Pranav Badami

Notion vs Glean reminds me a lot of Tesla vs Waymo... Just like I think Tesla is going to solve the 'software' problem of autonomous vehicles before Waywmo solves the 'hardware' problem... I think that Notion is going to solve 'enterprise knowledge search' before Glean solves the problem of document and knowledge creation... Why? A couple reasons: 1) Just like Tesla, Notion has a huge advantage when it comes to the amount of underlying data and documents to train on... They already have 100M+ users, and likely 10x that in terms of the number of documents, files, etc. in team's workspaces. 2) It's very hard to change people's behaviour re: where/how they create 'work'. It's why a lot of companies have come and gone in that category... As exciting as Glean's AI writing assistants might seem, most people are just fine (or even prefer) a good old fashioned editor/writer. I could be way off here, but this will be an intersting one to follow. Thoughts? Where am I getting it wrong? #ai #enterprise #knowledge #management #notion #glean

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The newest issue of The Pragmatic Engineer found a surprise uptick in eng hiring in the typically slow summer season - I'm curious to see how the macro environment impacts this uptick as we head into the fall, but I remain hopeful. I asked Gemini to give me the tldr of the article to share with my team (sorry, Gergely Orosz) and found it missed one of the most interesting pieces of the article. Gemini's highlights - Unexpected surge: Tech recruitment has seen an unusual spike in June and July, contrary to typical trends. Increased demand: Startups, especially AI-focused ones, are driving the hiring uptick. Global phenomenon: This trend isn't just limited to the US; Europe is also experiencing increased recruitment activity. Reasons for hiring: Companies are backfilling positions, investing in growth due to improved financials, and responding to increased VC funding. Challenges remain: While the job market is improving, finding qualified candidates and offering competitive compensation remains difficult for many companies. What I found most interesting - The nature of the backfills: the article finds that a lot of new headcount are actually backfills of folks that were "over-slashed" during rounds of layoffs. Not entirely surprising with the "trim the fat" and "rebuild lean" mentality, but interesting nonetheless. Either way, the uptick is encouraging (and don't always rely on Gemini's tldrs). #hiring #startups #VCbacked #softwareengineering

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🚨🚨 🚨 Unlocking Innovation: The Power of the Adjacent Possible Innovation programs can stall when the team tries to ideate way beyond their collective perspective and frame of reference. Like a software engineer brainstorming genetic modification of mycelia, or a senior executive ideating process improvements which they haven't been participated in for decades. It's challenging, exhausting, and ultimately self-defeating. Enter the concept of the "Adjacent Possible" - a game-changer for innovation. What is it? The Adjacent Possible, coined by Stuart Kauffman, represents the realm of new ideas within reach based on our current knowledge, resources, and capabilities. Why it matters: ➡️ Realistic Innovation: it focuses on achievable advancements, not far-fetched concepts. ➡️ Incremental Progress: each innovation opens doors to new possibilities. How to leverage it: • Constantly explore the boundaries of your adjacent possible. What's in your line of sight is what you know best. • Combine existing ideas in novel ways. Even small perturbations from status quo can generate large innovation leaps. • Stay curious about developments in adjacent industries. Cross-domain patterns create fresh sources of ideas, while also expanding the adjacent possible. Most of all, it takes the 'genius' pressure off the team. No one knows everything, but each one of us knows a lot about something, and we can all drive plenty of innovation potential by focusing on the spaces we know best. Are you exploring your Adjacent Possible? Share your thoughts below! 👇 #Innovation #innovationsystems #AdjacentPossible

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AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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Non-Engineering Roles at Early-Stage Startups Offering $120K+ Base Salary with Meaningful Bonus and Equity: Chief of Staff @ Milo (Consumer), Remote Biz Ops Lead @ Fractal Agriculture (FinTech), Remote; Backed by Virta Ventures Chief of Staff @ CakeAI (AI SaaS), NY; Backed by Primary Venture Partners Demand Generation Specialist @ Rootly (Consumer), Remote; Backed by YC, 8VC, Gradient Ventures Account Executive @ CommandBar (Enterprise SaaS), Remote; Backed by Soma Capital, YC, Insight Partners Product Marketing @ Slope (Enterprise), Remote; Backed by YC, Union Square Ventures, Liquid 2 Ventures Supply Planning Manager @ PROVEN Skincare (Consumer), Remote; Backed by YC, FJ Labs, Soma Capital, Social Capital Account Executive @ Accrue Savings (Consumer), NY; Backed by Ground Up Ventures, Tiger Global Chief of Staff @ UNIGRID Battery (Climate), CA; Backed by Union Square Ventures, LiquidMetal Ventures Job details and the full list (40+ opportunities) are in the comments below. If you're interested in non-tech jobs focused on specific industries like HardTech, HealthTech, Climate, etc., then DM me or let me know in the comments.

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NVIDIA's Jensen said "ChatGPT democratized computing, Llama2 democratized generative AI" ...and now Llama3 is the next level 🔥 It's fascinating to watch Meta's strategic moves. With Llama3, they prioritized training on a massive 15T token dataset to pack all into a lean 70B param model, instead of building a massive model. This allows Llama 3 to match trillion+ parameter models like GPT-4, but at 1/10th the compute, storage and inference costs! 💰 This technique was published by Google DeepMind a few years ago https://lnkd.in/gx7VU8aA Meta is not a dark horse in AI anymore. They might be the top dog. https://lnkd.in/gRRJYuxt #llama2 #llama3 #llm #chatgpt #gpt4 #ai #ml

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Success in deep tech, like any other startup, hinges on not running out of money It’s more pronounced in deep tech since business metrics won’t happen until after several funding rounds So founders need to convince investors and employees that whatever they are raising now will generate results (with ample buffer) that will entice investors to put in more money, even though there likely still won’t be a business that traditional investors can underwrite. Pure technical progress won’t cut it. It’s about turning armies of talent, customers, and partners into believers of the future you’re making possible Props to Becky Pferdehirt, PhD and Rajesh Swaminathan for a fantastic convo and Matt Caspari for hosting and moderating!

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Silicon Valley Slackers: Myth or Reality? We sat down with Menlo Ventures’ Deedy Das to discuss his viral tweet about underworked engineers earning $300K+ and the phenomenon’s broader implications. Mouse Jigglers & Ghost Engineers: Deedy shares wild stories of remote workers gaming the system, from "working" in Mexico for years to productivity software catching patterns of inactivity. Misaligned Incentives: Deedy argues that middle managers prioritize headcount over productivity, creating an environment where underperformance is overlooked. Measuring Productivity: Lines of code and git commits aren’t enough. Engineering productivity remains complex and difficult to quantify, so there’s no silver bullet. Viral Backlash: Deedy’s anecdotes sparked heated debates in tech, with some engineers admitting to coasting while others criticized him for "narking" on the culture. Should companies rethink how they measure and incentivize performance?

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A common mistake early-stage VCs make is confusing good decisions with good outcomes. Good outcomes don’t always mean good decisions—luck often masks flawed reasoning. Focus on process over outcome bias. Invest in strong decision-making frameworks, not just duplicating “wins.”

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Want a front-row seat to the frontier of tech? We’ve got the role (or two) for you! We’re expanding our frontier-tech team at Blackbird by hiring a Frontier Tech Investments Associate and Foundry Fellows! Got questions? We've got answers... 1️⃣ What are the roles? 🧪 Associate = a full-time VC investment gig in our Blackbird Investments team, working directly with me. We’re looking for someone with a science and/or engineering background and more curiosity than they can handle. You’ll grow your own investment brand and practice, support our portfolio founders, and will help build Foundry, our early-stage frontier-tech accelerator. ✨ Foundry Fellow = a casual/contract gig in our Blackbird Investments team, ~15h per week for 3 months. The Fellowship is ideal for PhD students and ECRs who want to learn more about startups and VC. You’ll go deep on emerging areas relevant to your expertise (or curiosity!), get a front-row seat to groundbreaking companies in those areas, build out your non-academic network, and develop a solid writing practice. 2️⃣ Why are you hiring? We love frontier tech, and we’re ready to grow our team. 3️⃣ Wow, it’s so great that you’re starting to look at deep tech! Look, we get it: we don’t make a lot of noise about our frontier tech investing. Buuuut we’ve been deep-tech investors since we backed Tim Kentley-Klay to found Zoox back in 2014—we’ve been on incredible journeys with PsiQuantum (building the world's first utility-scale quantum computer right here in Australia!), Inventia Life Science (transforming drug discovery with high-fidelity cell models), Remedy Robotics (surgical robots for remote endovascular procedures), Opto Biosystems (minimally-invasive neural implants to treat cancer), and more. We believe that frontier technologies, and great frontier-tech investing, will be part of the solutions to the greatest problems humanity faces today. 4️⃣ When do applications close? May 31st at 11:59pm AEST. 5️⃣ I have more questions! I’m sure you do! Clare Birch and I are hosting an AMA to answer any and all questions about these roles. Want to know what a week in the life of our team looks like? What’s keeping us up at night? What our ideal candidate looks like? Come along and find out - registration link in the comments 👇 Apply for these roles: Associate - https://lnkd.in/gCfj4EUJ Foundry Fellowships - https://lnkd.in/gj6ATZVZ If you know anyone that we should meet, send me their details! Cameron Elise Ben Andrew Robin Joseph Adelaide James Olivia Lucinda Raghav Jesse Christie Mohamed Tom Amee Pablo Haya Loong Hon Joshua Benjamin Megan Harry Denzil Matthew Diana Daniel Tom Deanna Justin Amar Lilly Stone Thomas

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What I've seen over the years is, early stage companies rarely grow beyond their founders’ capabilities; or at least, companies model after their founders really closely. If the founder is unfocused, chances are the whole company is unfocused. If the founder is incapable of making decisions, the company is likely to have meetings after meetings without clear conclusions. If the founder doesn’t put in 110% of herself in the company, it’s hard to expect anyone else at the company would. 1/ Having cofounders is advantageous in this regard, because no one is perfect and different cofounders can bring different skill sets and strengths 2/ Founders need to have good mentors 3/ Founders must set aside some time to constantly upgrade themselves and “sharpen the tooth”. 

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Check out my recent post on why President Trump is the forcing function for us to solve the “Missing Middle” and catch the industrial Tsunami of onshoring coming to the US!

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Waymo's market share is now equal to Lyft within SF. Incredible. Network effects is one of the best sources of defensibility. But it's proven to be not that important in ridesharing. When Waymo launched in August 2023, Uber and Lyft were at 66% and 34% share in SF. 15 months later in November 2024, Waymo is at 22% - the same as Lyft - with Uber at 55%. Note: stats from a partner at a16z. #ridesharing #Waymo #Lyft #Uber #a16z

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Kim Burgaard Rachel Perez Jay Leverett David Bellotti -- I'll be listening to this one for sure! Sergio H. Serge Madenian Episode Summary: The episode features an in-depth interview with Mike Krieger, the new chief product officer at AI company Anthropic, discussing his background, the decision to join Anthropic, the company's focus on responsible AI development, the challenges and opportunities in building AI products, and his vision for the future of AI technology and its applications. https://lnkd.in/guWW8cku

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I like this idea of "technical taste". It gets into where software engineering is as much creative art as it is science. Four great takeaways (IMHO) for software devs in this era in particular: 1. Aspiring engineers should cultivate a sense of curiosity, experiment with different tools and technologies, and embrace a mindset of continuous learning. 2. AI has the potential to streamline processes and enhance productivity for engineers, but it may also lead to disruptions in traditional software development workflows. 3. Developing technical taste and judgment is essential for making informed decisions about which technologies and approaches to pursue. 4. Collaboration and open-mindedness are key to leveraging the full potential of AI and staying ahead of technological advancements. I also really liked these two quotes from Sam Schillace: 1. "The right time to do something is when you have that feeling in the pit of your stomach that's like, 'oh, this is a great idea and it's going to suck to build because nothing's ready yet.'" 2. "Technical taste is like, 'how well have you consolidated that set of experiences and heuristics into judgment that you can apply accurately when you see new things?'" 3. "It may be the case that very small teams can do very large projects, or like we were talking about before, it may be the case we're just going to get really ambitious about what we try to do with the same size of teams, which is kind of where I would put my money." Great job on continuing to put out great episodes, Brett Berson and team First Round Capital! #ai #engineering #softwaredevelopment

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The reality of what generative AI is doing is opening up access to really capable AI and challenging companies on how they can leverage that. It’s saving people a huge amount of time compared to something they’ve been doing manually. And in my opinion, any time you can save this kind of time and effort, all of society lifts up. Think about this analogy: planting crops by hand to plowing by horseback to plowing by tractor… allowing for scale is a game-changer. Now that this access is being democratized, it’s making individuals a lot more impactful and scalable to have more output and throughput. But I think in time more will be expected of people. Right now the applications that AI is being implemented into are the lower hanging fruit, and now people can focus on the harder problems. 6 months from now… a year from now… it will be interesting to see the change Gen AI will have on every functional role.

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Did you know that YC founders get a secret weapon… and it’s not what you think. “Bookface” is YC’s internal social network. It was needed because YC had funded larger batches and the hardest part of a community is knowing who is in it and who you can trust and ask for help. On the platform, founders share real methods and advice that would break if it were shared widely It’s secret knowledge shared with a trust-first community - answering 80% of the questions a founder can have about building and selling a product, be it to clients, candidates or investors. Before the platform, if you had a B2B startup, you had to reach out cold to potential customers. Now there are over 1000 YC companies you can sell your service to and all of their contact information is in Bookface. As a result, YC alumni companies are often over 50% of your new sales during YC. It’s superpowers like this that make YC deals so attractive compared to the norm. You are investing in a founder with a 10x network already!

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What a week this has been for innovative companies in Seattle (first Smartsheet and now OctoAI). Today NVIDIA made public the news that they have acquired Madrona portfolio company OctoAI. Partnering with the founders since Day 1 (ok Day -1) has been one of the greatest experiences of my life. Luis Ceze, Jared Roesch, Tianqi Chen, Jason Knight, Thierry Moreau and Carlos Guestrin were all involved in the research and insights that helped create the TVM open source technology at the University of Washington computer science school and then the creation of OctoAI back in 2019 to drive commercial impact with this technology. From sorting out the terms of the original "pre-seed" round over a bottle of Caymus Vineyards wine to helping Amazon Web Services (AWS) understand the dynamics around the open source movement in Applied AI to learning our way in to product-market fit with the BEST inference optimization service available (OctoAI can help customers find their optimal fit of performance, customization, and cost), OctoAI has been the best! The company has helped set the table for AI-driven innovation for the years ahead and they will be a perfect compliment to the many capabilities at Nvidia. Luis, his leadership team, the board (including Carlos Guestrin Lip-Bu Tan and Mike Dauber) and so many "friends of OctoAI" know what a motivated, talented and authentic group of people are associated with this company. It is inspiring to see an acquisition at a total deal value of over $250 million in this highly dynamic and fast-moving phase of AI disruption. It is even more exciting to anticipate what will be possible with innovations powered by AI models and related technologies in the years ahead. Madrona has been investing in Applied AI for over a decade and we truly believe that we are just getting started! One of the hardest judgement calls as an investor and board member is to assess the benefits and risks of selling a company at a key inflection point in the journey. Nvidia made a compelling case that the impact for the OctoAI team and technology would be maximized within the market leader for AI infrastructure. I will be rooting every day that they all maximize this impact in the months and years ahead!

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