Amritansh Raghav

This old post from Ben Horowitz highlights a common struggle among entrepreneurs – expecting the team to perform seamlessly without investing in training. People are not plug-and-play; they bring diverse backgrounds and perspectives. You gotta spend time training and educating on your business, the way you want to talk to customers, and the right experience you want for them. Training is a powerful tool and needs to be done regularly! https://lnkd.in/ekv8c6WD #Entrepreneurship #Training #BusinessSuccess

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A Simple Two-step Process for Career Advancement Want to get ahead in your company? Do these two things: 1. Give away your Legos 2. Generate more impact I didn't say it would be easy! Only simple. Giving away your Legos means sharing responsibility effectively. By finding (and training) others who can take over for you, you free yourself to take on new things. And, of course, you create opportunities and growth for your team. But remember the word, "effectively." You can't set it and forget it. You are still ultimately responsible for the results, and you have to ensure the quality and results are there. Finding new, more impactful projects is even harder. The farther (or higher) you advance, the harder it gets. Playbooks run out. Mentorship is scarce. Stay focused on business impact and prioritize your time ruthlessly. Scores of books have been written on both topics. But ultimately the formula is simple -- free yourself by investing (and believing) in others, and use that freedom to pursue impact and generate results.

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I participated in a “SMART MANUFACTURING” panel with Gayathri Radhakrishnan, Rohini Chakravarthy and Abhijit Supekar (moderator) last week at TIECon 2024. The coolest part of the panel was 3 Women VCs talking about a topic that has not traditionally been discussed by women. I never imagined I’d see this in my lifetime. Things have indeed changed! We had a very lively discussion of whether we can expect lights out factory in 5-10 years. Automation is happening in all stages but full automation manufacturing is tough because it requires human like adaptability. It is not converting text into instruction or code - it is about precision. Robotics + AI is making this happen and we will get there. AI is going to bring the cost down for complete solution for example: there are robotic arms that can do more tasks and learn like a human and not just some specific tasks. Also check out our portfolio companies Micropsi Industries and RGo Robotics that are making it happen in this space. Thanks to Anshu Bahadur Hrishikesh Sathawane Nilesh Dixit for organizing the panel and Anita Manwani and Surbhi Kaul for making this happen! #TiECon2024 #AIUbiquity

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A powerful team is never just a collection of individuals. There is extraordinary value in connections and relationships that are built over time. But how do you quantify these nuanced and dynamic traits? Here are some ideas: ✨ DORA Metrics: While primarily leveraged for assessing software delivery performance, DORA Metrics can offer insights into team efficiency and collaboration. Metrics like deployment frequency and lead time for changes are indirect indicators of how well a team operates together. 🌟 Net Promoter Score (NPS): Going beyond customer satisfaction, internally, NPS can be adapted to gauge team members' satisfaction and willingness to recommend their team to others. It captures engagement, morale, and overall sentiment within the team. ♻️ Feedback loops: How often is the team giving feedback to others? Tracking data points like these over time, and especially showing how changing the team impacts the data can tell a compelling story. It might give a clear voice to a nuanced understanding of the impact of changing the team when there are concerns for doing so. As a leader what metrics do you track to help you understand how change impacts a team?

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Lior Solomon and the team at Drata thought if their Amplitude experiment produced at least 500 customer adoptions, that would be a success. So, when the experiment actually drove 2,000 customer adoptions, let’s just say they were excited about that. Learn how Lior and the team at Drata use Amplitude!

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A handy visual guide for Product folks about to contemplate and communicate, well, just about anything. As with so much in our domain, simple at surface, elaborate to execute, but priceless when proper.

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We need to move past the idea that knowing everything is the best; asking good questions is a much more critical and underrated skill that we need to embrace. I’ll demonstrate with a case study on how the exact problem to solve can dramatically shift based on answers to basic questions. But first, why does this matter? This is because good questions are the cornerstone to truly understanding the underlying requirements. So many issues would simply not exist if the right questions were asked at the right time - Many products with little to no adoption would not be built - Numerous designs would not be scrapped very late in the game - Countless incidents would be caught before they make it to production Let’s use my favorite leveling question shared previously https://lnkd.in/gxCHTWSu. "Imagine you join our team/company X and discover that our SLAs (Service Level Agreements) are consistently in the red. What steps would you take to address this issue?" Fundamental questions to ask: Q1: Are the customers actually unhappy? If there are no customer complaints, the problem may boil down to a simple SLA update. If there are complaints, changes to the system are likely necessary Q2: What specific SLAs are in red? How long is “consistent”? If multiple SLAs (latency, availability, consistency) have been red for 12 months, it's a deeper systemic problem. If a single SLA is red for 3 months, it’s a simpler problem. Q3: What is the SLA and what is the system performance? If the SLA and system performance don’t diverge that much, it can be solved with incremental steps. However, if the SLA is 99.99% and performance is 99%, then deeper issues must be addressed. To recap… Asking the right questions at the right time can entirely transform the approach and solution, saving a lot of time, effort and grief. It is a critical skill for senior engineers. I’ll leave you with this iconic clip from Margin Call… “Explain, as you might to a young child. Or a golden retriever” ~~~ ✍️ Do you agree? Share if you have examples where the right question changed project’s direction. ♻️ Repost if this is helpful.

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I’m less enamored with Lean Startups than I was 16 years ago. I think it was a good philosophy when people were first starting to take advantage of the plunging costs of building software due to open source and the cloud. The idea of product-market fit is the most recognized concept to come out of the Lean Startup movement. Everyone wants to achieve product-market fit even if most people cannot define it.  I guess you know it when you see it... Every startup is in a rush to say they have product-market fit because that is what is demanded of them. Saying you haven’t achieved PMF is like broadcasting you’re incompetent. But the opposite of product-market fit is not failure or incompetence. You could be researching, learning and iterating (or pivoting). For early stage investors especially, those activities sound like they would build a lot of future value. As Steve Blank (quoting Tolkein) says, “not all those who wander are lost.” To build better companies, especially outside of software (eg deeptech) we need to value the wandering. It has to be wandering for a purpose. The timing of when a startup finishes wandering might not neatly line up with how we name funding rounds. True innovation usually resists standardized frameworks. Read my full post, Sceptic Mode Part II: https://lnkd.in/g2HqneVV

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When you scale up testing, you need to be able to scale up your ability to triage all the failures. Check out the Foretellix Solution for scaling failure triage.

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Rupert Spira is one of the leading lights of Advaita vedanta in present times. The words he speaks come directly from the source (infinity) and have the potency to lead you to infinity. The simplicity and clarity of the teachings is remarkable. Advaita provides an effective solution to the problem of pain and suffering. Human life is such that pain and suffering can not be avoided altogether. There are ways to get temporary relief but that's not a true solution. Through Advaita one can transcend pain and suffering. It's a paradigm shift because it does nothing to the pain and suffering but alters ones identification with it. This directly reduces the effect pain and suffering has on one. Advaita also addresses the perennial problem of search for happiness in outside things by conclusively showing that you are the source of what you are searching. Understanding this knowledge and living it gives instant peace and access to bliss. Highly recommend this beautiful and subtle piece of work by Rupert. ~S~

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Last Tuesday, Malsgufa, our legacy CMS backend, was shut down. This milestone for BI's Tech and Product team culminated years of planning, effort, and execution. Malsgufa's first commit was on July 25, 2014, leading to 5,186 commits across nearly 30 repositories. Built and maintained by scores of engineers, its deprecation represents significant cost savings (20 production replicas, 3 instances of Solr, and an insane number of Zookeeper instances!), reduced security risk, and the elimination of an often-blamed boogeyman. The journey began in January 2020. Our challenge: moving traffic off Malsgufa without rebuilding everything in Muse. Initially, we tried GraphQL as an intermediary between Viking and our services, but progress was limited by Viking's complex Angular/Vue architecture. In January 2023, we pivoted to the strangler fig pattern with a shim. This approach proved far more effective – all Malsgufa traffic went through the shim first, with verbose logging to track unhandled requests. Meanwhile, we built Story Versioning API (SVAPI), incorporating lessons learned from Malsgufa's limitations around history and publishing states. We ran four major migrations (stories, custom pages, slideshows, and videos), building support in Muse and shimmed compatibility for Viking. Traffic gradually decreased from a torrent to a trickle, leading to the gloriously uneventful shutdown. Next, we will deprecate Viking by Q2 2025, unifying our users in the Muse ecosystem to create the industry's most innovative CMS. Special thanks to the entire Story Creation team: Chase Gruber, Chris Speziale, Daniel Arita, Danny Feliz, Dasha Lary, Dawin Camillo, Eric Saam, Frederica Chen, John Laslo, Kelly Filush, Morgan Cohn, Sarah Pai, Tyler Greenfield! Thanks also to DaD, Engagement, Helpfulness, Cloud Engineering, Test Engineering, and Operational Excellence! Finally, we recognize Malsgufa itself. Developed as a unified CMS backend to support Business Insider's expansion into new markets, it served our global newsroom reliably for a decade, publishing millions of stories despite no major changes in recent years. While it became less sustainable as our business evolved, it deserves our respect. Thank you, Malsgufa. May you rust in peace.

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Data is like crude oil. Any companies working on foundation models would protect it fiercely - it’s a competitive edge. This is unlikely to change any time soon. Oil refinery needs raw material. Absent data, a foundation model underfits. The leading models on LMSYS Chatbot Arena Leaderboard are fundamentally based on transformers. If model architecture does not give an edge, what does? Yup, one big area is data! This is especially the case where data is scarce: 1) highly specialized domains (financial trading, biomedical research, medical information, etc) 2) enabling new behavior (how the model determines the right function to call, how model understands in-depth video content, etc) These limitations cannot be solved with more compute. The model will perform poorly on areas lacking enough data. Furthermore, for new model behavior, the model cannot even do it to start with. Even if it can, how reliable is it (for practical applications)? Even with more public sourced datasets, the competitive edge will still be the additional data that your competitors do not have. Lastly, a fundamental pinning is that machine learning needs data. In fact, lots of high quality data. Even with a new paradigm shift, this will remain true. https://lnkd.in/gwbUFyFR #llms #foundationmodels #datasets #datageneration

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“One of the biggest lessons in management over the last decade is that micromanagement is bad. But I think this is an anti-pattern, because it creates disengaged and context-free leadership.” Today on First Round Capital Review, veteran engineering leader and Carta CTO Will Larson holds three commonplace management practices up to the light for a closer look. Send to an engineer in your life!

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I often find myself trying to communicate how the depth, breadth and nuance of thoughtful, contextualized product design can create systemic ripples across the landscape of society, culture, and economy. The principle of larger effects and systems seems rather timely given the impacts and implications of the work we find ourselves in the weeds. What might mindful, thoughtful innovation look like? If we are disruptive, working from a place of care and positive intent, are we still able to see the larger picture and the possible ripples from decisions? There is a power differential in recognizing the effects on systems. We often hear things like “technology is not neutral” or “the victors write the history”. This may mean there are far-reaching implications of decisions and systemic impacts without the realization of unintended consequences. If we are seeking to consider equity within a product we must increase our awareness and research, design, develop and execute from a space of curiosity without weaponizing approaches based on moral codes, personal beliefs and misaligned values. What does “for good” look like in practice, and to whom is it good for? We are often reliant on dominant narratives and frame things as edge cases. Those on the “edges” are often perceived as more work than necessary, less important, or statistically insignificant. This leads whole human identities to be framed as outliers.   These focused threads demonstrate how a product can drive change by reshaping perceptions and practices at both individual behaviours, choices, industry standards and cultural narratives. It’s about initiating change that can be sustained, leading to a reimagining of systems that have gone unchallenged. This guides us to examine the influence on social structures, economies, and ethical frameworks. A decolonization perspective asks us to critically examine how historical contexts have shaped products. Dismantling the inequities that are embedded within current systems, our journey begins in a world saturated with products designed without the richness of human difference in mind. The one-size-fits-all mentality prevails. Systems innovation would mean designing products that do not perpetuate colonial legacies but instead respect and uplift local knowledge, traditions, and needs. Who benefits from these innovations? Are these technologies accessible to all, or do they widen the digital divide? Do these innovations respect locality, or data sovereignty? Product equity must address global complexities, considering how a product fits into various cultural contexts and the impact on different communities. It's not just about doing no harm but actively doing good. Understanding balance—the need for steady iteration and the courage for radical change. We can build currents strong enough to redefine systems, rewrite narratives, and reshape these ecosystems. #ProductEquity #PrinciplesOfEquity #SystemsInnovation #SystemsThinking #Decolonization

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A successful systems design and delivery strategy begins by assuming that change is likely the only constant. Be adaptable, or fail.

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I ruffled some feathers some weeks ago stating "there's no such thing as _healthy_ tension between Product and Engineering." 😎 This was an intentionally controversial statement, because high contrast is a useful way to stir up conversation. 🔥🔥🔥 I spent a fun 30 minutes with Matt Watson of Full Scale chatting about this topic to add all the necessary nuance and shades of gray. 👉 Link in comments Other topics covered: ✅ Why traditional team structures create conflict ✅ The real definition of a "10x developer" (it's not what you think) ✅ How AI is forcing developers to think differently ✅ Why misaligned incentives kill innovation ✅ The evolution from CTO to true product leader Give it a listen and hit me up with comments below! 👇

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How do you ensure you're innovating while also honing in on the areas that will drive the most impact? Navigating the dual demands of exploration and focus is a pivotal challenge every product leader faces, especially as your company evolves. In my latest conversation with Vrushali Paunikar, CPO at Carta, we explored how Carta approached this challenge. In the early days, Carta experimented widely, planting seeds in various markets and nurturing a range of ideas. But as the company grew, the strategy shifted to doubling down on what worked—focusing efforts on areas with the most potential for long-term success. We also covered: ✅ How Carta transitioned from broad experimentation to focusing on proven product lines.     ✅ The importance of validating your innovations to ensure they’re addressing real customer problems, not just creating something new for the sake of it.                               ✅ Vrushali’s insights on making informed decisions about equity distribution in early-stage startups, drawing from Carta’s extensive data. As Vrushali puts it, "We’re not just innovating for the sake of innovating; it's about creating truly differentiated experiences that people want to live in.” Listen to the full episode here 👇 🎧 Spotify: https://lnkd.in/eU8ye-Th 🎙️ Apple Podcast: https://lnkd.in/eNrPdm2n How are you refining experimentation and focus in your product strategy? Let’s discuss in the comments! #productthinking #productmanagement #carta #leadership #strategy

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