Prakash Ramamurthy

Surround yourself with high achievers – the ones who deliver exceptional results, set high expectations, and push others to excel. These passionate, sometimes controversial leaders make a real impact. Echoing the wisdom of former Google CEO: 'Hire the divas.' #Leadership #Innovation #Success"

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Here are my key takeaways from the second panel at the ”Resilience in the Ever-Changing Environment" conference at Nasdaq in #NY moderated by Kris Pederson who is leading the EY Center for Board Matters, featured industry luminaries like Bhawna Singh, Okta CTO, Mike O'Rourke, Head of Nasdaq AI & Emerging Technology, and Usman Sheikh; Partner & Chair of the Blockchain & FinTech Practice At Baker McKenzie They discussed product differentiation and M&A strategy in relations with emerging technologies such as #GenAI, #QuantumComputing, #Blockchain, #EdgeComputing; shaping the future of business and society, highlighting the importance for boards to be well-versed in such areas and to ask timely questions to ensure management has been considering these topics and making informed decisions. Boards should consider how generative AI can enhance productivity, improve customer experiences, and drive innovation, while ensuring it is used ethically. Boards should help establish ethical guardrails for AI usage, promote transparency, and address potential biases. They should collaborate with stakeholders to ensure AI aligns with societal values and ethical standards. Additionally, risk management around AI should include the following: AI Laws: Boards need to stay informed and proactive about the evolving legal landscape surrounding AI. This includes understanding compliance requirements, anticipating regulatory changes, and engaging with policymakers. Active engagement can help shape policies that balance innovation with ethical considerations. Ethical and Secure AI Deployment: As AI becomes more integral to business operations, ensuring its ethical use and securing AI systems are paramount. Companies should extend security measures to their entire data platform and pipeline and adhere to high standards of ethical AI practices, possibly under the guidance of specially formed committees. AI Innovation in the Wrong Hands: There is a significant risk of AI technology being misused by malicious actors. Boards should implement robust ethical guidelines to ensure their AI innovations are not misappropriated or used unethically. This involves careful vetting of partners and clients, as well as ongoing monitoring of AI deployments to detect and prevent misuse. Attack Protection / AI Security: As AI systems become more integrated into business operations, they become increasingly attractive targets for cyberattacks. Boards must prioritize AI security by investing in advanced security measures and conducting regular audits. This includes safeguarding AI algorithms, ensuring data integrity, and protecting the underlying infrastructure to prevent unauthorized access and attacks. #NasdaqResilience #TechInnovation #BoardGovernance #GenerativeAI #QuantumComputing #Blockchain #EdgeComputing #AIEthics #AIRegulation #BoardLeadership #BoardOversight #BoardResponsibilities #BoardOfDirectors

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One of my favorite people is Bob Van Nortwick. He started & built AWS for Startups in 2010. Let me share a story about Bob. It’s 2012. By this time I’ve known Bob for a few years - he was the AWS liaison to our portfolio at a16z. Credits, technical support, meeting Werner Vogels, you name it, Bob got it done. He built this team to over a thousand people by the time he left ten years later. This is a HUGE role. Startups are a large part of AWS, which is the growth engine of Amazon. You’d expected Bob to have self-portraits adorn his home, start off meetings with grandiose introduction, & relentlessly name drop founders & investors. Not Bob. He’s hilarious & humble, a combo of dad jokes with f-words sprinkled in. He listens to you with complete attention. Even when I call Bob, I can HEAR his focus. He sees me even when he cannot see me. Most of all, Bob was (& is) RESPONSIVE. Anytime I’d email him, he’d reply in five minutes or less. If I explicitly wrote “this can wait” he’d STILL reply in five minutes or less. Back to my story. It’s about 11pm ET on a Tuesday in NYC. I’m in my hotel room winding down. I should sleep but jet lag. Then I see the email no one wants.   A founder emails me about how his entire infrastructure melted down an hour earlier. I’m not technical but I understand adjectives. This is disaster. And, he’s launching his new ipad app this Thursday.   Less than 48 hours.   Which will be featured on the App Store. To millions of people. I immediately email Bob but I’m sure we’ll have to delay the launch and therefore lose the feature. As usual, he replies in five minutes, asks to be connected directly with the founder. I email the founder the next day. No reply. Not a good sign, but understandable. I email Bob. No reply. Shit. What I didn’t know was that Bob & his team were meeting every hour, pulling all nighters, do everything possible. They probably needed a week; they did it less than 48 hours. On Thursday, the founder emails “WE’RE ON THE STORE!!” The launch is a success! Whenever I share this story about Bob, he smiles & says “We’re just doing our job.” Amazingly, everything I just wrote is not the best part about Bob. He’s a fantastic dad with three grown & accomplished children. But of course he’d be a great father! He’s humble, hard working. Even though we’ve never worked formally together, when you work with Bob, you feel like you share an email address with him.   Why did I write this?   Do I owe Bob a poker debt? Is this a sponsored post by AWS? No, I just caught up with him, reminiscing about old times, & he has the same warmth, same deep attention, same dad humor. Our industry has wild & extreme personalities.   I’ve worked with some of them. It’s fun but exhausting. BUT there are very decent people here too.   They don’t get headlines. They don’t want them. But their stories,  their achievements, their character,  deserve sharing. If you know Bob, please tease & embarrass the shit out of him. 😁

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How did Keyfactor, a leader in identity and access management, scale from $15M to $100M in 5 years? I was personally curious, which is why invited their incomparable CMO, a true GOAT, Jamie Walker, on The GOATS of Growth to find out. She cited 3 key strategic decisions, one of which you'll hear in the clip below, that she made early on based on her lack of budget and desire to build to predictability into the fabric of their growth. For the full episode, please search for The GOATS of Growth online or where you consume podcasts. Or just click the link in the comments below. Jaime, you were a great guest! Thanks for joining me and for allowing me to share your approach to growth with my audience. Please follow Jaime to learn more about her and for more great insight.

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Devops is one of the hardest categories to build in. Not because the product is hard, but more because distribution is even harder. The best entrepreneurs in Devops started organically. The Facets.cloud founders started building Devops automation platform inside Capillary. They didn’t intend to start a company. When entire Capillary cloud orchestration moved to Facets and other startup team started asking for it, that’s when Facets team have to build a separate company. Capillary hence became the anchor customer of Facets. And at Neon we are proud to back Facets mission to revolutionise the way software is developed and deployed, enabling teams to do more with less and ultimately drive greater value for their customers. Read more about Facets' journey here: https://lnkd.in/g5m7BzZw  Pravanjan Choudhury Anshul Sao Rohit Raveendran

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New on First Round Capital Review, Will Larson digs into why common management practices have become anti patterns, and which ones engineering execs should lean into to sharpen their team strategy. Always fun to learn from old Stripe co-workers :)

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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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In a recent article, we see Saumya Bhatnagar, co-founder and chief product officer at the AI sales rep startup Jeeva, reflect on her experiences as a woman in technology. As someone who has often found herself as the only woman in different settings, she underscores a significant challenge in our industry: the underrepresentation of women in tech roles and leadership positions. This issue is especially salient in fields like AI, where innovation thrives on diverse perspectives. Saumya’s journey highlights a growing movement among women in tech to build supportive communities. They are finding ways to connect, share experiences, and empower one another as they navigate challenges in the industry. This is significant for the IT sector as it fosters a more inclusive environment, which is proven to drive creativity and better outcomes. As we look to the future, it's clear that increasing diversity opens doors for new ideas and innovations. The industry must prioritize creating spaces where everyone feels valued and heard. This shift can also attract a wider talent pool, which is essential in an era where skill shortages are prevalent. However, this journey will not be without challenges. Changing workplace cultures takes time and commitment from all of us. We must each play a part in supporting our colleagues and advocating for equality in every room we occupy. I encourage all my connections to reflect on their experiences and share how they might contribute to this transformation. What strategies are you using to promote diversity and inclusion in your workplace? Let's continue this important conversation. 💬 #WomenInTech #Diversity #AI #Innovation https://buff.ly/4fzuQcT #WomenInTech #AIInnovation #WomenInAI #TechLeadership #SheLeads #WomenEngineering #AICommunity #JeevaTech

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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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Congratulations to the #Observability Product and Engineering teams on the launch of Log Manager & Insights, now in beta! Log Manager and Insights enables you to proactively store, inspect, and monitor your log data on the Fastly Platform as an alternative to sending it to one of Fastly's supported third-party logging endpoints. We surface key insights you need for monitoring without requiring you to build complex data pipelines, so you can focus on delivering value and optimizing your customers’ experiences. 

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Key management needs to evolve from manual processes and centralized key storage to scalable, automated solutions to meet today's operational and security demands. I discuss this shift, the importance of workload-specific IDPs, and reducing reliance on shared secrets in my latest blog post.

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While attending a conference recently, I had a conversation with a leading technology CTO. His concern was simple but powerful: ‘Our current system is rigid. It slows us down.’ He went on to explain how their data infrastructure, though powerful, couldn’t keep up with the company’s evolving needs. This is a problem many businesses face today. Systems that were once state-of-the-art are now inflexible, unable to adapt to new demands. That’s why composability is so important. It’s about breaking down monolithic structures and allowing businesses to innovate at their own pace. At Syntasa, we’ve built a composable CDP that enables companies to add or remove data capabilities as needed — without disruption. Imagine running your marketing campaigns with the freedom to experiment, pivot, and grow without being held back by your tech stack. Composability is the new agility, and it’s time every company embraces it. https://lnkd.in/eWBJAzGb

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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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We are pleased to announce that you can now achieve up to an aggregate 1.3 million I/O operations per second (IOPS) and 12 GB/s throughput per OCI compute instance with the OCI Block Volume Service. In addition, you can also attach up to 32 Ultra High Performance (UHP) volumes to a single OCI compute instance. This service update is particularly useful for high I/O workloads, such as OLTP, AI/ML, data warehousing and analytics, databases with large data sets and extensive complex processing. https://lnkd.in/eHErX5mC

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Some nice points from Chris My personal opinion is that: Security is going through a phase that the Observability market went through in the previous decade. Observability market went through 4 phases: 1. Point solutions, 2. Emerging solutions for emerging tech and process 3. Followed by consolidation and platformization. Large companies acquired several start ups. 4. Finally AI hoping to make sense of the overwhelming disconnected data and this part is still being worked on. Sounds familiar? Exactly what we see in Cybersecurity now. In my opinion the next thing would be the consolidation of Observability and Cybersecurity which probably already started with Cisco's acquisition of Splunk, Appd, Thousandeyes and now their renewed emphasis on Cybersecurity. In both the scenarios a tool on its own is as effective as the People and the Process of an organisation. #platformization #cybersecurity

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Challenges of AI Networking for hyperscalers and enterprises Sept 27, 2024 I had the opportunity to meet with Manohar Paluri, VP of AI at Meta, this evening at the AI Tech Leaders Club, just under 24 hours before the AI Infra Summit on September 27, 2024. It’s been confirmed that the large training cluster at 500K GPUs is the next frontier for the hyperscaler industry. Meanwhile, on the enterprise side, standalone cluster sizes typically range from 20K to much smaller setups for retraining and inference. From my experience, while the challenges in these two sectors are intertwined, they can still be stated separately. 1) Checkpointing Challenges: Large GPU clusters require numerous checkpoints to maintain system reliability. The industry has recently implemented networking and checkpointing solutions for clusters with around 20K GPUs. Imagine the challenges we’ll face at the scale of 500K GPUs! 2) GPU Utilization: Typical GPU utilization hovers around 20%. While hyperscalers may achieve better numbers, overall utilization remains low. For this, a startup came up a clever solution to power down the idle GPUs dynamically to save up to 60% of power consumption from a GPU cluster. This approach could either reduce power usage from idle GPUs or, in conjunction with increased GPU utilization through further resources sharing—like memory, network, and model partitioning/parallelization—enhance overall efficiency. 3) Deployment Flexibility: The deployment of data center networks (hyperscaler cloud) or private networks (on-premises) for enterprises often lacks the necessary flexibility. For more insight, I recommend reading the justification for Google’s Optical Circuit Switching (OCS) network. Following conventional practices without innovative solutions can lead to over-investment in AI and cloud infrastructure. 4) ROI Optimization: Classic cloud infrastructure is often not optimized for ROI in AI networking, which leads to operational challenges for enterprises. To understand this, a little involved discussion is needed. Once understood, it becomes part of your instinct. Consider the competitive disadvantage faced by businesses that optimize ROI in their AI networks. Free Takeaway from me: Conversations about the challenges of AI infrastructure and networking are very welcome at the AI Infra Summit, and participants will receive the latest AI networking problem slide! 😊

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