# From 0 to 3 Million: The Glasp Growth Story Source: https://glasp.co/story --- # Chapter 1: Why We Built Glasp *The story of how a small team grew a web highlighter from zero to 3 million users, told chapter by chapter.* In September 2020, Glasp started as nothing more than an idea and a few lines of code. A tool that would let people highlight and save the parts of the internet that mattered to them, capturing knowledge that would otherwise be scattered or lost. We had no funding, no users, and certainly no playbook for how to grow a web service in the crowded landscape of productivity tools. What we did have was a mission: to create a platform where knowledge could be shared openly, where the insights you highlight today might help someone else tomorrow. We wanted to build a digital legacy of human learning, a place where knowledge doesn't die with us but lives on for others to discover. This story is about how we grew Glasp from zero to 3 million users without traditional growth hacking shortcuts or massive marketing budgets. Instead, we focused on creating genuine value, building authentic connections, and staying true to our mission even when growth seemed painfully slow. ## A Journey That Was Never a Straight Line Our path hasn't been a smooth climb. There were pivots, experiments that failed, and many moments of uncertainty. We adjusted our target audience several times, from product managers to writers to broader knowledge workers. We jumped on emerging technologies like AI while keeping our core focus on human curation and connection. And when the way people find information shifted again, from search engines to AI answer engines, we had to rethink distribution from first principles one more time. Each chapter of this story covers one part of that journey: - How we built our initial user base through hundreds of personal onboarding calls (Chapter 2) - How we leveraged underused distribution channels like academic backlinks, Medium, and repeat Product Hunt launches (Chapter 3) - How we created viral moments by being early with AI tools like our YouTube Summary with ChatGPT (Chapter 4) - How a community of learners became our strongest growth engine (Chapter 5) - How we adapted when AI assistants started answering questions directly, and what we did about it (Chapter 6) - Why a two-person startup began publishing research papers, and what that did for us (Chapter 7) - The principles that held all of it together (Chapter 8) - The lessons that survived it all, and where the journey goes next (Chapter 9) ## What This Story Is, and What It Isn't This isn't a blueprint to replicate exactly. Your product and circumstances will be different. Rather, it's a collection of principles, stories, and tactics that worked for us. Some strategies took months to bear fruit. Others created immediate spikes in users. The common thread was authenticity, persistence, and a genuine desire to create something of lasting value. There is also a personal thread running through it. Part of why Glasp exists is that I nearly died when I was young, and that experience left me with a question I couldn't put down: what happens to everything a person has learned when they're gone? Glasp is our attempt at an answer. If the things you read, highlighted, and found meaningful can be passed on, then learning becomes something you leave behind, not just something you consume. Whether you're building your own product, growing a community, or simply curious about how a small team can compete in today's digital landscape, we hope our experience offers useful insights. The greatest growth hack isn't a trick or shortcut. It's creating something people genuinely want to use and share, and then having the patience to let that value compound over time. Let's begin at the beginning, with zero users and a lot of hope. --- # Chapter 2: Finding Your First 1,000 Users ## The First 100: Friends, Family, and Faith Every startup begins with a crucial question: who will use this? In the early days of Glasp, the answer was simple: we would. We built it first for ourselves, creating a tool to save and organize the content we were consuming online. But product development isn't just about code. It's about people. I still remember sending those first hesitant messages in August and September 2020: "I've built something I think could be useful. Would you mind trying it out?" Those first users weren't strangers. They were friends, former colleagues, and people in our immediate network. We called this "founder-friend" distribution: personally reaching out to people we knew and asking them to try our product. The initial growth was painstakingly slow. One by one, user by user, we grew to our first 100 users through direct messages and personal connections. But these weren't just any users. They were people willing to get on a video call with us, to share their screens, and to give us unfiltered feedback about what worked and what didn't. ## One-on-One Onboarding: The 800-Call Marathon Looking back, the numbers seem staggering. By the time we reached 1,000 users, we had personally conducted over 750 onboarding calls. Each call lasted 15 to 20 minutes, with my co-founder Kei and I splitting them between mornings and evenings. These weren't sales pitches. Each call started with our story: why we created Glasp, our vision for an open knowledge platform, and how we hoped to make a difference. We shared personal experiences, sometimes including how I nearly died and how that shaped our mission to make knowledge live beyond individuals. The most valuable part came next. We asked users to share their screens and show us how they currently saved information online. We watched as they navigated through Notion pages, browser bookmarks, and note-taking apps. We observed where they hesitated in our sign-up flow, where they got confused, and what excited them. "Can you click there?" we'd ask, using Zoom's annotation features to guide them. "What were you expecting to happen when you clicked that button?" These calls were exhausting but invaluable. They gave us: 1. **Real-time user feedback** on our interface and functionality 2. **Insight into user workflows** before they even touched our product 3. **Emotional investment** from users who now had a personal connection to our team 4. **Clarity on our target audience** as patterns emerged across different user types Even when users didn't become active on the platform, they remembered our story. Months or years later, some would reach out: "I remember what you're building. My colleague needs exactly this!" Others became unofficial advisors, like the SEO consultant who regularly sent us reports without being asked. The lesson was clear: in the earliest stages, depth of connection matters more than breadth of reach. Those calls created a foundation of users who didn't just try our product. They understood why it existed. ## Finding Our Target Audience One of the most challenging aspects of building Glasp was identifying exactly who it was for. Initially, we noticed many of our saved articles related to product management, so we hypothesized that product managers might be our target audience. This led to our first focused outreach efforts. We joined product management communities on LinkedIn and Slack, some with 150,000 members. We carefully identified active members and sent personalized messages about how Glasp could help them compile reading lists of product management articles. The response was encouraging but revealed an important insight: product managers would sign up and bookmark articles, but they weren't highlighting or taking notes as often as we'd hoped. More importantly, they rarely shared their collections with others. This led to our first pivot. If we wanted Glasp to spread through word of mouth, we needed users who not only consumed content but also had an incentive to share it. Writers, particularly content writers and SEO specialists, emerged as a promising audience. "Writers need to research, compile sources, and then create content from those sources," we reasoned. "What if Glasp could bridge that gap?" We shifted our outreach to writing communities, and soon found users who were using Glasp in their workflow with editors. They would research articles, highlight key passages, and then share their Glasp profile with editors during review sessions. This was a crucial early lesson: your initial hypothesis about who will use your product is often wrong. The users who get the most value from your product might be in an adjacent space you hadn't considered. By conducting hundreds of personal conversations, we could spot these patterns and adjust quickly. Each audience pivot wasn't a failure. It was a refinement of our understanding. Every conversation brought us closer to finding the people who would not only use Glasp but champion it to others. ## The Power of Screen Sharing: Learning by Watching One of the most valuable aspects of our onboarding calls wasn't what users told us. It was what they showed us. By asking users to share their screens, we gained insights that no survey or analytics dashboard could provide. We saw how people actually organized information in their digital lives. Some had meticulously organized Notion databases. Others had browser bookmarks stretching back years. Many were using screenshots or copy-pasting text into notes as makeshift ways to save important passages. This direct observation revealed pain points that users themselves couldn't articulate. When someone says "I want a better way to save articles," they might not mention that they also need those articles to be easily searchable six months later, or that they'd benefit from seeing highlights from other readers. Screen sharing also exposed usability issues immediately. We'd watch as new users hesitated over buttons, misunderstood features, or searched for functions in the wrong places. Rather than wondering why our activation metrics weren't improving, we could literally see the friction points. "I notice you're looking for the highlight button on the top menu," we'd say. "We actually put it in the right-click menu. Does that make sense for your workflow?" These observations directly informed product improvements. We made the onboarding flow more intuitive, clarified confusing terminology, and prioritized features based on the workarounds we saw users creating for themselves. Don't just listen to users. Watch them. The gap between what people say they do and what they actually do is often where the most valuable product insights hide. ## Cost-Conscious Growth: Why We Avoided Paid Channels In the early days of Glasp, we made a deliberate choice that shaped our entire growth strategy: we would focus exclusively on channels with near-zero customer acquisition costs. This wasn't just about being frugal. As a consumer product without a clear monetization strategy, we knew that paying to acquire users would be unsustainable. If our customer acquisition cost (CAC) couldn't be recouped, growth would eventually hit a wall. "If we're not going to make money from users right away, we can't spend money to get them," we reasoned. This constraint became a creative advantage. We identified two primary channels that aligned with this zero-CAC approach: 1. **SEO**: Creating content that would continue to drive traffic for years without ongoing costs 2. **Word of mouth**: Building features valuable enough that users would naturally share them This focus on organic growth meant progress was slower at first. While other startups were celebrating rapid user growth through paid ads, we were meticulously crafting content, building backlinks, and refining our product based on direct user feedback. We wrote tutorials on Medium, created guest posts for other blogs, and produced content addressing specific use cases like "How to export highlights from Kindle" or "Top Chrome extensions for researchers." Each piece of content was designed to rank for valuable keywords while demonstrating Glasp's utility. We were particularly strategic about backlinks, recognizing their outsized importance for SEO. We reached out to educational institutions (including my alma mater) and even government sites like the Japanese Ministry of Education to secure high-authority links. These efforts required persistence, and many emails went unanswered, but the links we gained provided enduring SEO value. This disciplined approach meant that our user acquisition wasn't dependent on continuing to spend. Once a piece of content ranked well or a community of users formed, it continued to drive sign-ups without additional investment. The slow-but-sustainable approach paid off. By the time we reached our first 50,000 users, our blended CAC was mere cents per user, a foundation that allowed us to scale to millions without raising significant funding. ## The Multiplier Effect: Translating Content into Multiple Languages Early on, we discovered a powerful growth lever that exemplified our efficient approach: content translation. After being featured in a publication called Ness Labs, we asked users who spoke other languages if they'd be willing to translate the article. The response was overwhelming. Our users translated that single article into nearly 10 languages, including German, Italian, Spanish, and Tagalog. Each translation opened Glasp to new language markets without requiring us to create new content from scratch. This multiplier effect became a recurring strategy. When we created valuable content in English, we could extend its reach by having it translated by community members. Instead of writing ten different articles, we could write one great article and have it reach ten different markets. The translations did more than increase our reach. They made users feel like contributors to our mission. The people who helped translate weren't just users; they became part of building Glasp's global community. This experience taught us that constraints often lead to creativity. Without a budget for professional translation or international marketing, we found a solution that was not only cost-effective but actually strengthened our community bonds. ## Case Study: Our First 1,000 Users By the time we reached 1,000 users, we had developed a repeatable (if labor-intensive) process: 1. Identify a community of potential users (initially product managers, then writers) 2. Join their groups and communities (primarily on LinkedIn and Twitter) 3. Send personalized messages introducing Glasp (hundreds per day) 4. Conduct one-on-one onboarding calls with interested users 5. Gather feedback and continuously improve the product 6. Create content targeting their specific use cases 7. Encourage satisfied users to share with colleagues The journey to 1,000 users took approximately three months of consistent effort. While not rapid growth by venture capital standards, these were high-quality users who understood our product deeply. Many of these early adopters remain active users years later and have become our most vocal advocates. What's remarkable is how different this approach is from conventional growth tactics. We didn't use giveaways, viral loops, or aggressive marketing. Instead, we built genuine relationships with real users and let our product's utility speak for itself. This foundation of authentic growth would serve us well as we began to scale beyond our initial user base. The next challenge was finding ways to reach tens and then hundreds of thousands of users without losing the personal touch that had defined our early growth. --- # Chapter 3: Distribution That Compounds After reaching our first 1,000 users through direct outreach and personal onboarding, we faced a crucial question: how could we grow beyond our personal networks while maintaining zero (or near-zero) customer acquisition costs? The answer lay in finding scalable distribution channels that aligned with our long-term vision. We needed methods that would compound over time rather than requiring constant reinvestment. ## SEO: Playing the Long Game Search engine optimization became our primary focus for sustainable growth. Unlike paid advertising that stops generating users the moment you stop spending, SEO investments continue to pay dividends for years. We approached SEO with three distinct strategies. ### 1. Strategic Content Creation We identified high-intent keywords related to our product features and created in-depth content around them. Articles like "How to Export Kindle Highlights," "Best Chrome Extensions for Researchers," and "How to Take Notes on YouTube Videos" targeted specific problems that Glasp solved. These weren't superficial blog posts designed to game search algorithms. We created genuinely helpful guides that showcased our product's capabilities while providing standalone value. A reader could implement our advice even without signing up for Glasp. This approach meant our content often ranked well for relevant keywords. More importantly, the users who found us through these searches had specific problems that Glasp immediately solved, leading to higher activation and retention rates. ### 2. Strategic Backlink Acquisition We recognized early on that certain backlinks carried disproportionate SEO value. Government (.gov) and education (.edu) domains in particular could significantly boost our search rankings. Rather than using automated outreach or link exchanges, we took a more thoughtful approach: - We reached out to my alma mater to feature Glasp in their alumni resources - We contacted the Japanese Ministry of Education to include Glasp in their educational tools directory - We established relationships with educational blogs and research platforms These high-authority backlinks didn't just improve our rankings. They placed Glasp in contexts where serious readers and researchers would discover it. ### 3. User Interview Case Studies We transformed our user interviews into detailed case studies that served two purposes at once: they provided social proof for potential users while creating valuable SEO content. These case studies highlighted diverse use cases: - A job seeker who followed product managers on Glasp and read their recommended articles to eventually land a PM role - A venture capital team using Glasp collaboratively to research potential investments - Writers using Glasp to collect research before drafting articles Each case study targeted specific keywords while showcasing real-world applications of our product. When potential users searched for ways to solve similar problems, they'd find these stories and see Glasp as a solution. The beauty of this SEO-focused approach was its compounding nature. Each piece of content we created continued working for us month after month, year after year. The results weren't immediate, often taking 6 to 12 months to fully materialize, but they were lasting and built upon each other. ## Medium: Leveraging Existing Distribution In addition to our own blog, we used Medium as a strategic channel for reaching new audiences. Medium's recommendation algorithm offered a way to get our content in front of readers who hadn't heard of Glasp. We published in-depth tutorials, thought pieces on knowledge management, and guides to effective learning. Each article included natural mentions of Glasp where relevant, without being overly promotional. The key insight was understanding Medium's algorithm, which rewards engagement. We focused on creating genuinely valuable content that readers would highlight, respond to, and share, the actions that would boost an article's distribution within Medium's ecosystem. This strategy created a virtuous cycle: users would discover our articles on Medium, many would sign up for Glasp after reading them, and then they would use Glasp to highlight and save other Medium articles, creating visible social proof of our tool within the platform. ## Guest Posting: Borrowing Audience Trust While building our own SEO presence, we simultaneously pursued guest posting opportunities on established platforms. This allowed us to borrow the trust and audience of existing publications. We specifically targeted technology blogs, productivity websites, and knowledge management communities. Rather than pitching overtly promotional content, we offered genuine value through articles like: - "Top 10 Chrome Extensions in 2022" for technology review sites (with Glasp naturally included) - "How the World's Top Thinkers Organize Their Knowledge" for productivity blogs - "The Future of Social Reading" for forward-thinking publications These guest posts served multiple purposes: 1. Introducing Glasp to established audiences 2. Building authoritative backlinks to our website 3. Positioning us as thought leaders in our space 4. Creating content that could be repurposed across channels The key to successful guest posting wasn't volume but strategic placement. A single article on the right platform could bring more qualified users than dozens of posts on less relevant sites. ## Product Hunt: Multiple Launches for Multiple Features Most products launch on Product Hunt once and consider it done. We took a different approach, launching individual features as standalone products. After our initial Product Hunt launch in September (which brought modest traffic), we realized we could return to the platform with each major feature release: - PDF highlighting capabilities - YouTube transcription and highlighting - AI summary generation - iOS and Android apps - Audio transcription tools Each of these launches brought a fresh wave of attention, backlinks, and users. More importantly, it signaled to the community that Glasp was constantly evolving and improving. This strategy of "feature as product" launches accomplished several goals at once: 1. Regular visibility on a high-traffic platform 2. Continuous backlink generation 3. A reputation for innovation and development velocity 4. Natural opportunities for previous users to re-engage What we learned was that Product Hunt wasn't just a launch platform. It was an ongoing distribution channel we could tap repeatedly with the right approach. ## The Compound Effect: Why We Prioritized These Channels Looking back, the common thread connecting all these channels was their compounding nature. Unlike paid advertising that delivers predictable but temporary results, these organic approaches started small but grew over time. Six months into our SEO efforts, we might rank for a handful of keywords. Twelve months in, that number might grow to dozens. Two years in, we could rank for hundreds of relevant terms, each bringing a steady stream of qualified users. The same compound growth applied to our content, backlinks, and community presence. Each asset we created continued working for us indefinitely, requiring maintenance rather than replacement. This approach aligned perfectly with our resource constraints. As a small team without external funding, we couldn't afford strategies that required constant reinvestment. We needed to build assets that would appreciate over time. The results speak for themselves: by the end of our first year, we had gained tens of thousands of users without spending on acquisition, laying a foundation that would eventually support millions. What's more, these users came to us already aligned with our mission. They discovered Glasp through content about learning, knowledge management, and thoughtful technology use. They weren't bounty hunters chasing free trials or incentives. They were people who genuinely resonated with our vision of open knowledge sharing. --- # Chapter 4: Riding the AI Wave While our SEO and content strategies provided steady growth, we also experienced several breakthrough moments that rapidly accelerated user acquisition. These moments weren't accidental. They came from deliberately positioning ourselves at the intersection of emerging trends and real user needs, and most of them came from one source: the AI wave that began reshaping the internet in 2022. This chapter is about how we rode that wave, and how we tried to do it without losing sight of what Glasp was for. ## The Aurelius Effect: One Right Partnership Before AI entered the picture, our first major growth acceleration came from a strategic YouTube sponsorship that returned far more than we expected. By August 2021, we had gathered enough evidence about our target audience to consider a YouTube sponsorship. Rather than spreading a small budget across many creators, we concentrated our resources on one partnership. After researching dozens of potential partners, we identified Aurelius, an Australian YouTuber with around 300,000 subscribers whose audience aligned perfectly with our target users: thoughtful knowledge workers interested in productivity and learning. The sponsorship itself was straightforward, a brief mention of Glasp in one of his videos. What we didn't anticipate was the cascade it set off: 1. Aurelius featured Glasp in a video, driving the initial wave of sign-ups 2. Other creators who watched Aurelius began discovering and mentioning Glasp 3. These creators made their own videos, posts, and articles about Glasp 4. Their audiences discovered Glasp, and the most influential among them created even more content This "influencer cascade" created a multiplier effect far beyond our initial investment. In the creator economy, reaching the right person can mean indirectly reaching their entire network of peer creators. When resources are limited, depth of partnership beats breadth. ## DALLE-dle: An Early Experiment at the Edge of AI In mid-2022, we began noticing early signals of the coming AI revolution. DALL-E had just been released, demonstrating impressive image generation. At the same time, Wordle had become a global phenomenon as a simple, engaging word game. Rather than merely observing these trends, we asked: how can we combine them with Glasp's core functionality to create something unique? The result was "DALL-E Wordle" (or "DALLE-dle"), a game where players guessed which famous quote had been used to generate an AI image. We used quotes from the highlights collected on Glasp, creating a natural connection to our core product. The experiment was featured in PC Gamer, a major gaming publication, as an interesting new take on the Wordle format, driving significant traffic to Glasp. DALLE-dle wasn't our core product, but it created awareness and positioned us as builders in the AI space just as public interest was beginning to surge. ## The ChatGPT Chrome Extension: Days, Not Weeks When ChatGPT launched in November 2022, we immediately recognized its potential. Rather than viewing it as competition, we asked how we could build with it. Within days of ChatGPT's release, we created one of the first Chrome extensions for ChatGPT, letting users access the AI assistant from any webpage. This simple tool addressed a real friction point for early ChatGPT users. The timing mattered enormously. In its first weeks, our extension became one of the most installed ChatGPT-related Chrome extensions, quickly reaching 300,000 installations and bringing a massive new audience into our ecosystem. This wasn't luck. It was the result of constantly monitoring technological trends and being prepared to act fast when an opening appeared. By being among the first to build useful tools around ChatGPT, we captured attention that would have been far harder to earn even weeks later, once the market was saturated. ## YouTube Summary with ChatGPT: The Tool That Outgrew Us Our biggest viral success combined two things we already had: YouTube highlighting (which predated ChatGPT) and our new AI integration experience. YouTube contains an enormous amount of valuable knowledge, but extracting and retaining it is hard. We built the YouTube Summary with ChatGPT, a Chrome extension that could: 1. Automatically extract the transcript from any YouTube video 2. Run that transcript through an AI model to generate a concise summary 3. Present the summary alongside the video for easy reference 4. Let users save both the summary and their own highlights to Glasp It addressed a clear pain point: the time it takes to extract knowledge from long-form video. Instead of watching a 30-minute video, users could read a summary in 30 seconds, then decide whether the full content deserved their time. The response was immediate and overwhelming. Users shared screenshots across social media, generating organic promotion we could never have afforded to buy. YouTube creators made videos showing how it improved their research process. Newsletter writers included it in their roundups of essential AI tools. Business publications like Forbes covered it as an innovative use of AI. Within a year, the YouTube Summary with ChatGPT had been installed by over 2 million users, more than double our core Glasp user base at the time. Our extension had become more popular than our product. Rather than seeing that as a problem, we treated it as an opportunity. The YouTube Summary wasn't a standalone tool; it connected directly to users' Glasp accounts, introducing them to highlighting, note-taking, and knowledge sharing. Users who came for the AI summary often stayed for the rest. It became a natural upgrade path from casual AI tool user to committed Glasp user. ## Digital Clones: Your Highlights, Talking Back Building on that momentum, we developed Digital Clones: personalized AI assistants trained on a user's Glasp highlights and notes. The concept was compelling. As you highlight articles, books, and videos in Glasp, you're effectively creating a dataset that reflects your interests, knowledge, and thinking patterns. Train an AI on that personal dataset and you get a digital extension of your mind, a "clone" that can discuss topics in a way that reflects your perspective. Digital Clones solved several problems at once: 1. It gave users a way to explore and interact with their collected knowledge 2. It provided a compelling reason to keep highlighting and saving content 3. It made our mission literal: knowledge that engages with others even beyond the individual It wasn't as immediately viral as the YouTube Summary with ChatGPT, but it attracted attention from technology publications and futurists who saw it as a glimpse of where personal knowledge management was heading. And it created a powerful engagement loop: the more users highlighted, the more useful their clone became. ## The Supporting Cast Around these flagship features, we shipped a series of smaller AI experiments and systems: - **Idea Hatch** used language models to find meaningful relationships between seemingly unrelated pieces of content in a user's collection, turning a passive archive into an active thinking partner. - **Content automation** helped our two-person team operate like a much larger one. A single YouTube video could become a structured blog post, social snippets, and newsletter content, with humans reviewing and refining rather than drafting from scratch. - **The Kindle Personality Test** analyzed a user's Kindle highlights to generate playful insights about their reading patterns and recommend books. Low development cost, naturally shareable results, and a clear connection back to reading and highlighting. None of these were core products. All of them compounded attention, trust, and sign-ups. ## What These Wins Had in Common Looking across the Aurelius cascade, DALLE-dle, the ChatGPT extension, the YouTube Summary with ChatGPT, and Digital Clones, the same principles kept showing up: ### 1. Be first, even if imperfect Our ChatGPT extension and YouTube Summary with ChatGPT weren't the most feature-rich options that eventually emerged, but they were among the first available when interest peaked. The window for a new trend is measured in days, not weeks. We prioritized speed above polish, while holding a minimum quality bar, and iterated after capturing attention. ### 2. Solve real problems tied to your core value The YouTube Summary succeeded because it killed a real pain (hours of video, minutes of time), not because it showed off AI. And every feature we shipped connected back to knowledge capture and sharing. Trend-chasing for its own sake produces traffic; trend-chasing in service of your mission produces users. ### 3. Build distribution into the product Our most viral features had sharing built in. The YouTube Summary's subtle branding appeared in every screenshot users posted. Digital Clones made people want to show others their personal AI. The product did its own marketing. ### 4. Monitor early signals None of these opportunities appeared without warning. We noticed rising interest in AI image generation before DALLE-dle, and the early excitement around ChatGPT before our extension. Paying attention is a strategy. ### 5. Enhance the core, never replace it AI features made highlighting more valuable; they didn't substitute for it. Digital Clones got better the more you highlighted. Idea Hatch got better the more you saved. Each feature deepened engagement with the core product instead of diverting from it. ## The Balancing Act: Trends vs. Long-Term Vision These viral moments accelerated growth dramatically, but they carried a risk: becoming known for trendy features rather than our mission of knowledge sharing. We navigated that tension by insisting that new features, no matter how trendy, served the long-term vision. The YouTube Summary with ChatGPT wasn't an AI gimmick. It genuinely helped people extract knowledge from video, which is exactly what Glasp exists to do. We passed on many viral opportunities that didn't fit, even when they might have driven short-term growth. In the end, these moments weren't separate from our sustainable growth strategy. They were accelerators layered on top of it. By connecting new technologies to an enduring mission, the spikes settled into sustained engagement rather than temporary attention. --- # Chapter 5: Building With the Community As Glasp grew from thousands to millions of users, we faced a fundamental challenge: how could we maintain the personal connection and community focus that defined our early days while operating at a much larger scale? This chapter explores how we built a thriving community around Glasp and how that community shaped not just our growth, but our product direction and content itself. ## Glasp Talk: Turning Interviews into Community Assets One of our most successful community initiatives was Glasp Talk, a series of interviews with professionals, thought leaders, and interesting people from various fields. What began as casual conversations evolved into a cornerstone of our community strategy. The genesis of Glasp Talk came from a key insight: the most valuable knowledge often remains locked in people's minds rather than written down in articles or books. Through conversation and thoughtful questioning, we could extract and preserve insights that might otherwise never be shared publicly. Each week, we interviewed someone notable: entrepreneurs, writers, product managers, designers, and other knowledge workers. These conversations explored their work processes, thinking frameworks, and life philosophies. While the interviews themselves provided valuable content, the true power of Glasp Talk emerged in how we integrated it with our product ecosystem: 1. **Content multiplication**: Each interview was transformed into multiple formats: video, podcast, article, highlights, quotes, and social media snippets. 2. **Evergreen knowledge**: Instead of chasing news cycles, we focused on timeless questions and insights that would remain relevant for years. 3. **Community connection**: Featured guests often became active Glasp users and advocates, introducing the platform to their networks. 4. **Legacy focus**: Every interview concluded with the same question: "What legacy or impact do you want to leave on the world?" This aligned perfectly with our mission of preserving and sharing knowledge. Perhaps most importantly, Glasp Talk exemplified our approach to community building. Rather than treating community as a marketing channel to be exploited, we created genuine value for our community members while advancing our mission of knowledge sharing. ## Email Newsletters: Old Technology, New Approach In the age of algorithmic feeds and fleeting attention, we found tremendous value in one of the oldest digital communication tools: email newsletters. Initially, we used Mailchimp to send onboarding sequences and product updates to new users. As our user base grew, the costs became prohibitive, reaching thousands of dollars per month for a startup with limited resources. We pivoted to Substack, which offered free newsletter functionality. But the real unlock came when we realized we could automatically subscribe new Glasp users (with proper opt-in) to our newsletter. This integration created a powerful growth loop: 1. New users joined Glasp and opted into the newsletter 2. They received curated content collections and community updates 3. They discovered valuable articles and highlighted them in Glasp 4. Their interactions guided future content recommendations Our subscriber base first grew past 350,000 people, with open rates around 30 to 35 percent, far above industry averages. It has kept growing since and now stands at more than 550,000 subscribers, one of our most valuable community touchpoints. The key to the newsletter's success wasn't technological innovation but curation. Every recommendation was personally selected by our team, focusing on evergreen content that delivered genuine value rather than trendy or clickbait material. This reflected our broader philosophy: we weren't optimizing for impressions or short-term engagement, but for long-term value and trust. By consistently delivering content that helped people learn and grow, we built a newsletter that people actually looked forward to receiving. ## Community-Driven Product Development From the beginning, we involved our community directly in product development. This wasn't just about gathering feedback. It was about co-creating Glasp with the people who used it most actively. Several of our most successful features emerged directly from community requests and observations: - **PDF highlighting**: After seeing users struggle to save information from PDFs, we built a dedicated PDF reader with highlighting. - **YouTube transcription**: Users were manually transcribing YouTube videos to save key points, so we built automated transcription and highlighting. - **Top highlights**: When we noticed users highlighting the same passages across articles, we created a feature showing the most highlighted passages. - **AI summaries**: Community feedback on our YouTube Summary with ChatGPT led us to expand AI summaries to all content types. By watching how our community actually used Glasp, sometimes in ways we never anticipated, we discovered features that genuinely improved their experience rather than adding complexity. We fostered this collaboration through several channels: - **Slack and Discord communities** where users could share ideas and use cases - **Regular user interviews** to deeply understand workflows and pain points - **Public feature requests** where users could vote on priorities - **Beta testing groups** for early access to new features This created a virtuous cycle. Community members felt ownership in the product's evolution, which made them more likely to stay engaged and invite others. Their input led to more useful features, which attracted more users, who brought fresh perspectives and ideas. ## The Power of Use Case Amplification One of our most effective community strategies was amplifying creative use cases discovered by our users. When someone found a novel way to use Glasp, we highlighted their approach through case studies, social media, and the newsletter. Some compelling examples: - A PhD student who used Glasp to research collaboratively with peers across universities - A book author who gathered and organized research materials through Glasp highlights - A language learner who saved and reviewed vocabulary and phrases from online content - A journalist who used our YouTube transcription to quickly extract quotes from interviews Showcasing these stories accomplished several goals at once: 1. **Educated existing users** about new ways to use the product 2. **Attracted similar users** who faced the same challenges 3. **Validated our users** by celebrating their creativity 4. **Generated content** that strengthened our SEO and social presence It also shifted the relationship from company-to-user to a collaborative community where users inspired each other. Glasp wasn't just a product; it was a platform for a wide range of knowledge workflows. ## Open Source Knowledge: Sharing Our Technology As our AI tools gained popularity, particularly the YouTube Summary with ChatGPT, we made a decision that seemed counterintuitive from a traditional business perspective: we open-sourced key components of our technology. This aligned with our core mission of open knowledge sharing. By making our code accessible, we enabled: 1. **Developer adoption**: Technical users could integrate our tools into their own workflows 2. **Community improvement**: Users contributed enhancements and bug fixes 3. **Educational impact**: Students and self-taught developers could learn from our implementations 4. **Trust building**: Transparency about how our AI tools worked increased user confidence Open-sourcing wasn't just philosophical. Developers who used our code became advocates in technical communities. Educators built tutorials around our tools, extending our reach into programming and AI learning communities. We believed the value of Glasp wasn't in proprietary technology but in the community and knowledge ecosystem we were building. Sharing our implementation strengthened our position rather than compromising it. ## Maintaining Authenticity at Scale Perhaps the greatest challenge of community building is staying authentic as you grow. With 100 users, personal relationships are natural. With millions, there's a temptation to automate and depersonalize every interaction. We addressed this with clear principles for community engagement: 1. **No growth at the expense of trust**: We refused manipulative engagement tactics, even when they might drive short-term growth. 2. **Value first, promotion second**: Every piece of content or communication had to provide standalone value, whether or not it converted users. 3. **Transparency about mistakes**: When we made errors or hit problems, we shared them openly rather than presenting a perfect facade. 4. **Continued direct engagement**: Even at scale, we kept direct connections alive through interviews, calls, and personal responses. 5. **Mission reinforcement**: We consistently tied product decisions and communications back to open knowledge sharing. Rather than seeing community as a resource to be optimized, we treated it as a collaboration between people who shared our vision for more accessible and connected knowledge. ## The Community Flywheel By the time we reached several hundred thousand users, we had created what we call the Community Flywheel: a self-reinforcing cycle where community engagement drives product improvement, which attracts more community members, who contribute more knowledge and insights. The flywheel worked because each element strengthened the others: - **User-generated highlights** created valuable data that improved recommendations - **Community-identified use cases** informed product development - **Shared knowledge collections** attracted new users with similar interests - **Public profiles and social features** connected like-minded learners Once this flywheel gained momentum, growth became increasingly organic. New features and content still accelerated adoption, but the community itself became a powerful acquisition channel as users invited colleagues, shared highlights, and created content about Glasp. This approach requires patience. Community flywheels don't generate immediate results the way paid advertising can. But they create sustainable, compounding growth that doesn't disappear when you stop spending. When building for the long term, investing in community isn't a nice-to-have. It's a strategic advantage that creates defensible network effects and reduces dependency on paid acquisition. --- # Chapter 6: The AEO Era: From Search Engines to Answer Engines For our first four years, the growth engine described in Chapter 3 kept doing its job. We wrote genuinely useful content, earned authoritative backlinks, ranked for the questions our future users were asking, and let the whole thing compound. Then the ground started to move. ## The Ground Shifted Under SEO By 2025, a growing share of the people who used to type questions into Google were asking AI assistants instead. ChatGPT, Claude, Perplexity, and Google's own AI results were answering questions directly, in full sentences, often without the user ever clicking a link. The blue links we had spent years climbing toward were being summarized away. For a company whose acquisition strategy leaned heavily on compounding search traffic, this was an existential question. It was also a familiar one. We had seen a platform shift up close before, in late 2022, when ChatGPT appeared and we shipped an extension within days (Chapter 4). The lesson from that experience wasn't "AI is coming." It was "when the interface changes, the people who adapt early win attention that latecomers have to fight for." So instead of mourning the decline of the ten blue links, we asked the same question we asked in 2022: what does this shift make newly valuable, and how does it connect to our mission? ## From Ranking to Being Cited The answer we arrived at has a name: Answer Engine Optimization, or AEO. In the search era, the goal was to rank: get your page into the top results and earn the click. In the answer era, the goal is to be cited: when an AI assistant composes an answer about highlighting, learning techniques, or research workflows, you want it drawing on your work and pointing readers back to you. What struck us was how little the underlying principles changed. Answer engines, like search engines before them, reward sources that are genuinely useful, clearly structured, and consistently trustworthy. The fundamentals we had practiced since Chapter 3 (real value, clean structure, patient compounding) still applied. What changed was the reader. We were no longer writing only for humans who skim, but also for models that parse, weigh, and quote. That reframing turned an existential threat into an execution problem. We knew how to solve execution problems. ## Deep Dive: Betting Again on Long-Form Our biggest AEO investment was content, and it looked almost old-fashioned: a library of long-form, evergreen guides we call Deep Dive. We built out more than 100 in-depth articles covering the territory our users care about: AI tools and how to choose between them, learning science, note-taking and knowledge management, reading workflows, research methods. Each one is structured the same way: a clear table of contents, key takeaways up front, FAQ sections, and consistent formatting that both a human skimmer and a parsing model can navigate. Then we applied the multiplier we discovered back in Chapter 2, deliberately this time. Every article is translated into 7 languages. Where community members once translated a single press article for us, we now run translation as a standard part of the publishing pipeline. One well-researched guide becomes seven entry points in seven markets. The bet is the same compounding bet as before: every guide is an asset that keeps working, except now it works in two ways. It ranks in what remains of traditional search, and it gets cited by the answer engines that are replacing it. ## Making Glasp Machine-Readable Content was half the work. The other half was making Glasp itself legible to machines. We added an llms.txt file to the site, a plain-language guide that tells AI crawlers what Glasp is, what lives where, and what matters most. We expanded structured data (JSON-LD) across the site, so that articles, books, quotes, and profiles describe themselves in a vocabulary machines understand without guessing. Then we went a step further than describing ourselves to AI, and connected to it. We built a remote MCP (Model Context Protocol) connector, so that users can plug Glasp directly into their AI assistants. With permission, an assistant can search your highlights, recall what you've saved about a topic, and bring your own collected knowledge into a conversation. This is worth pausing on, because it reframes what "distribution" means. In the search era, your product surface was your website and your extension. In the answer era, your product surface includes the AI assistants your users already talk to every day. Being present there isn't marketing. It's product. And it ties back to the mission in a way we found genuinely exciting. We've always said the knowledge you collect should outlive the moment you collected it. An assistant that can draw on your highlights years later is exactly that promise, kept through a new interface. ## Beyond Text Answer engines don't only read articles, and neither do people. So we started turning our strongest Deep Dive guides into other formats: podcast-style audio conversations and video versions distributed on YouTube. This was the "create once, publish everywhere" principle from our resource-efficiency playbook, pointed at a new goal. The same research that produced a written guide becomes something to listen to on a commute and something YouTube surfaces to learners who would never have found the article. Each format reinforces the others, and each is one more way to be the source an answer draws on. ## The Proof: 500 to 19,000 Daily Sessions from ChatGPT Strategy is cheap. So we measured. At the start of 2026, ChatGPT was sending us 517 visitors a day. We made a deliberate bet: stop investing in direct SEO and run the AEO playbook as a series of experiments on our largest content surface, a corpus of more than 400,000 YouTube Q&A pages. The first decision set the tone: measure from our own server logs instead of subscribing to tools that poll the models from outside. Cloudflare's AI crawler logs and Search Console told us, deterministically, which pages AI bots actually fetched and how often. That data turned guesses into a roadmap. The experiments themselves were almost embarrassingly concrete. Pages that bots requested often had question-form titles matching how people phrase prompts, so we rewrote titles as questions. They had prose summaries up top, around 130 characters, that worked as standalone answers, while ignored pages carried 14-character fragments, so we rewrote our TL;DRs to hold the complete answer even if a model reads nothing else. We mined the 404 errors AI bots left behind, tens of thousands a week, as a literal list of pages users were already asking for, and built them. We deleted tens of thousands of dead pages with zero Google and zero bot interest, and indexation on everything that remained improved. And pages already earning Google clicks were locked against rewrites, so the new channel never cannibalized the old one. Four months later, on May 5, ChatGPT referrals hit 19,129 daily sessions: 37x growth. The striking part is that AI bot crawl volume stayed flat the whole time. The same bots were visiting. They were simply finding more answers worth citing. We shared the full playbook in a guest post on Sean Ellis's newsletter, in the same spirit as everything else in this story: what we learn, we publish. ## What We Learned The AEO era is young, and we don't pretend to have it fully figured out. But a few lessons already feel solid. First, AEO is not a replacement for everything we knew. It's SEO's principles aging into a new interface. Genuine value, clear structure, and earned trust still win. If you built your growth on tricks, the answer engines are bad news. If you built it on substance, they're an opportunity. Second, being early matters again. The window we exploited when ChatGPT launched has a sequel: most companies are still treating AI search as a curiosity, which means the citations are still up for grabs. "Be first, even if imperfect" survived the platform shift intact. Third, what compounds has changed shape. It used to be rankings and backlinks. Now it's being a citable, structured, trustworthy source, in text, in audio, in video, and through protocols like MCP that put you inside the conversation itself. The deepest lesson, though, was about identity. When the way people find information changed, we didn't have to change what we are. A platform built on capturing and sharing knowledge openly turns out to be well positioned in a world where machines are constantly looking for knowledge worth repeating. The mission aged well. That confidence in substance over tactics led us somewhere we never expected a two-person startup to go: publishing original research. That's the next chapter. --- # Chapter 7: Research as a Growth Channel In 2026, Glasp started doing something that isn't in any startup growth playbook we've ever read: we began publishing research papers on arXiv. Not blog posts dressed up with charts. Actual papers, with methods sections, pre-registered thresholds, held-out test sets, and public repositories. Written by a team you can count on one hand, between everything else a startup demands. This chapter is about why we did it, what we found, and why we think original research might be one of the most underrated growth channels of the AI era. ## Why a Startup Publishes Research The honest answer has two halves, one idealistic and one strategic, and we'd be telling the story wrong if we hid either. The idealistic half: it's the mission at a different altitude. Glasp exists to make learning public, to ensure that what one person figures out can benefit the next. For years that meant individual highlights and notes. But after millions of people had saved millions of highlights, the platform itself had learned something about how humans read, and keeping that locked in a private database felt like a violation of our own premise. If a user's highlights deserve to outlive the moment, so do the patterns across all of them. The strategic half: in the answer-engine era we described in Chapter 6, original research is among the most citable content that exists. Answer engines are hungry for primary sources, for claims that come with evidence attached. A thousand blog posts repeat each other; a paper with novel findings is the thing they all end up citing. Publishing research is differentiation that cannot be copied quickly, because the only way to copy it is to do the work. ## What the Highlights Taught Us Our main research line asked a deceptively simple question: when you highlight a passage, how much of that choice is *you*? The intuition we started with, and that most of the personal-knowledge-management world shares, is that highlighting is deeply personal. Your highlights are your intellectual fingerprint. An AI trained on them should be able to predict what you'll find important in ways no generic model could. The data said something more interesting. When different people highlight the same article, they agree far more than they differ. What stands out in a text mostly stands out to everyone; salience is largely shared, social rather than idiosyncratic. The individuality is real, but it doesn't live where we expected. It lives in *selection*: which documents you choose to engage with in the first place, which topics you return to, what you decide is worth your attention at all. And that selection behavior turns out to be remarkably stable over time, less like a mood and more like a trait. In other words: within a document, we read like a crowd. Across documents, we read like ourselves. Finding this meant breaking some of our own assumptions, including ones we had been excited about. An early version of one analysis seemed to show individual highlighting styles beating the crowd; our own audit found bugs and leakage in that result, and we retracted and rebuilt the work before publishing. The honest version of the paper was different from the one we had hoped to write, and it was stronger for it. ## A Natural Experiment in AEO We also turned the research lens on ourselves. The shift from search engines to answer engines, the one that forced the strategy change in Chapter 6, is exactly the kind of event researchers call a natural experiment. We were living inside it, with our own traffic and citation data as the laboratory. So we studied the transition rigorously and published that analysis too. There was something satisfyingly recursive about it: the growth strategy itself became open knowledge. The same way we once turned user interviews into case studies, we turned a platform shift into a paper anyone can read, check, and build on. ## Open by Default Every paper went out with a public repository. This was Chapter 5's open-source instinct carried to its conclusion: we had open-sourced tools, and now we were open-sourcing findings. The reasons are the same ones that made open-sourcing our AI tools work. Transparency builds trust, and trust compounds, a principle we'll come back to in the next chapter. Researchers who can verify your work become advocates for it. And in an era when AI systems increasingly decide which sources to lean on, a track record of verifiable, honestly reported research is the deepest trust signal we know how to send. There's also a discipline benefit we didn't fully anticipate. Knowing the work will be public, with the analysis open to inspection, forces a level of rigor that internal dashboards never demand. Publishing made us more honest with ourselves about what our data does and doesn't show. ## What Founders Can Take From This A few transferable lessons, for anyone sitting on product data and wondering. Your product data probably contains publishable insight. Not engagement metrics, which interest no one outside your boardroom, but genuine questions about human behavior that only your vantage point can answer. We could study how people highlight because we're where people highlight. Whatever your product is, you're the world's best-positioned observer of something. Rigor is the price of admission, and it's higher than content marketing. Be prepared to question your favorite hypothesis hardest, to have your best finding dissolve under audit, and to publish the honest result instead of the exciting one. We found that out firsthand. The retracted-and-rebuilt paper taught us more than a smooth success would have. And the payoff is unlike other channels. A viral feature spikes and decays. A research finding, once cited, keeps being cited; it becomes part of how a field talks about a topic. It's the compound effect again, operating on the longest time horizon we've found yet. For a company whose founding question was how knowledge outlives the person who found it, publishing research isn't a detour from the mission. It might be the most direct expression of it we've shipped. --- # Chapter 8: Principles for Sustainable Growth Throughout Glasp's journey from zero to three million users, we developed a set of principles that guided our decisions and shaped our approach to growth. These weren't abstract ideals. They were practical frameworks that helped us navigate challenges, capitalize on opportunities, and build a sustainable product in a rapidly changing environment. This chapter distills those principles, explaining how they influenced our decision-making and how they might apply to other founders and teams facing similar challenges. ## Long-Term Thinking with Short-Term Opportunism Perhaps our most fundamental principle was balancing long-term vision with short-term opportunism. We described this as "AND thinking" rather than "OR thinking." Long-term thinking alone leads to missed opportunities; pure opportunism leads to distraction and dilution. The magic happens when you can pursue immediate opportunities that align with your long-term vision. This principle guided many of our key decisions: - When AI tools emerged, we quickly built extensions that drove immediate growth (opportunism) while ensuring they connected to our core knowledge-sharing mission (long-term thinking). - We invested heavily in SEO content that wouldn't yield results for months (long-term thinking) while simultaneously pursuing viral moments that could drive immediate user acquisition (opportunism). - We maintained our focus on creating an open knowledge platform (long-term thinking) while adapting to evolving user needs and technology trends (opportunism). The practical application requires asking two questions about any potential initiative: 1. "Does this serve our long-term vision, even if indirectly?" 2. "Can we execute this quickly enough to capture immediate value?" When both answers are "yes," you've found the sweet spot where long-term thinking and opportunism converge. ## Persistence: The Ultimate Growth Hack During our journey, we encountered many founders with brilliant ideas who simply gave up too soon. That observation led to one of our core beliefs: persistence itself is the most powerful growth hack. Growing a product from zero to meaningful scale rarely happens quickly. The "overnight success" stories celebrated in tech media typically gloss over years of steady work before the breakthrough moment. For Glasp, persistence looked like: - Conducting hundreds of user interviews when we had only a handful of active users - Creating SEO content month after month before seeing significant results - Maintaining our mission focus despite the temptation to pivot to more immediately lucrative opportunities - Working through technical challenges and setbacks without becoming discouraged We came to see persistence not as stubbornness but as a strategic advantage. In a world where most competitors eventually give up, simply continuing to improve your product and serve your users gives you an edge. This doesn't mean blindly pursuing a failing strategy. Persistence should be coupled with adaptation and learning. We often changed tactics based on feedback and results, but we kept the core mission and kept pushing forward even when progress seemed slow. ## Resource Efficiency: Doing More with Less As a small team without significant funding, we had to be extremely efficient with our resources, particularly our time and attention. This constraint became a strength, forcing us to develop systems that maximized our impact. ### Content multiplication Rather than creating separate content for different platforms, we developed a "create once, publish everywhere" approach. A single Glasp Talk interview, for example, would become: - A YouTube video - A podcast episode - A blog post - Social media snippets - Newsletter content - SEO-optimized articles in multiple languages This let us maintain a robust content operation despite limited resources, with consistency across channels and formats for every kind of audience. ### Automation and AI As covered in Chapter 4, we leveraged AI to automate parts of our content creation and curation. This wasn't about replacing human judgment but amplifying it. Our system could generate a first draft of an article from a YouTube video, which we would then review and refine. We could produce ten times the content we could have created manually while holding the quality bar. ### Strategic outsourcing to the community Instead of building a large team, we involved our community where they could add unique value. User translations, case study interviews, and feature testing were all areas where community members contributed willingly and produced better results than we could have alone. This wasn't exploitation. It was collaboration. Community members participated because they got value from the process, whether through recognition, learning, or the satisfaction of contributing to a product they used daily. Resource efficiency goes beyond doing more with less. It's about identifying the highest-leverage activities, focusing your limited resources there, and finding creative ways to cover everything else. ## Community-Driven Development We built Glasp with our community, not just for them. This influenced every part of our product process, from ideation to iteration. ### Continuous user interviews Even after scaling to hundreds of thousands of users, we kept doing regular user interviews. These weren't just feedback sessions. They were opportunities to deeply understand how people used Glasp in their workflows, and they kept revealing unexpected use cases: educators collecting research for course materials, venture capitalists tracking industry trends, writers organizing ideas for books. ### Public roadmap and feedback loops We maintained a public roadmap where users could see upcoming features, vote on priorities, and suggest ideas. The transparency built trust, and the feedback loop caught issues and opportunities before we invested serious development time. ### Beta testing with power users Before releasing major features, we invited our most engaged users to beta test. This caught bugs early, gave our most passionate users early access that strengthened their connection to Glasp, and created a group who could help others adapt to new features. Users who participated in shaping Glasp became its most passionate advocates, driving organic growth through word of mouth. ## Mission Alignment: The North Star Throughout our growth journey, we maintained a clear mission: to create an open knowledge platform where people share what they learn and build on each other's insights. This mission served as our North Star for evaluating opportunities and making hard decisions. When considering new features, partnerships, or growth initiatives, we always asked: "Does this advance our mission of open knowledge sharing?" This simple question kept us from pursuing directions that might drive short-term growth but dilute our purpose. For example, we were approached about gamification elements that might have boosted engagement metrics but would have incentivized quantity over quality in knowledge sharing. We declined. Mission focus also helped us attract and retain users who shared our values. Rather than trying to appeal to everyone, we built a product that deeply resonated with people who cared about learning, sharing knowledge, and leaving a lasting impact through their ideas. The power of mission alignment is internal consistency. Every feature, communication, and decision reflects the same core values, creating a coherent experience users can connect with at a level deeper than utility. ## The Compound Effect: Small Actions, Big Results The final principle was an appreciation for the compound effect: small, consistent actions accumulating into remarkable results. ### SEO as a compound investment A single article might not drive significant traffic immediately, but hundreds of articles accumulating authority over years create a sustainable acquisition channel. After three years of consistent content creation, our organic search traffic brought tens of thousands of new users monthly, far more than we could have afforded to buy. ### Community trust as compound interest Every positive interaction with a user, whether a helpful support response, a thoughtful feature, or a valuable piece of content, deposited a small amount of trust. Over thousands of interactions, those deposits became a reservoir of goodwill. When we faced technical issues or made mistakes, our community was patient and supportive rather than quick to leave, because the trust was already banked. ### Product improvement cycles We preferred continuous, incremental improvement over infrequent overhauls. Each small enhancement might not transform the experience, but hundreds of them compounded into a product that felt increasingly polished and valuable. The same logic applied to growth metrics. A 5 percent weekly growth rate seems modest next to viral spikes, but it compounds to nearly 13x over a year, and it's far more sustainable. ## Putting It All Together These principles formed an integrated framework: 1. **Long-term thinking with short-term opportunism** kept us mission-focused while capitalizing on new trends and technologies. 2. **Persistence** kept us moving through challenges and slow periods, accumulating advantages as competitors gave up. 3. **Resource efficiency** let us accomplish more than our team size suggested possible. 4. **Community-driven development** ensured we built features people actually wanted, with shared ownership that drove advocacy. 5. **Mission alignment** gave us direction and attracted users who resonated with our vision. 6. **The compound effect** gave us the patience to invest in strategies that wouldn't pay off immediately but would create durable growth. Together, they produced a growth approach that didn't depend on massive funding, growth hacking shortcuts, or unsustainable tactics. It was built on creating genuine value, building authentic relationships, and letting those advantages compound over time. The two chapters before this one, on the answer-engine era and on publishing research, are these same principles applied to a new landscape. The technologies changed; the framework didn't. As we look to the future, that's the part we expect to stay constant. --- # Chapter 9: The Journey Continues When we started Glasp in September 2020, we couldn't have predicted the path that would take us from zero to three million users. We didn't anticipate the AI revolution that would transform our product, the global community that would emerge around our mission, or the countless ways users would integrate Glasp into their knowledge workflows. We certainly didn't anticipate that, a few years in, the search engines we had so carefully optimized for would start being replaced by answer engines, or that we'd respond by publishing research papers. What we did know was our mission: to create an open knowledge platform where people share what they learn and build on each other's insights. That mission has remained our guiding light, even as our product, team, and community have evolved. Looking back at the journey, several lessons stand out. ## The Power of Authentic Connection From those first several hundred onboarding calls to our ongoing Glasp Talk interviews, authentic human connection has been at the center of our growth strategy. In a digital landscape increasingly dominated by algorithms and automation, genuine relationships create differentiation and loyalty that can't be easily replicated. For founders building new products, this suggests that time spent deeply understanding and connecting with early users isn't just nice to have. It's a strategic investment that shapes everything that follows. ## Patient Capital Beats Fast Money By focusing on organic growth channels and sustainable user acquisition, we built a foundation that doesn't depend on continuous cash infusion. This approach was born from necessity, since we didn't have significant funding, but it became a strategic advantage. The lesson isn't that funding is bad. It's that building growth mechanisms that don't rely on paid acquisition creates resilience and independence. Patient capital, whether your own time or investors who share your long-term vision, lets you build something enduring rather than chasing short-term metrics. ## Technology Trends Are Opportunities, Not Threats Throughout our journey, we've lived through transformative technological shifts: the rise of generative AI, then the shift from search engines to answer engines. Rather than treating these changes as threats to our model, we embraced them as opportunities to extend our core value proposition. This adaptive approach let us capitalize on the AI revolution while keeping our identity as a knowledge-sharing platform. By asking how each new technology could serve the mission rather than distract from it, we turned potential disruption into acceleration. We expect to have to do this again, and we'd rather be early than comfortable. ## Mission Matters More Than Metrics Although this story has discussed user numbers and growth strategies at length, our success has never been defined primarily by metrics. We measure our impact by how effectively we're advancing our mission of open knowledge sharing. That focus attracts users who share our values, guides our product decisions, and creates a sense of purpose that sustains us through challenges. In a business landscape often obsessed with growth at all costs, having a clear "why" beyond the numbers provides both direction and meaning. ## The Future of Glasp As we look ahead, we remain committed to the mission while continuing to evolve the product and community. Our vision extends beyond the three million users we've reached so far, to a world where knowledge flows more freely between individuals, across generations, and beyond traditional barriers. The methods will keep changing. AI will keep transforming how we create, consume, and share knowledge. Increasingly, the "reader" of what we publish is as likely to be an AI assistant as a person, and we intend to be a source those assistants trust and cite. New platforms and formats will emerge. User needs will evolve. Through all of it, our principles stay constant: creating authentic connections, building sustainable growth, embracing new technologies in service of the mission, and prioritizing long-term impact over short-term gains. We hope this story of going from zero to three million users offers insights you can apply to your own projects, whether you're building a product, growing a community, or simply trying to share knowledge more effectively. The path won't be identical. Every product and team faces unique challenges and opportunities. But authentic connection, patient growth, technological adaptation, and mission focus can guide you through whatever path emerges. Thank you for joining us on this journey. The story of Glasp continues to unfold, and we invite you to be part of writing its next chapters. ## Timeline of Key Milestones **September 2020**: First lines of code written for Glasp **October 2020**: First users sign up through personal invitations **January 2021**: Reached 100 users through founder-friend distribution **June 2021**: Shifted focus from product managers to writers as target audience **August 2021**: YouTube sponsorship with Aurelius (300K subscribers) **September 2021**: First Product Hunt launch **November 2021**: Reached 1,000 users **Early 2022**: Began focusing on SEO and content marketing **Mid 2022**: Created DALL-E Wordle (DALLE-dle), featured in PC Gamer **November 2022**: ChatGPT released; launched Chrome extension within days **December 2022**: Created YouTube Summary with ChatGPT **January 2023**: YouTube Summary with ChatGPT went viral, featured by major publications **March 2023**: Launched Digital Clones feature **June 2023**: Reached 1 million total users across all products **September 2023**: Newsletter subscribers surpassed 250,000 **Early 2024**: Reached 3 million users across the Glasp ecosystem **Early 2026**: Launched Deep Dive, a library of long-form guides translated into 7 languages **2026**: Shipped AEO infrastructure: llms.txt, structured data, and a remote MCP connector so AI assistants can work with Glasp **2026**: Published a series of research papers on arXiv based on Glasp's highlighting data **June 2026**: Published this story at glasp.co/story