine tuning.
In terms of applications that are ripe for disruption from generative AI, there are many. First of all, the idea of personalized “AI Assistants” for consumers broadly will likely represent the most powerful shift in the way we use computing in the future. Shorter term we expect specific “assistants” for major functional areas. In particular software development and the engineering function overall will likely be the first adopter of AI assistants for everything from code development to application troubleshooting. It may be best to think of this area in terms of the jobs to be done (e.g., SWE, Test/QA, SRE etc), while some of these are using generativeAI today, there is much more potential still. A second closely related opportunity area is data and analytics which is dramatically simplified by generative AI. Additional rich areas for building generative AI applications are all parts of CRM systems for marketing, sales, and support, as well as recruiting, learning/education and HR functions. Sellscale is one of our latest portfolio companies accelerating sales and marketing through generative AI. In all of these areas we think it is important for startups to build deep moats using proprietary data and fine tuning domain specific models.
We also clearly see applications in healthcare, legal, manufacturing, finance, insurance, biotech and pharma verticals all of which have significant workflows that are rich in text, images or numbers that can benefit greatly from artificial intelligence. Federato is a Pear portfolio company that is applying AI to risk optimization for the insurance industry while VizAI uses AI to connect care teams earlier, increase speed of diagnosis and improve clinical care pathways starting with Stroke detection. These verticals are also regulated and have a higher bar for accuracy, privacy and explainability all of which provide great opportunities for differentiation and moats. Separately, media, retail and gaming verticals offer emerging opportunities for generative AI that have more of a consumer / creator goto market. The scale and monetization profile of this type of vertical may be different from highly regulated verticals. We also see applications in Climate, Energy and Robotics longer term.
Last but not least, at Pear we believe some of the biggest winners from generative AI will be at the infrastructure and tooling layers of the stack. Startups solving problems in systems to make inference and training more efficient, pushing the envelope with context lengths, enabling data integration, model alignment, privacy, and safety and building platforms for model evaluation, iteration and deployment should see a rapidly growing market.
We are very excited to partner with the entrepreneurs who are building the future of these workflows. AI, with its recent advances, offers a new capability that is going to force a rethinking of how we work and what parts can be done more intelligently. We can’t wait to see what pain points you will address!
Last month, PearX S21 alum Transcera announced its seed round led by Xora Innovation, joined by Tau Ventures and existing pre-seed investors Pear, Digitalis Ventures, and KdT Ventures. To mark this milestone, we wanted to share more about Pear’s partnership with Transcera and its founders, Hunter Goble (CEO), Justin Wolfe (CSO), and Wayne Lencer (scientific co-founder).
We first met Hunter and Wayne when they applied to Pear Competition. Hunter was still an MBA student at HBS and Wayne was a professor at Harvard Medical School and researcher at Boston Children’s Hospital. At the time, they were part of the Nucleate program and looking to commercialize a new drug delivery platform they were working on.
When we met the team, we were excited about Transcera for several reasons:
Enormous unmet need and market opportunity. Today, many of the most impactful and best-selling medicines are so-called biologic drugs, comprising complex molecules that are typically synthesized via living systems rather than chemical means. These are large, bulky molecules including peptides or proteins that often exhibit little-to-no uptake upon oral dosing, and instead have to be injected into the blood or under the skin. For obvious reasons, when given a choice, patients strongly prefer the convenience of a self-administered pill. For example, pharma companies are now racing to develop orally administered versions of GLP-1 receptor agonists for obesity, as the first such drugs approved for this blockbuster indication have required administration via subcutaneous injection.
Broad, differentiated, and defensible technology platform – inspired by nature, informed by high-quality science, and validated preclinically. For almost three decades, Wayne and his group have been studying how large, orally ingested bacterial toxins, such as cholera toxin, are able to cross the intestinal epithelial barrier to cause disease. The lab discovered that structural features of key membrane constituents called glycosphingolipids directly influence the cellular sorting of these lipids and any associated payloads. Building on this foundational work, Transcera has demonstrated preclinically that synthetic lipids can be harnessed to achieve transport of biologics across intestinal barrier cells, enabling oral delivery and enhanced biodistribution. This active transport mechanism is differentiated from most existing approaches to enhancing oral bioavailability, which have primarily focused on passive diffusion enabled by permeation enhancers and other formulation excipients, and have suffered from relatively low absorption and narrow applicability.
Ambitious operating team with complementary skill sets. Prior to HBS, Hunter spent 5 years at Eli Lilly working on the commercial launch of a key drug product, and he also served as an internal consultant around new product planning for the pharma company’s immunology division. Justin completed his PhD in the Pentelute lab at MIT where he focused on delivery strategies for biologic drugs, including novel conjugation approaches for peptides, and he later worked as a scientist advancing the discovery and medicinal chemistry of macrocyclic peptides at Ra Pharmaceuticals through its acquisition by UCB. Whereas Hunter brings a savvy commercial mindset and disciplined financial rigor to Transcera, Justin in turn brings apt academic and industry domain expertise and strong scientific leadership skills. Hunter, Justin, and Wayne all share a passion for translating basic science research into technologies and programs that can make a tremendous impact for patients.
We have been impressed with the Transcera team’s execution and scientific progress so far. During PearX S21, we worked closely with Hunter on shaping the story and crafting the pitch ahead of Demo Day. Before joining the Pear team full-time as Pear’s biotech partner, I served as an industry mentor to Transcera, advising the team on questions related to IP in-licensing. After joining Pear, I continued to work closely with Transcera and fellow syndicate co-investors on scientific strategy, fundraising, and partnering.
Over the past two years, the Transcera team has proven to be resilient and resourceful. The production and scale-up of the synthetic lipid conjugates were challenging to master, but the team’s diligent efforts yielded multiple promising lead compounds. Critically, the team has expanded to bring in hands-on expertise in chemistry, cellular biology, and preclinical development, among other areas.
With this recent financing, we are excited to continue to back the Transcera team, and we are eager to see further development of the platform, with the ultimate goal of unlocking the full potential of biologic drugs for patients.
I’m incredibly excited to share that Arash Ferdowsi, Co-founder and former CTO of Dropbox, has joined Pear as our newest Visiting Partner!
I’ve known Arash since 2007, when Dropbox was still just two people: Arash and his Co-founder Drew. I was immediately inspired by their vision and drive and fortunate enough to be an early backer. The first time I sat down with Arash and Drew, we didn’t talk about the ins and outs of cloud storage, but instead we just talked about becoming good long-term partners.
Arash helped to grow and scale Dropbox from inception to IPO. As Co-founder and CTO, he truly accomplished so much: building and scaling a company that is used by hundreds of millions of people.
Arash departed the company in 2020, and since that time he’s become a successful angel investor. We’ve been fortunate to partner with him on co-investments and welcome him to Pear as a visiting speaker on a number of occasions.
Over the last 15 years, Arash and I have truly built a great relationship on a foundation of true partnership, and I’m very excited to have him join Pear in a more official capacity.
We’re looking forward to Arash working with Pear founders. Welcome to the family, Arash!
Honey Homes, closed their Series A recently, led by Khosla Ventures and supported by Pear and others. To mark the occasion, we thought we’d do a little lookback of our history working with the Honey Homes team over the last few years.
We were first introduced to Honey Homes’ Founder and CEO Vishwas Prabhakara through DoorDash alums, including Evan Moore. The Khosla team knew that the Honey Homes team had a promising early idea and felt Pear would be great seed partners in shaping it into a venture-scalable business.
Once we met the team, we were excited about backing them for a few key reasons:
First of all, we knew this was a massive and unsolved market opportunity. US homeowners spend $250 billion annually on their homes via a highly-fragmented vendor network. The Honey Homes team saw a big opportunity to streamline that network and create a product experience that has never existed for home owners. Most home services companies are marketplaces or managed marketplaces, so it is challenging to make the economics work and keep the quality bar high while scaling. This results in churn from both the supply and demand side. Honey Homes saw an opportunity to do things differently and build out a new model – a homeowner subscription business where they employ handy people. This changes the economics and raises the quality bar substantially.
Secondly, they had a clear vision for a product to meet that market demand. The Honey Homes team wanted to build a membership service for busy homeowners to manage and complete to-do lists. I was a new homeowner myself at the time, could easily relate the never ending list of tasks to maintain my home and the difficulty of finding and keeping handymen. I found the idea of a reliable membership service really enticing.
Finally, we felt that the team was really strong and perfectly suited to tackle this problem. Vishwas was Yelp’s first General Manager and he was also COO of Digit, where he gained valuable experience as an operator. He understood first hand the piecemealing that homeowners have to do for maintenance and improvement work. Avantika Prabhakara, who leads Marketing at Honey Homes, has a rich marketing background from organizations like Opendoor, Trulia, and Zillow, so she’s also deeply familiar with the challenges people face on finding reliable contractors and handyman services.
Khosla and Pear co-led the seed round in July 2021. Over the last two years, they’ve focused on building out the infrastructure to make this service work, growth in their initial markets, and eliminating key risks in order to raise their Series A. They grew from just a co-founding team to 12 employees and 14 handymen during this time. They also expanded across the Bay Area and Dallas and onboarded 500+ subscription customers. In total, over 20,000 home tasks have been completed for members through more than 10,000 Honey Homes visits over the last two years.
I’ve been lucky enough to not only be an investor into Honey Homes, but also an early customer. I started using Honey Homes in March 2022, and I’ve had hundreds of tasks completed in my home ranging from fixing a frustrating leaky pond to helping us move our furniture to fixing water-damaged cracks in our ceiling to cleaning out dryer ducts. We use the service so regularly that even my daughter knows our handyman, Miguel, by name. Honey Homes has had an incredibly strong customer response: everyone who hears about it wants to join and they’ve done an excellent job retaining customers.
We’re so proud of the team for successfully raising their Series A and cannot wait for their continued growth and success!
We’re excited to share that Aparna Sinha is Pear’s newest Partner! Aparna has made an outsized impact in her time with us as a Visiting Partner, and we couldn’t be more thrilled that she’s joining our team full time.
Aparna brings a strong thesis and a depth of experience in enterprise, developer, and AI to Pear and is excited to work with ambitious founders during this breakout moment in AI. “We’re in the midst of unprecedented technological advancement. AI is re-shaping our present and enabling the most significant breakthroughs of our lifetimes. The breadth and pace of this technological shift creates an opportunity for startups to disrupt the value chain and reshape how we interact with our world,” says Aparna. “Pear’s co-founder is a female former founder with a PhD in engineering, and our work to grow top female technical entrepreneurs resonates with me,” she continued.
Over the last six months, Aparna helped launch PearX for AI, a new track of the PearX program tailored towards AI builders. We recently welcomed six teams to the inaugural PearX for AI cohort and are excited for these founders to debut their companies with the world soon. Through the PearX for AI program, Aparna is partnering with founders to define their product, win early customers, and grow. She’s able to leverage her deep experience from Google and in enterprise software to give Pear’s portfolio companies an advantage in the market.
Aparna is also building out our AI advisor community, connecting Pear founders with industry experts from organizations like Stanford, Google, OpenAI, Hugging Face, McKinsey and more. At this moment, AI is touching every single facet of technology and she’s been working to build a top notch council of advisors to assist Pear founders on their entrepreneurial journeys.
We’re so excited to welcome Aparna. If you’re a founder looking to connect, please email her at email@example.com.
Last week, we welcomed Naomi Chetrit Band to the Pear team to lead our Dorm program as a Senior Associate on the investment team. At Pear, we have a long history partnering with students to build the next wave of category-defining companies. We met the founders of companies like Affinity, Viz.ai, Nova Credit, and WindBorne when they were still in school, and we love partnering with students to build businesses from the ground up. With Naomi joining our team, we’re excited to take our program to the next level.
Naomi is excited to concentrate on supporting student founders. “My lifelong excitement for learning and education finds its natural home on campuses and inside classrooms. Living in Israel, surrounded by a vibrant startup ecosystem, I developed a strong inclination towards working with founders and supporting early stage startups. Being at Pear now allows me to blend both of my passions, for which I am truly grateful,” says Naomi.
Naomi joins us from the Wharton School, where she just completed her MBA. She also worked as a Pear Fellow during her time at UPenn. Naomi is also an Israeli CPA and Attorney with a career spanning EY-Parthenon, EY, and S. Horowitz & Co.
Welcome to the team, Naomi! If you’re a student builder or want to learn more about our Dorm program, you can connect with Naomi on Twitter, LinkedIn, or at firstname.lastname@example.org.
Louis’ journey to finance and accounting began with his life-long card playing hobby. He loves working with numbers and rules, and describes himself as quietly a very competitive person. During high school and college, Louis was a professional-caliber Magic: the Gathering player, peaking as a top 300 player in the world while he was in graduate school, but his first love is cribbage, which he grew up playing with his family.
Professionally speaking, Louis is an expert at VC finance. Prior to Pear, Louis worked across finance, tax, and fund accounting at firms like Emergence, Ohana Real Estate Investors, and Foundation Capital. At Pear, Louis’ role involves managing the financial functions of the firm and working across our four funds. He closely monitors budgeting and operating finances, portfolio valuations, LP reporting, and manages the annual tax and audit process. He’s also focused on helping Pear build scalable finance processes that will meet Pear’s needs as we continue to grow.
“I am excited to be at Pear because we are working with founders at the very start of their journey. It’s so fun to be with them from day one, with a ton of excitement and opportunity in front of them. I am also excited to be working with such a humble, collaborative team. It’s fun to feel like we’re all pushing in the same direction, building something together,” Louis says.
Outside of work, Louis lives in the Bay Area with his wife, two young children, and two cats. Questions for Louis? You can reach him at email@example.com or find him on LinkedIn.
We first met Federato’s Co-founders Will Ross and William Steenbergen in March 2020, when they were first year grad students at Stanford’s Graduate School of Business. They were winners of the 2020 Pear Competition and we also invited them to join PearX, our early-stage bootcamp for founders.
When we met Will and William, they only had a product concept and some initial customer validation. But even though they didn’t have solid proof yet, we decided to partner with them in building Federato for a few key reasons:
First, we saw a big market opportunity. New risks like climate change, cyber security, and social inflation were changing the landscape. In the insurance industry, risk is the opportunity, and it’s a really hard problem to solve. Insurers operating processes are unable to accommodate emerging risks, but Federato brought a solution to the table to help insurers take on risks of under utilized data assets. We knew at the time that climate change was already affecting the insurance industry in dramatic ways. The elevated frequency of damaging weather events drove more than $100B in uninsured losses between 2018-2019 alone, and this number has only continued to grow since then.
Second, even though they were early in their journey, the founders had a clear vision. We believed in their vision to bring AI into how insurance companies manage the risks associated with an ever-changing world, including the elevated frequency of damaging weather events caused by climate change. They concluded that the best way to achieve this was through a federated learning mechanism (hence the name Federato) that would allow insurance companies to benefit from their own data, as well as other entities’ and insurance companies’ data, safely. We also appreciated that their solution delivered a simple, convenient, and beautiful UX experience, where every interaction was optimized for the user.
Third, we believed in the team from the get go. In their early days, they described themselves as “two deeply passionate, data science/product people who came together to do something about climate change with machine learning.” Will conceived of the concept behind Federato when he was an Associate at Venrock and William built ML models for the insurance industry at his prior startup, Building Blocks. Together, they researched and deeply understood the space. They didn’t just bring us an idea on a slide deck, but instead they brought a thoroughly thought out plan with multiple in-depth customer interviews, a light proof of concept built on publicly available data, and a clear understanding of the end user and end buyer. We could see that this was a team with a clear analytical mind and a bias for action, which is a rare occurrence.
During PearX, the team coined the term RiskOps, which is about realizing that risk cannot be priced without taking distribution into account. This is a tricky concept to explain clearly, but we worked closely with them to articulate this vision at Demo Day. We also partnered closely with Will and William in developing the first version of their operational underwriting software that continuously monitors risk at every underwriting decision, rather than only a few times per year. Arash and I remember working together to create hand drawn mockups of their initial software over long Zoom meetings during the height of Covid lockdowns.
Shortly after presenting at Pear’s S20 virtual Demo Day, Federato closed a Seed round led by Caffeinated Capital. Between their Seed and Series A rounds, we worked with them on important company-building milestones, like refining the product, building a strong company culture, and navigating long sales cycles through acquiring their first few customers.
We also helped the Federato team prepare for a successful Series A raise through our Series A Bootcamp. They successfully raised their Series A from Emergence in 2022.
In less than a year following the Series A raise, Federato proved itself even more. They truly became an economically efficient marketplace that connects data to the value it can actually create in underwriting. In this year, Federato team tripled their customer base, doubled their spend with existing customers, and entered new segments.
Riding off of this strong momentum, they just closed their Series B round from Caffeinated, Emergence, and Pear, and we’re excited to continue working with Will, William, and the entire (growing!) Federato team on their mission to modernize the insurance industry!
Last month, I had the immense privilege of helping judge Pear VC’s Stanford student Competition. The event highlighted the brightest student founders from Stanford vying for their first check. The Pear Competition has a history of identifying and nurturing exceptional talent, supporting unicorn companies such as Viz.ai and other breakout companies including Nova Credit, Federato, Conduit Tech, and Wagr.
Pre-seed is a notoriously hard stage to invest, as startups often lack any metrics, product, traction, or proven revenue model. The excitement and challenge lies in the ability to identify hidden gems despite the uncertainty, requiring a skillset that combines intuition, experience, and a deep understanding of market landscapes across a wide range of industries.
With the invaluable experience of judging and doing diligence on close to 100 founders alongside renowned investors and proven operators, Mar Hershenson and Ilian Georgiev, I wanted to share 5 key takeaways in pre-seed investing from one of the best early-stage VCs:
1. Passion and Market Insight
Impressive founders had a deep understanding of their market, derived from a unique blend of professional experience, customer interviews, and thorough research. They could clearly pinpoint “hair on fire” problems and delve into pain points along the customer journey in excruciating detail, ultimately laying the foundation for a compelling vision for the problem they aim to solve.
These founders masterfully answered highly nuanced follow-up questions, while still demonstrating a humbling awareness of what they still needed to learn.
2. High Learning Rate
Another exciting key trait of founders was a demonstrated “high rate of learning”. These founders were unafraid to openly discuss assumptions and hypotheses that were proven wrong, providing insights into how their understanding of the market and potential solutions continually evolved. This grounded reflection illustrated their willingness to pivot when necessary, ensuring they could navigate the inevitable uncertainties of the startup journey.
3. Execution Velocity
Several founders stood out with their relentless drive to move fast. They leveraged no-code tools, pounded the pavement to connect with customers, and used smokescreen tests to gauge demand. These tenacious entrepreneurs consistently found ingenious, low-cost, and scrappy ways to rapidly test hypotheses, never allowing a single obstacle to halt their progress. They made do with what they had, not waiting on “ideal” resources or the “perfect team”.
High commitment and perseverance was another trait we looked for in founders. Despite the glamour of eye-catching TechCrunch headlines, the reality is that the founder journey is an uphill marathon. Most startups must navigate the treacherous “pit of despair” for an average of 18 months before achieving product-market fit. A demonstrated ability to weather these upcoming challenging times after the initial excitement fades is a vital asset to tackle the inevitable hurdles of entrepreneurship.
Some of these founders had a history of starting previous businesses, often grappling with numerous setbacks and pivots. They could detail stories of struggles and challenges they faced in their founding journey, demonstrating a balance of grit and determination to continually refine their craft.
5. True Meaning of a “No”
Perhaps the most insightful lesson was that a “no” from a VC often does not mean that the founder or the business wasn’t exceptional. Many factors can contribute to a “no” despite an impressive company, such as a competing investment, the market size, or a mismatch with the VC’s sector focus. Founders often forget that building an outstanding business and securing funding from a specific VC are distinct pursuits. Never let a single “no” derail your founding journey. Embrace the challenge, learn from the feedback, and keep building. Success is not solely defined by the checks you secure but by the impact you create through the relentless pursuit of your vision.
In essence, the art of pre-seed investing lies in recognizing founders who possess a unique combination of passion, adaptability, and resilience. These entrepreneurs are driven by their vision and demonstrate an uncanny ability to navigate uncertainty, making them invaluable assets in the early-stage startup ecosystem, and proving that success is ultimately measured by the tenacity to transform a compelling idea into a lasting impact.
Guest post written by Alex Wu, a Pear Fellow at Stanford.