Startup Project

Author: Nataraj Sindam

  • #77 Learn It All Mindset with CEO Damon Lemby

    Damon Lemby, CEO of Learn It, a company that has trained over 1.9 million individuals, shares his journey from professional baseball to the world of education, offering insights on leadership, learning, and the future of work.

    The Power of the “Learn It All” Mindset

    Lemby argues that the key to success in today’s dynamic world is not being a “know-it-all,” but embracing a “learn it all” mindset. This means being humble, curious, and constantly seeking new knowledge. He emphasizes that this approach is crucial for navigating the rapid changes in the business world, especially with the rise of AI.

    Overcoming Imposter Syndrome: A Practical Framework

    Recognizing that imposter syndrome is a common struggle, Lemby outlines a three-step framework for overcoming it:

    Identify the Source:  Clearly define what you’re worried about.

    Purposeful Awfulizing:  Imagine the worst-case scenario and determine if you can handle it.

    Work Hard, Focus, & Let Go:  Put in the effort, practice, and release the need for perfection.

    Navigating AI and the Future of Work

    Lemby believes that while AI will significantly impact the workforce, those who adapt and learn to leverage it will thrive. He advises companies to empower their employees with access to AI tools and encourage them to explore these technologies.

    Building Trust and Elite Teams

    Lemby emphasizes that a company is not a family, but a team that needs to be constantly evolving. He encourages leaders to build high-performing teams, recognizing that sometimes this may involve letting go of individuals who have reached their capacity within the organization. He also underscores the importance of giving people the benefit of the doubt, acknowledging that building trust is essential for long-term success.

    Invest in Your Growth:

    Lemby encourages listeners to invest in their own development, read biographies of successful individuals, and constantly seek new knowledge. He also shares his own investment philosophy, focusing on seed-stage companies and traditional businesses with a strong leadership team and a solid market fit.

    Key Takeaways:

    • Embrace a “learn it all” mindset for success in a dynamic world.
    • Conquer imposter syndrome with a practical framework.
    • Leverage AI for growth and prepare for the future of work.
    • Build elite teams and trust your employees.
    • Invest in your own development and seek out new knowledge.

    This conversation with Damon Lemby offers valuable insights for entrepreneurs, leaders, and anyone seeking to navigate the evolving business landscape.

    —

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  • How Mighty Capital Defies the Odds of Technology Investing by Being Product-First

    In a world where venture capital success is often described as a game of chance, with a hit rate of one in 20 or even one in 30, Mighty Capital stands out. Founded by entrepreneur, product leader, & author SC Moatti, Mighty Capital has carved a unique path in the industry, focusing on a “product-first” approach and achieving a remarkable hit rate of one in five.

    On a recent episode of the Startup Project podcast, SC Moatti shared insights into her journey with host Nataraj SIndam, revealing the secrets behind her unconventional success.

    From Product Guru to VC Pioneer

    SC Moatti has a diverse background, ranging from a successful career in product management at companies like Meta and Nokia to founding her own companies and angel investing. Her passion for product excellence led her to establish “Products That Count,” a non-profit organization dedicated to fostering knowledge and best practices within the product management community. This platform has served as a valuable resource for Mighty Capital, providing valuable insights into emerging trends and identifying potential investments.

    The Product Mindset in Venture Capital

    Mighty Capital distinguishes itself by applying a product mindset to venture capital. This means looking beyond traditional metrics and focusing on the core elements of a successful product:

    • Team: They meticulously evaluate the team’s performance, board composition, and the CEO’s ability to be coached.
    • Traction: They seek companies with demonstrable revenue growth, analyzing revenue composition and customer references.
    • Market: They analyze the market, roadmap, and the company’s potential for growth.
    • Terms: They prioritize fair terms that foster a long-term partnership with entrepreneurs.

    This approach, combined with her deep understanding of the product landscape, and the unique network of Products That Count, has enabled Mighty Capital to invest in companies like Amplitude, Grok, Airbnb, and Digital Ocean, demonstrating a knack for identifying winners before they become mainstream.

    Beyond the Numbers: Building a Better Board

    SC Moatti also highlights the importance of board governance in early-stage companies. She teaches a course on the subject at Stanford’s Executive Program, emphasizing the critical role of board members in maximizing shareholder value through effective use of financial and human resources. She believes that effective board engagement transcends the traditional power dynamics, focusing instead on collaborative partnerships with founders.

    The Future of Product Management and AI

    SC Moatti believes that product management is a constantly evolving field, and emphasizes the need for ongoing learning and adaptation. She encourages aspiring product managers to engage with the product community through platforms like “Products That Count,” to keep up with the latest trends and challenges.

    When it comes to the future of AI, SC Moatti cautions against focusing solely on small, quick-win problems. She advocates for tackling larger, more complex issues, such as drug discovery, self-driving cars, and loneliness, areas where AI has the potential to revolutionize industries and improve lives.

    Key Takeaways for Startups

    SC Moatti’s insights offer valuable lessons for aspiring entrepreneurs:

    • Think big, start small: Focus on solving big problems but take a smaller, incremental approach to execution.
    • Invest in product excellence: Prioritize product quality and user experience as foundational elements of success.
    • Embrace lifelong learning: Continuously expand your knowledge and skills in the ever-evolving tech landscape.
    • Seek out mentors: Connect with peers and industry leaders who can offer guidance and support.

    Mighty Capital’s success serves as a testament to the power of applying a product mindset to the world of venture capital. By prioritizing a product-first approach and building strong relationships with entrepreneurs, they are defying the odds and shaping a new era of VC innovation.

    Nataraj is a Senior Product Manager at Microsoft Azure and the Author at Startup Project, featuring insights about building the next generation of enterprise technology products & businesses.

    Listen to the latest insights from leaders building the next generation products on Spotify, Apple, Substack and YouTube.

  • How Scispot is redefining modern biotech’s data infrastructure

    Biotech is becoming one of the world’s single biggest generator of data, expected to reach 40 exabytes a year by 2025—outstripping even astronomy’s fabled data deluge. Yet as much as 80 percent of those bytes never make it into an analytics pipeline. Three bottlenecks explain the gap: (1) stubbornly paper-based processes, (2) binary or proprietary instrument file formats that general-purpose integration tools cannot parse, and (3) hand-offs between wet-lab scientists and dry-lab bioinformaticians that break data lineage.

    Verticalization 2.0: Solving for Domain-Specific Friction

    Enter Scispot, a Seattle-based start-up founded in 2021 by brothers Satya and Guru Singh, which positions itself not as an electronic lab notebook or a data warehouse, but as a middleware layer purpose-built for life-science R&D, quality and manufacturing. The strategic insight is subtle and powerful: horizontal cloud platforms already exist, but they optimize for structured, JSON-ready data. Biotech’s heterogeneity demands schema-on-read ingestion and ontology mapping that an AWS or Snowflake cannot supply out of the box.

    Scispot’s architecture borrows liberally from modern data stacks—an unstructured “lake-house” for raw instrument output, metadata extraction via embeddings, and API access to graph databases—but is wrapped in compliance scaffolding (SOC 2, HIPAA, FDA 21 CFR 11) that is prohibitively expensive for labs to build alone. The company is effectively productizing the cost of trust, a move that mirrors how Zipline built FDA-grade logistics in drones or how Databricks turned Apache Spark into audit-ready enterprise software.

    YC’s Real Dividend: Market Signal Discipline

    Although accepted to Y Combinator on the promise of a voice-activated lab assistant, Scispot pivoted within weeks when early interviews revealed that customers valued reliable data plumbing over conversational bells and whistles. This underscores a counter-intuitive lesson from YC alumni: the program’s most enduring value may not be its brand or cheque, but its insistence that founders divorce themselves from their first idea and marry themselves to user-observed pain.

    That discipline paid off. Scispot signed its first customer before writing a line of production code—a pattern consistent with what Harvard Business School’s Thomas Eisenmann calls “lean startup inside a vertical wedge.” By focusing on a tiny subset of users (labs already running AI-driven experiments) but solving 90 percent of their total workflow, the brothers accelerated to profitability in year one and maintained “default alive” status, insulating the firm from the 2024 venture slowdown.

    Why Profitability Matters More in Vertical SaaS

    Horizontal SaaS vendors can afford years of cash-burn while they chase winner-take-all network effects; vertical players rarely enjoy those economies of scale. Instead, their defensibility comes from domain expertise, proprietary integrations and regulatory moats. Profitability becomes a strategic asset: it signals staying power to conservative customers, funds the painstaking addition of each new instrument driver, and reduces dependence on boom-and-bust capital cycles.

    Scispot’s break-even footing has already shaped its product roadmap. Rather than racing to become an all-in-one “Microsoft for Bio” suite, the team is doubling down on an agent-based orchestration engine that lets instrument-specific agents talk to experiment-metadata agents under human supervision. The choice keeps R&D burn modest while reinforcing the middleware thesis: be everywhere, own little, connect all.

    Lessons for Operators and Investors

    1. Treat Unstructured Data as a Feature, Not a Bug. Companies that design for messiness—using vector search, ontologies and schema-on-read—capture value where horizontal rivals stall.
    2. Compliance Is a Product Line. SOC 2 and HIPAA are not check-box exercises; they are sources of price premium and switching cost when woven into the core architecture.
    3. Fundamentals Trump Funding. YC’s internal analysis, echoed by Sizeport’s trajectory, shows no linear correlation between dollars raised and long-term success. Default-alive vertical SaaS firms can wait for strategic rather than survival capital.
    4. Remote Trust-Building Is a Competency. Sizeport’s COVID-era cohort had to master virtual selling and onboarding. As biotech globalizes, that skill set scales better than another flight to Cambridge, MA.

    What Comes Next

    Sizeport’s stated near-term goal is to become the staging warehouse for every experimental data point a lab produces, integrating seamlessly with incumbent ELNs and LIMS. Over a five-year horizon, the company aims to enable customers to mint their own AI-ready knowledge graphs—effectively turning drug-discovery IP into a queryable asset class. If successful, the platform could evolve into the “Databricks of Biotech,” but without owning the data outright.

    Nataraj is a Senior Product Manager at Microsoft Azure and the Author at Startup Project, featuring insights about building the next generation of enterprise technology products & businesses.

    Listen to the latest insights from leaders building the next generation products on Spotify, Apple, Substack and YouTube.

  • #74 Sajid Rahman – Angel Investor Secrets – Lessons from 1000+ Startup Investments

    In this episode of Startup Project, host Nataraj sits down with Sajid Rahman, a prolific angel investor with over 1000+ investments under his belt. They delve into the evolving investment landscape, exploring the significant changes that have occurred since their last conversation a couple of years ago.

    • Guest: Sajid Rahman – Top Angel Investor – GP at My Asia VC
    • Host: Nataraj – Senior Product Manager, Investor at Incisive.vc & Startup Advisor

    From Bull Run to Downturns:

    Rahman notes a significant shift from the bull run of 2020–2021, where companies secured funding at sometimes unjustified valuations. Rising interest rates and global challenges have led to a market correction, with many startups facing down rounds or struggling to raise capital. However, this also presents opportunities for investors to enter later–stage deals at a discount.

    Secondary Market Dynamics:

    The conversation touches upon the impact of changing market conditions on secondary deals. Rahman suggests that many secondary deals from 2021 may not hold their value, citing examples like Robinhood and Stripe, which have seen significant valuation fluctuations. He also highlights the unique case of SpaceX and the potential spin-off of Starlink, which could offer earlier liquidity for investors.

    Demystifying Dry Powder:

    Rahman addresses the concept of “dry powder“ – uninvested capital committed to VC funds. He clarifies misconceptions surrounding this term, explaining that LP commitments don‘t always translate to immediate deployment of capital. The decision to call capital depends on market conditions and the fund‘s investment strategy. While the current dry powder might not reach the levels of 2020–2021, Rahman believes it will gradually return to the market as valuations stabilize and investor confidence grows.

    The Web3 Evolution:

    The discussion then shifts to the Web3 space, where Rahman actively invests in web infrastructure companies building on blockchain technology. He acknowledges the presence of scams and emphasizes the importance of thorough due diligence. Rahman outlines three key narratives driving the current Web3 boom: the intersection of AI and blockchain, real–world asset tokenization (RWA), and decentralized infrastructure development. He also observes a trend of Web3 companies opting for traditional equity models instead of token–based fundraising to avoid regulatory hurdles.

    Sajid‘s Investment Approach and Portfolio:

    Nataraj and Rahman explore Sajid‘s diverse investment portfolio, which spans angel investments, syndicates, and four different funds focusing on Web3, YC companies, general early–stage startups, and soon, AI. Rahman shares his insights on managing multiple funds and his strategy for sourcing deals, which involves both inbound inquiries and proactive outreach. He reveals that his personal investment portfolio is heavily skewed towards startups, reflecting his belief in their long–term potential.

    The AI Boom and Valuation Concerns:

    The conversation concludes with a deep dive into the AI space, where Rahman sees value creation in both foundational models and application–layer companies. While he acknowledges the hype surrounding AI startups and the potential for overvaluation, he believes the sector holds immense promise. Rahman is currently working on launching an AI–focused fund to capitalize on the opportunities within this rapidly evolving field.

    This episode offers valuable insights into the current state of the investment world and the trends shaping the future. Rahman‘s experience and perspectives provide valuable guidance for both aspiring and seasoned investors navigating the ever–changing landscape.

    Additional Resources:

    #startup #investing #venturecapital #web3 #AI #angelinvesting #podcast #startupproject #secondarydeals #drypowder #blockchain #artificialintelligence #fundmanagement #YC #startupecosystem

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  • #73 Brian Bell – From Product Manager to Full Time Investor

    Brian Bell is the Managing Partner at Team Ignite. Bell has experience in product development in AI at Microsoft, AWS, and startups.

    Full conversation includes:

    🔸Transition from Product Management to full time investing

    🔸Investing in YC

    🔸Operating an investing Syndicate

    🔸Growth hacks to grow your syndicate

    🔸Is AngelList loosing its advantage?

    🔸Red flags in pitch decks

    🔸If money was not an object, what would you be doing?

    & more.

    Listen now 👇

    Follow Brain on twitter here – https://twitter.com/brianrbell

    Follow Nataraj on twitter here – https://twitter.com/natarajsindam

    Follow 100 Days of AI here – https://thestartupproject.io/100-days-of-ai/

    Subscribe now 👇

    🔸Spotify – https://open.spotify.com/show/3Cx7Q5r9Ow9eikxQjsJjjq

    🔸YouTube – https://www.youtube.com/channel/UCs8lGcgpE7JC-alvUhMPk3g

    🔸Apple Podcasts – https://podcasts.apple.com/us/podcast/startup-project/id1551300319?uo=4

    #startups #angellist #investing

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  • #72 Todd Bishop GeekWire Co-founder, Business and tech journalist on big tech, AI and more!

    New episode with Todd Bishop, GeekWire’s co-founder.

    Todd is a longtime business and technology journalist who reports on subjects including AI, the cloud, startups, and health technology, plus Amazon and Microsoft, in addition to hosting GeekWire’s weekly podcast. This is Todd’s second appearance on the Startup Project podcast.

    In our conversation, we discuss:

    🔸 How is a tech business journalist using AI?

    🔸 Does AI live up to the hype?

    🔸 Covering Big tech’s AI strategy as Geekwire Editor

    🔸 Amazon’s ecommerce AI assistant

    🔸Why hasn’t Amazon integrated Alexa with an LLM?

    🔸Data privacy legislation in AI

    🔸Layoffs in tech

    🔸TikTok Ban, will it or will it not happen?

    🔸Much more

    Listen now 👇

    YouTube: https://www.youtube.com/channel/UCs8lGcgpE7JC-alvUhMPk3g

    Lister to Todd’s first appearance on the podcast here.

    Follow Todd on twitter here – https://twitter.com/intent/user?screen_name=toddbishop

    Follow Nataraj on twitter here – https://lnkd.in/gUJ_Gah

    Follow 100 Days of AI here – https://lnkd.in/g_8T8_rZ

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  • #71 Peter Mueller Founding Partner Breakwater VC about Pre Seed Investing in Seattle Tech Startups

    In this episode Nataraj talked to Peter Mueller who is the founding partner of Breakwater ventures investing in early stage tech startups in Pacific Northwest and Wester Canadian Startups.

    The conversation includes:

    – how to think about angel investing & pre-seed investing?

    – Seattle pre-seed ecosystem

    – learnings from Seachange fund

    – thesis for breakwater

    – Whats making Western Canada an interesting place to invest?

    – investing in AI

    – long tail opportunity in AI

    & more.

    Follow peter on twitter here – https://twitter.com/pjsmueller

    Follow Nataraj on twitter here – https://twitter.com/natarajsindam

    Follow 100 Days of AI here – https://thestartupproject.io/100-days-of-ai/

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  • #70 Brendan Rogers From Founding WAG (NASDAQ: PET) to Investing in India

    In this episode Nataraj spoke to Brendan Rogers Ex Cofounder of Wag, a NASDAQ listed public company.

    Full conversation includes:

    • Origin story of WAG
    • Journey of investing in India
    • Why he is bullish on Indian startups?
    • Opinion on different sectors & more

    Listen to full conversation below:

    YouTube: https://youtu.be/DakyHNYpsQ4?si=ODH4G_8g65UEUPvx
    Spotify: https://open.spotify.com/episode/3ZAb7zfrzvGxVcEs4jGSOK?si=946c85e02bad4f85
    Other: https://podcasters.spotify.com/pod/show/startupproject

    To stay in loop for future conversations check out thestartupproject.io

    I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, subscribe to it.

    Follow me on Twitter, LinkedIn for latest updates on 100 days of AI. If you are in tech you might be interested in joining my community of tech professionals here.

  • #69 Direct-to-Consumer Companies & Long Tail Opportunity in AI (Above Average Newsletter)

    Welcome to 50th edition of the Above Average Newsletter. Your bi-weekly source of Above Average takes on the business of big technology written by Nataraj Sindam.

    Topic 1: What’s with Direct-to-Consumer Companies?

    What’s common among all these companies?

    All birdsBrilliant earth groupPelotonRent the runway

    They are all public direct to consumer companies whose stock is down ranging from 80 to 95% in last couple of years.

    If you are direct to consumer company the best time to go public was in 2021 when the pandemic has fueled an ecommerce spending spree. Once this is over, the markets realized a lot of these direct to consumer companies have no path to profitability and have unsustainable business models.

    So what can we learn from what is happening with direct to consumer companies –

    When you are willing to spend on high customer acquisition cost (CAC), you can create a short term non profitable direct to consumer company, even when industry dynamics don’t support it. If you spend enough amount of money on Facebook and Google ads you can sell any decent product.

    VC money was used to subsidize CAC, that is clear. But that stopped and these companies are not close to profitability and a lot of them are on the verge of bankruptcy. But if I am an investor in such brands the one thing I would look for is that the product innovation should reflect in my customer acquisition cost being low. If you are not able to get very low customer acquisition cost on your product or brand, then technically you are not creating value with your product. Your customer acquisition cost reflects whether the product/brand is actually desired by the customer & if the industry dynamics support it or not.

    Topic 2: Where is the AI opportunity?

    It’s easy to see big funding rounds in AI for foundation model companies and think AI is all about Fearsome Foursome funding Geoffrey Hinton’s ex-students or ex-open ai employees.

    But I think the real opportunity in AI for next couple of years is in the long tail of building specific narrow application that solve small problems that were not possible before. There is treasure trove to be exploited by teams of 1-3 developers to build SaaS applications which can generate millions in revenue.

    LLMs are a super power for full stack application developers. If you want to build something and are looking for such ideas feel free to reach out to me.

    Topic 3: 100 Days of AI experiments

    AI is going to impact us all, so as part of 2024’s first 100 days I am going to spend 1-2 hrs a day learning, experimenting, reading & tinkering with the latest AI models, products & content. You can follow along by following me on Twitter or here on my blog . My goal in this 100 days will be focused on what new things we can build using AI and what to expect from AI in future. The series is also published here on hackernoon .

    If you are listening to this and have not subscribed to the newsletter, please go subscribe.

    Till next time, stay above average.

    Nataraj

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  • #68 Why the new AI button on your keyboard is inevitable? (Above Average Newsletter)

    This episode is the audio version of Nataraj’s newsletter Above Average.

    Welcome to 49th edition of the Above Average Newsletter. Your bi-weekly source of Above Average takes on the business of big technology written by Nataraj.

    1. Why the new AI Button on Your Keyboard is inevitable?

    Microsoft is adding a new AI button to your PC keyboard. This is the first time Microsoft changed the PC keyboard in last 30 years. If you are a regular user of ChatGPT or its competitors you will notice your own behavior, that you use it repeatedly and it might get lost in the 10s of chrome tabs you have opened.

    You also realize that its a constant companion on your daily work. Microsoft already realized this and jumped head on into creating Copilots for all its products.

    The next step in this strategy is to have a dedicated button that will launch bing copilot which uses gpt-4 and is currently free.

    The move highlights couple of things:

    Copilots are going to an enduring form factor

    We will use copilots so often that it requires its own button

    Its a great use of Microsoft’s distribution power to create a new user behavior

    If this new behavior works its acts as counter to Google search. Your first step for any answer would be to tap that button and start asking the question. A better interface potentially to transition from a search dominant world to answer dominant world.

    2. Who is the biggest AI VC in town?

    As some one who closely works with a venture fund and interacted with lots of investors and invested in 20+ startups its important to note that the unseriousness of ZIRP era was prevalent in VC industry as much as it was in any other industry.

    This meant higher valuations that defy the gravity of the business became common. Chasing each others and asking the question “who else is investing” became the most important criteria. Deals closed faster than ever. Crypto as a sector suck more oxygen in the room that it should. Mostly because too much capital was chasing too few deals and in the process new & some old investors lost track of what is important. Its important for a VC to invest in important things in tech.

    Now with AI era on us, the biggest investors in AI are not the VC firms but its the fearsome foursome – Microsoft, Google, Amazon & Nvidia.

    The amount of investment commitments from these 4 companies has already exceeded $20B with a conservative estimate.

    Big tech companies never really invested in crypto like they are investing in AI.

    So what’s the take away here – if you think AI hype cycle is similar to crypto hype cycle, you are wrong. AI is an enduring cycle worthy of hype, unlike crypto which was propped up by VCs with out enough depth.

    3. My Experiments with AI:

    One of the reason this newsletter is less frequent than usual (from now on it will be twice a month) is because I am working on writing more on AI as part of a series I am calling 100 days of AI. If you are interested in gen AI experiments, ideas & trends follow along here. Here are some posts I have written about AI.

    – Design Thinking using Semantic Kernel – Get Insights from YouTube Podcast Video using Open AI’s GPT 4 – Build Your Own Chat with Data App

    Till next time, stay above average.
    Nataraj

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