MG Gurbaxani

I've been so excited to share the results of this report! We partnered with Forrester to do an objective deep dive with our hundreds of customers to understand the total economic impact of implementing Cortex. Many of these customers migrated from using open source frameworks like Backstage due to low adoption or various other reasons. Happy to say the results are in... and it's more clear than ever that adopting Cortex leads to real tangible ROI across various parts of engineering productivity. Check out the full report below and reach out if you want to supercharge your developer experience :)

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In big companies it’s often not build vs buy. It’s build and buy and do nothing, simultaneously. Many big companies we worked with at Propeller were, at any given moment: • Running internal teams/programs developing competitive products,  • Exploring alternative, overlapping partners, and • Contemplating increasing, pausing or reallocating investment altogether. You’ll do better if you assume big companies aren’t making a binary, or irrevocable, decision.

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40 mins of immensely actionable advice for all Vertical SaaS founders from ServiceTitan’s Ara Mahdessian. The TL;DR: - Everything about your business needs to back into delivering tangible customer ROI: Your product, your messaging and your org structure - If you are in a market where your product workflows can deliver meaningful financial ROI: Go deep - Invest deeply in Customer Success: Be a person of your word, if you promise ROI orient your team around unlocking it - Expand faster than you think: Move up or down market, start building product 2 and 3 before you think your ready. The compounding effect is real - Act fast if it’s the wrong fit: Both the company and the team member will thank you later - Psycho analyze what drives you and your team: Why are you on this journey? What are you chasing? #builders #mindset

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Technically having a long context is still not enough

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Coming back from RSA Conference this week, it’s clear that there is the new normal in venture funding is firmly established... The key theme for startups is continued expectation of reasonable growth to profitability. If that message wasn’t clear before, it should be now.  Raise what you need and work like hell to grow revenue was the approach of Mandiant (part of Google Cloud). Some specific approaches that are clear: > The deeper you can go into your next investment series revenue range, the better. I spoke to companies who want to raise a Series A round at $1M revenue. At that revenue range, your valuation is going to take a double hit: lower revenue, and much lower revenue multiple. > You should be able to show you can get to profitability using funding from your Series A round. Whether you do, or not, is up for debate. > Understand at what point you can get to default alive. To calculate your default alive revenue point, do this: Take your existing operating expenses as a constant. Project out revenue at your current revenue growth rate. Can you make it to profitability on the cash you have available today? If yes, you are default alive If not, default dead Money costs something now. You’re going to see less of it. Make the most of what you raise. #RSAC #RSAC2024 #startup #cyber #cybersecurity #startups #funding #VC

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Great article from McKinsey about why scaling AI products is a whole other ball game to developing and deploying them 'in the lab'. "Models account for only about 15 percent of the overall cost of gen AI applications. Understand where the costs lurk, and apply the right tools and capabilities to rein them in." If this resonates - come and talk to us at Mystic AI as we can ease the transition from R&D to full production and help keep the costs in check as you scale. https://lnkd.in/eGpigNad

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The importance of getting to 'the second product' at the right time totally resonated with me when I first read Elad Gil's High Growth Handbook. Must have been in 2019, seems like a very long time ago. More recently (like, yesterday!) we waved goodbye to the Beta label on our big second product at Hello Retail, called Product Intelligence. Time to start taking it to the market, after 4 years of hardcore, entirely homegrown, AI development. Product Intelligence is an API product. So in order to show what's actually inside it, we've built this super neat free tool called the Product Explorer. Paste any product into it and it gives back purchasing pattern data—predicting, with crazy accuracy, what shoppers buy next, the LTV of the product, when it's bought, and how it's best discounted. The Product Explorer is the marketing vehicle to understand the data. The actual product is this: Customers now get to access this for all their own products and use it at scale. Run thousands of products through it—to know how to best promote every single product. There's a lot for us to start unpacking for sure. I've been with Hello Retail for a little over half a year now and we're launching more exciting stuff than I can easily communicate. But this for sure stands out, big-time. #RiskInMarketing #CMOstories

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Have you ever looked for theory that can answer - how to approach investors - what kind of product to build first - how you’ll defend the company against competitors This new article from CDA partner, Kevin Maney extends Steven Johnson's writing from the book Emergence to #CategoryDesign. All #Startups and #VentureCapital teams should dig in. (link to article in comments)

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I built a customer success platform from scratch—no co-founder, no team, no funding, no capital, and no experience—all while working 40+ hours a week. I realised that existing CS platforms were too complex, too expensive, and focused on "looking busy" (pointless dashboards, endless automation, playbooks on top of playbooks). All the start-ups I've worked with needed a platform long before they implemented one. Put off by the cost, complexity, and management requirements, it was seen as a "nice to have." That's why I decided to build something specifically for start-ups. During a break between jobs, after some rapid research, I jumped right in. I found a development tool to quickly spin up an MVP. Despite a steep learning curve, I figured it out as I went. For the first few months, I worked 12-14 hours a day, every day. It was inefficient, and I threw several versions in the bin and started over. Many hours were frustratingly wasted, but at least I was learning from my mistakes. I found my stride about four weeks in. When I started a new job, I'd work all day, have dinner, walk the dog, and then work until midnight. I spent almost every weekend working on it, and worked through summer and over Christmas. After a few thousand hours and no more than £500 spent (subscription costs for the platform I was using), I finally "launched." I was hoping for a flood of messages asking for demos but quickly realised I needed to learn how to take a product to market. That brings me to now. I’m still learning the marketing side of things, but I believe I've built a tool that helps start-ups deliver customer success and addresses real issues around price and complexity. CS-X.io delivers a better customer experience and can turn around new features faster than any other platform on the market. My mission is to help you go from "start-up" to "scale-up" by accelerating your customer success efforts and giving you the right tools for the job. I don't know if all the hours I've invested will be worth it in the end, but all that matters is I’m trying something, learning something, and believing in something. If you have any tips for me or other people who are doing the same thing, let me know in the comments! P.S - A special thanks to my incredibly patient, supportive and encouraging partner Hollie Ellis, I really couldn't have got this far without cheering me on! #customersuccess #csplatform #saas #startup #csp

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AI-driven predictive maintenance is transforming how businesses manage their equipment and infrastructure. By leveraging AI, companies can reduce downtime, save costs, and enhance safety, leading to improved operational efficiency and productivity. Implementing best practices and learning from industry leaders can help businesses successfully integrate predictive maintenance into their operations. #AI #SaaS #PredictiveMaintenance #MachineLearning #DataAnalytics #Automation #TechInnovation #DigitalTransformation #CloudComputing #BusinessStrategy #ArtificialIntelligence #FutureOfWork #BusinessGrowth #AIIntegration #ManufacturingTech #EnergyTech #HealthcareTech #TransportTech #MaintenanceSolutions #OperationalEfficiency

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GlobalData Plc - the UK Data & Information Services Company. It reminds me a lot of IHS which Markit bought many years ago. Niche industry vertical dataset focus They recently sold 40% of their Healthcare vertical to Inflexion for $550m. They mention the money will be used for M&A in consumer, technology and healthcare industries. What do they buy next? I share a lot of my ideas in my blog post below. Do they go deeper in consumer and try to take a swing at a consumer transaction data provider like Envestnet | Yodlee? Do they think about something like Circana which is the combination of NPD & IRI? Or do they stay small and do little tuck ins like consumer survey businesses? How do they get more distribution? More visibility? Especially in the US! Maybe they start announcing new datasets on Initial Data Offering. Maybe they make acquisitions for distribution. There are some exciting consumption based data marketplaces that could be a great way for them to sell more. One thing is for sure, they have some unique data assets and in the AI hungry data buying world, I am watching their moves closely. How did I do my analysis on Global Data? Leveraging FinChat of course.

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In previous posts, I've shared aspects of the Chief of Staff role (what makes a strong CoS, how to navigate the first 90 days, how to present so your CEO listens). Today, I will share aspects of another role I've done – 𝐕𝐂 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦/𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫, 𝐚𝐧𝐝 𝐰𝐡𝐲 𝐢𝐭'𝐬 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭. 𝐇𝐚𝐯𝐢𝐧𝐠 𝐚 𝐬𝐭𝐫𝐨𝐧𝐠 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐬 𝐕𝐂𝐬 𝐭𝐨 𝐜𝐨𝐧𝐭𝐢𝐧𝐮𝐞 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐯𝐞 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐩𝐨𝐬𝐭-𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭. As portfolio companies embark on their growth journeys, having a dedicated VC platform operator can be a game-changer in accelerating their success. A platform operator acts as a strategic partner, providing hands-on operational support and leveraging the collective resources and expertise of the fund to drive tangible results across critical areas. If the VC has a strong operator in the platform role, their portfolio companies can benefit from a range of services tailored to their unique needs: 1. Operations and Community: A good platform operator can streamline processes, foster collaboration, and cultivate a thriving community within the portfolio, enabling knowledge-sharing and collective growth. 2. Business Development: With a deep understanding of the VC's investment thesis and industry landscapes, a platform operator can actively identify and facilitate strategic partnerships, distribution channels, and growth opportunities for the portfolio companies. 3. Marketing and Strategy: From crafting compelling narratives to executing data-driven marketing campaigns and refining go-to-market strategies, a platform operator can amplify the visibility and positioning of the portfolio companies. 4. HR and Talent: Attracting and retaining top talent is crucial for scaling startups. A platform operator can provide guidance on talent acquisition, employee engagement, and culture-building initiatives, ensuring the portfolio companies have the right people to drive their vision forward. By leveraging the expertise of a dedicated platform operator, a VC's portfolio companies can focus on their core strengths while benefiting from a comprehensive support system designed to accelerate their growth trajectories. Not to mention the time freed up for the investment team to do what they do best – source and evaluate deals. Investing in a platform operator can be a force multiplier, maximizing the impact of the fund and propelling the portfolio companies toward even greater success. And funds with 25 or more companies should strongly consider having this role on their team.

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Tomorrow is the summer edition of SaaStock Local London and we've a great entrepreneur sharing his story of how he orchestrated an exit (to Zuora). If your building a SaaS with a view to a future exit (most folks except Basecamp), Or your currently thinking about M&A Then this is the inside story from a great founder, James Henderson, who got a fantastic outcome. The content will not be recorded, so you have to be there to get the insights such as: Why selling was right for James and Zephr - How do you plan an exit - What forces did James consider before he sold - How he managed his team and board through the process - What happens when you make a deal and sell All these questions and you get to ask your own. So make sure you're there if you're serious about building a SaaS company to sale. Around 17 tickets remaining. Link in the comments. #exits #M&A #founders #saas #london #CEO #saastocklocallondon

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It's been a Monumental quarter for Cognite and we are still not finished Last week, we release perhaps one of our most extensive sets of Product updates, with 40+ features spanning areas such as: - Advanced AI-driven data search for Industrial users - Collaborative & Generative Industrial Canvas for Industrial planning - Offline autonomous robotics mission planning - Streamlit-powered AI-application development - 3D contextualization & configuration - and more Cognite Data Fusion® is now even more personalized. We bring the most relevant tools, insights, and data directly to our users with workspaces for industrial users and data managers Cognite is transforming how companies operate, starting with the frontline. Field workers now have instant access to OT, IT and Engineering data in the field from their phone and can easily search for and act on highly critical findings. For more technical details, demos, and Industrial insights:

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This acquisition highlights the importance of data management as a critical precursor to implementing generative AI. From the WSJ: "Data is a critical part of enabling generative AI because vast quantities of it are needed to train AI models like OpenAI’s GPT-4 and Anthropic’s Claude. For businesses, their private data is needed to customize those AI models to perform data analysis, summarization and other tasks with it. Without it, AI models are limited to what they have learned from their initial training on public data online, up to a certain point in time." https://lnkd.in/gXMAhJ26

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Great to be chatting more about #agenticAI and #generativeAI with Matthew Cloke, John Cotterell and Joe Dunleavy. Really excited about the potential impact on business & society!

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SaaS to AI shift will happen faster than most of us think Enterprise software to the Cloud/SaaS shift took time Why? - A big mindset change was needed - The business model had to be different - Lots of education + trust building was needed Understandably, it took time for this shift But to go from SaaS to AI.... Practically, it’s just switching to a new API

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Wrapping the final article in the Science of Perpetual Data series - it focuses on Complex Adaptive Systems Thinking and Feedback Cycles. It is a quick intro to an area where businesses can tap a lot of value ad #analytics and really exploit the value of their #data. https://lnkd.in/eX6XWr_M

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10 Lessons in building a $150m ARR SaaS business within 8 years Whilst also investing in over 200 SaaS Companies The Go to Market Handbook for B2B SaaS Leaders 🎯 I had the chance to be Interviewed by Rubén D. with my Co-Author Richard Blundell about our straight-to-the-point WorkBook for SaaS Leaders. Stoked to be in my favourite Newsletter The VC Corner 💙 The Go-to-Market Handbook for B2B SaaS Leaders pulls from our decades of experience founding, scaling & investing in companies. I invest in a new company every week, in fact 2 this week 😉 A few things Founders & CEOs are making a killing on from the Book: • 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿’𝘀 𝗽𝗮𝗶𝗻 💡—if you’re not crystal clear on this, you’re missing the mark. The proposition will miss the most valuable buyers.. ⬇ 💲 • 𝗚𝗼 𝘀𝗹𝗼𝘄 𝘁𝗼 𝗴𝗼 𝗳𝗮𝘀𝘁 ⏳—strategic, deliberate steps will get you further than rushing. Why 80% of Start Ups never find Product Market Fit... ⬇ 💲 • 𝗨𝗻𝗹𝗼𝗰𝗸 𝗵𝗶𝗱𝗱𝗲𝗻 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 💰—pricing and packaging aren’t afterthoughts, they’re growth drivers. Price for the Entire Lifecycle to get richer... ⬆ 💰 For SaaS Founders & Leaders trying to nail product-market fit or scale efficiently, this interview is a must-read👇 https://lnkd.in/e-3uaGB9

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