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Building AI x learning products. Harvard’17. Side project: tldw.us YouTube: youtube.com/@ZaraZhangg Substack: zarazhang.substack.com
The Innovator
Zara Zhang is a forward-thinking tech pioneer who bridges AI and education, constantly challenging traditional learning and career paradigms. She leverages her Harvard background to build cutting-edge products that make knowledge more accessible and impactful. Zara’s social presence is a blend of insightful cultural commentary, product showcases, and empowering guidance on mastering AI’s evolving landscape.
Top users who interacted with Zara Zhang over the last 14 days
Head of Product Quality → AI Builder ⚙️ Building a better job search with AI 💻 Skiing, travel & freedom 🌍⛷️ Documenting my journey ⚡
everyone wants growth tactics. nobody wants to know why people buy. weird. startup growth without the fairytales.
3x head of GTM @YC/HF0 DevRel l vibe coding
🧑💼founder｜⌚️entrepreneur |🎤public speaker|✈️IP address常变｜生意人就是不断生出主意的人
Civil Engineer in water utility sector; Love God & love people. Student of financial markets and macroeconomics. Demographics is fascinating.
AEO & SEO | Entrepreneur | Notion Enthusiast | 💡Lean Startup & MVP Promoter | Finance & CS Double Major
AI Educator. Web Developer, Web Designer, #AIforGood Advocate.
Paid media & growth strategy | 10 yrs scaling @Airwallex ($1B ARR) | Ex-Google, Fanatics | $100M+ revenue driven | SF 🚀
Take control of your destiny and challenge the limits of growth.
The backend for AI coding 🌐 insforge.dev ⭐️ github.com/InsForge/InsFo… 💬 discord.com/invite/DvBtaEc…
AI Voice Generator for Creators. An easy-to-use tool to create podcasts, voiceovers, reels, and YouTube videos.
Building AI productivity agents at Bytedance (飞书多维表格 @Larksuite) ex-WPS AI PM ｜AI × Product × Systems｜公众号「下维 Next Dimension」
Crypto Clown
Founder | youngest startup government contract winner in germany | Software Engineer at Spherecast (YC) | I am new here, follow me
24 yr old learning and building AI in public | Ex- cofounder | Exploring Growth/Marketing in AI | prev Maths @UW, MSCS @Northeastern
unpack
Prompt Engineer | Computer Science | ASU | Software Engineer | Momentum Investor | Entropreneur |
I have generated over $1,000,000 in sales online from selling tshirts! Now i show you exactly how i did it 🤓
Moonshot AI (Kimi) Lead supporting product engineering and MLE teams Serial Entrepreneur Facebook AI Research Reinforcement Learning team
I read biographies of great entrepreneurs, simplify AI & personal growth, and share practical lessons you can use to grow in work + life. Support ↓
Zara shapes her algorithm like a black belt hacker, but considering she ditched social media for eight years, you have to wonder if she treats Twitter like a vintage artifact—dusting it off only to remind us all how much better she’s been without it.
Building TLDW, a pioneering AI-powered tool that distills hours of video content into game-changing 5-minute insights, showcasing her knack for solving the right problems in education technology.
Zara’s life purpose is to revolutionize how people learn and adapt in a world transformed by AI, dismantling outdated education models and creating tools that unlock deeper understanding and real-world impact for learners everywhere.
She believes in self-directed learning over credentialism, the power of technology to democratize education, and that intentional digital engagement can reshape social media into a force for meaningful growth rather than mere entertainment.
Zara’s biggest strengths include visionary thinking, practical innovation, and an uncanny ability to synthesize complex AI concepts into tangible learning solutions that resonate with forward-looking communities.
Her laser focus on innovation and deep knowledge can sometimes make her social feed feel niche or inaccessible to a broader, less tech-savvy audience, which might limit mass appeal without tailored outreach.
To grow her audience on X, Zara should blend her high-level insights with more accessible, bite-sized content that invites broader participation. Hosting regular Twitter Spaces or AMA sessions on AI learning hacks could humanize her brand and turn passive followers into an engaged community.
Fun fact: Despite stepping away from social media for eight years, Zara returned with a laser focus on molding her algorithm into a personalized AI learning hub, proving even the algorithm can be hacked with enough intention and persistence.
Top tweets of Zara Zhang
Sometimes a video is so high-signal, you feel like taking notes all the time So we make it easy in TLDW: select any lines in the transcript, and convert them into notes with one click (or get AI to explain it if you don't get it) @karpathy 's interview is one of those videos where you'd want to do this
Introducing TLDW: a better way to consume long YouTube videos I’m excited to launch a side project I’ve been building with two friends: TLDW (Too long; didn’t watch), a tool that helps people learn from long YouTube videos. TLDW was inspired by my own pain points when learning from YouTube. Over the past year, I’ve noticed a shift in my content consumption habits, where I’ve been spending more and more hours watching long YouTube videos to learn: video podcasts, founder interviews, lectures, tutorials... Many of them are more than 1-hour long and packed with high-value information. I also started to listen to audio podcasts less and started watching more of the video versions on YouTube. Because: 1. Many of them are very dense in information, and I get easily distracted when listening to audio only. I can focus better when watching the video version. 2. Many of these shows contain visual information like product demos, screen shares, and slides. Also, even watching the speaker’s dynamics and body language can help me digest the content better. Apparently, many other people feel the same, because YouTube is now the biggest podcasting service in the US. Yep, YouTube, not Apple Podcasts or Spotify. When I recommended my followers do the same, I noticed that many people didn’t have the attention span to sit through these hour-long videos. Instead, they tend to toss the link to an AI tool (say Gemini or NotebookLM) and get it to generate a text summary. I don’t like text summaries. 1. Converting video (a high-bandwidth format) into text (a low-bandwidth format) is very problematic. You lose all the rich visual information (demos, slides, speakers’ emotional cues). You also lose lots of details that made this video worth consuming in the first place: the anecdote/example that hits you in the gut, the turn of phrase that makes a line memorable... Many times, it’s not the gist of the video that we remember, but the little details. 2. Text summaries are generic (unless you put in an extremely detailed prompt specifying what you’re looking for, which 99% of people don’t do). Your summary and my summary will look the same. But given the same hour-long video, we will obviously care about different things. An AI researcher watching a talk by Sam Altman might pay attention to parts about model training, whereas a product manager might be more interested in how models are being productized. Summaries should be personalized. So here’s the dilemma: How do we allow people to consume long-form videos efficiently, while also preserving the fidelity of the original content AND making it a personalized experience? We felt like the answer lies in this new format: highlight reels. In the past, AI has mostly been used for “compression”: turning a 1-hour video into a 1-paragraph summary. But what if we use it for “filtering” or “curation” instead? Pick out the 5 minutes that I should pay attention to, but just give me the original clip without watering it down. This is what gave rise to TLDW’s key feature: personalized highlight reels. We run the video transcript by an LLM which will identify the most high-signal parts of a video. These “highlight reels” are then displayed using different colors on the progress bar, and clicking on each will take you directly to the corresponding timestamp. And this can be personalized, because different viewers care about different things: Say you’re someone working in education, you could type in “future of education”, and the model will highlight all the parts that discussed education in the video. We believe “personalized highlight reels” are a better solution than “generic text summary”. Since launch, many users said they really like this user interface, and that this is the tool they’ve been waiting for. In addition, we also have a few features that addressed my own pain points when trying to watch technical videos to learn AI: 1. When you come across a term/jargon you don’t understand, you can select it in the transcript and click “Explain” - the AI will explain it for you in CONTEXT. The key here is “in context”. Before, I used to manually type out these terms in ChatGPT, but ChatGPT didn’t have the context of what I was watching. The meaning of words/phrases changes depending on the context. Because our AI has the whole video transcript in its context window, it’s able to provide a context-specific explanation in one click. 2. When you come across a memorable line, you can select it in the transcript and click “Take notes”, and this will automatically be added to your personal notebook. 3. You can chat with the video transcript. Ask questions such as “what are the juiciest quotes” or “how does the speaker feel about [insert topic]”. 4. All your past videos and notes are saved in one central place, so this could become your personal learning hub. Things we’re planning to add in the future: 1. Being able to share quotes/clips easily with other people/on social media, so that you can learn in public 2. Multilingual support and adding translation features 3. Enhancing the personalization: the AI could learn about your taste and interests and recommend reels based on those I worked on TLDW on nights and weekends with 2 amazing partners: @zhangsamuel12 (developer) and @YanYiqi73877 (designer). This was not our full-time job; we’ve been working on it out of genuine passion for the problem space and a desire to get our hands dirty building in AI. We also open-sourced the code (link in comment). The product is still very early and has a lot of room for improvement, so would appreciate your feedback through emailing me (zara.r.zhang@gmail.com) or tagging me on X (zarazhangrui). Try TLDW here: tldw.us or see a pre-generated example here: tldw.us/analyze/IcbuTT…
I learned more about AI from the Internet than from Harvard. I've compiled the specific resources I've found useful into a website. And I'm sharing it for FREE: - YouTube videos & channels - Podcasts - People to follow on X - Newsletters I read every day - AI products that I like Happy learning! zara.faces.site/ai
“In reality, workshops (and how-to books) mostly give you a boost of inspirational energy and the illusion that you’ve learned something. The only way to really learn is by writing.” (In the context of screenwriting) Same thing can be said about watching video podcasts & talks today vs getting your hands dirty building something. Love these side notes by @jmechner in The Making of Prince of Persia @stripepress
Most engaged tweets of Zara Zhang
Introducing TLDW: a better way to consume long YouTube videos I’m excited to launch a side project I’ve been building with two friends: TLDW (Too long; didn’t watch), a tool that helps people learn from long YouTube videos. TLDW was inspired by my own pain points when learning from YouTube. Over the past year, I’ve noticed a shift in my content consumption habits, where I’ve been spending more and more hours watching long YouTube videos to learn: video podcasts, founder interviews, lectures, tutorials... Many of them are more than 1-hour long and packed with high-value information. I also started to listen to audio podcasts less and started watching more of the video versions on YouTube. Because: 1. Many of them are very dense in information, and I get easily distracted when listening to audio only. I can focus better when watching the video version. 2. Many of these shows contain visual information like product demos, screen shares, and slides. Also, even watching the speaker’s dynamics and body language can help me digest the content better. Apparently, many other people feel the same, because YouTube is now the biggest podcasting service in the US. Yep, YouTube, not Apple Podcasts or Spotify. When I recommended my followers do the same, I noticed that many people didn’t have the attention span to sit through these hour-long videos. Instead, they tend to toss the link to an AI tool (say Gemini or NotebookLM) and get it to generate a text summary. I don’t like text summaries. 1. Converting video (a high-bandwidth format) into text (a low-bandwidth format) is very problematic. You lose all the rich visual information (demos, slides, speakers’ emotional cues). You also lose lots of details that made this video worth consuming in the first place: the anecdote/example that hits you in the gut, the turn of phrase that makes a line memorable... Many times, it’s not the gist of the video that we remember, but the little details. 2. Text summaries are generic (unless you put in an extremely detailed prompt specifying what you’re looking for, which 99% of people don’t do). Your summary and my summary will look the same. But given the same hour-long video, we will obviously care about different things. An AI researcher watching a talk by Sam Altman might pay attention to parts about model training, whereas a product manager might be more interested in how models are being productized. Summaries should be personalized. So here’s the dilemma: How do we allow people to consume long-form videos efficiently, while also preserving the fidelity of the original content AND making it a personalized experience? We felt like the answer lies in this new format: highlight reels. In the past, AI has mostly been used for “compression”: turning a 1-hour video into a 1-paragraph summary. But what if we use it for “filtering” or “curation” instead? Pick out the 5 minutes that I should pay attention to, but just give me the original clip without watering it down. This is what gave rise to TLDW’s key feature: personalized highlight reels. We run the video transcript by an LLM which will identify the most high-signal parts of a video. These “highlight reels” are then displayed using different colors on the progress bar, and clicking on each will take you directly to the corresponding timestamp. And this can be personalized, because different viewers care about different things: Say you’re someone working in education, you could type in “future of education”, and the model will highlight all the parts that discussed education in the video. We believe “personalized highlight reels” are a better solution than “generic text summary”. Since launch, many users said they really like this user interface, and that this is the tool they’ve been waiting for. In addition, we also have a few features that addressed my own pain points when trying to watch technical videos to learn AI: 1. When you come across a term/jargon you don’t understand, you can select it in the transcript and click “Explain” - the AI will explain it for you in CONTEXT. The key here is “in context”. Before, I used to manually type out these terms in ChatGPT, but ChatGPT didn’t have the context of what I was watching. The meaning of words/phrases changes depending on the context. Because our AI has the whole video transcript in its context window, it’s able to provide a context-specific explanation in one click. 2. When you come across a memorable line, you can select it in the transcript and click “Take notes”, and this will automatically be added to your personal notebook. 3. You can chat with the video transcript. Ask questions such as “what are the juiciest quotes” or “how does the speaker feel about [insert topic]”. 4. All your past videos and notes are saved in one central place, so this could become your personal learning hub. Things we’re planning to add in the future: 1. Being able to share quotes/clips easily with other people/on social media, so that you can learn in public 2. Multilingual support and adding translation features 3. Enhancing the personalization: the AI could learn about your taste and interests and recommend reels based on those I worked on TLDW on nights and weekends with 2 amazing partners: @zhangsamuel12 (developer) and @YanYiqi73877 (designer). This was not our full-time job; we’ve been working on it out of genuine passion for the problem space and a desire to get our hands dirty building in AI. We also open-sourced the code (link in comment). The product is still very early and has a lot of room for improvement, so would appreciate your feedback through emailing me (zara.r.zhang@gmail.com) or tagging me on X (zarazhangrui). Try TLDW here: tldw.us or see a pre-generated example here: tldw.us/analyze/IcbuTT…
Sometimes a video is so high-signal, you feel like taking notes all the time So we make it easy in TLDW: select any lines in the transcript, and convert them into notes with one click (or get AI to explain it if you don't get it) @karpathy 's interview is one of those videos where you'd want to do this
I learned more about AI from the Internet than from Harvard. I've compiled the specific resources I've found useful into a website. And I'm sharing it for FREE: - YouTube videos & channels - Podcasts - People to follow on X - Newsletters I read every day - AI products that I like Happy learning! zara.faces.site/ai
People with Innovator archetype
post-training @reflection_ai. prev @ndea and co-founded beatgig.com. yc w19.
Web3 Artist ✦ Content Creator Jun mod: @SaharaLabsAI | Ambassador: @awenetwork_ai Maxi: @SentientAGI
Film director | AI Consultant | Partner with irrational.tv Paris | Sharing practical ways to use AI for you and your business. All views are my own.
Building: easyrunner.xyz and @docqai. ex-@truelayer. ex-@hudl. Fullstack generalist, master of none. Product & Engineering. #GenAI #RAG #AIAgents #Infra.
software engineer. crafting impactful things to open source world | building overwrite: mnismt.com/overwrite | changelogs: changelogs.directory
🎯AI玩家
0x0.5x engineer | robotics | design | biology | systems | built beapolymath.app |
building things and self⁉️
柬埔寨第四年大历练中。对区块链有点感兴趣。PVE & PVP 业余选手。保持精进兄弟们团结起来。相信okb。
perpetual delusional optimist / vibe trading arc
@webflow ✦ views and thoughts are my own.
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