Vivek Vaidya

During yesterday's LibreQoS APNIC webinar, I posed the question: won't more bandwidth solve these problems? As Herbert Wolverson said, yes, more bandwidth is good, but, still these problems remain if queueing is done incorrectly. Here's my take on why bandwidth alone is not as good as bandwidth good queueing policies: Generally it was believed that 'data is important, so don't throw it away; hang on to it and send it later'. In practice, this has proven to be suboptimal as two issues may emerge: 1) latency increases for some flows due to heavy demand from other flows using the same bottleneck link, 2) even a single flow can have excessive latency due to aspects of typical TCP behavior (referred to bufferbloat) when the buffers grew large enough that the data being buffered was retransmitted anyway. It turns out that not all data is equally important. Active Queue Management is the art of deciding priorities, both in deciding what data to throw away, but also in allowing some later arriving data to be transmitted ahead of data in another connection that arrived before it. These problems have been studied, and good solutions have been found by using certain queueing policies in routers and switches, referred to as “fq_codel’ and “cake”. These track the different flows not by classifying the data, but by watching the behavior. Flows that send relatively little data (DNS lookups), or at a measured pace (video chat) have priority over flows that send a lot of data as quickly as possible (App and System updates, Video and ISO downloads).

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The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

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DeepCast shipped a number of really cool new features recently in advance of a broad outreach push to podcast listeners. One new feature is our new Daily DeepDigest tool that sends you a concise daily email including any new episodes from the trailing 24 hours from any podcasts you Subscribe to (on DeepCast). Think daily podcast cliff notes or podcast news ticker tape, with a hint of Morning Brew various brews or PitchBook News—it's increasing information throughput when you're pressed for time. And this feature is rapidly evolving to distill other key extractions from shows you're already interested in, but also exposing you to other shows you might be unfamiliar with that also have nuggets to share—and thus increasing your aperture yet still conscious of your time. Want to go deeper on any given episode? Click the episode detail and you're off to an episode on DeepCast, where you can subsequently read a longer form distillation of that episode or go straight to the source and listen to the episode. (And podcaster friends, these pages are definitely increasing indexing and thus Google entry points to your shows!) I'm loving this feature as a user, personally. Can't wait to see what others think! #BuildingInPublic #Podcasts #AllTheWorldsInformation #HowYouWantIt

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Hiring a Founding AE with 2-3 years of experience? Without clarity, face a great honeymoon but miserable marriage.  In a recent discussion with a coach of B2B sellers, she shared that the boom of 2020-2023 saw many sellers become order takers and lose their skills. The need to prospect went down and sellers working with eager buyers forgot how to create the momentum early in the sales process. Another trend is job openings for Founding AEs looking for 2-3 years of experience. This seems to be motivated by investor instructions to “keep things lean.” I’m all for lean, but make sure to look for some key AE traits to make sure you’re getting full value out of your precious cash. Simple things to look for: -Startup experience. Be extremely cautious of hiring sales reps who have only worked in enterprise companies. I hired a rep once who fit this profile who was talented at getting people on the phone but couldn’t build his own prospecting lists in salesforce given he was use to having someone do it for him. Not a good match. Ask for details around how they would setup their day to prospect, have they created their own decks, how would they run a POC, etc. Listen for the details and ask for examples. -Domain knowledge. Look for AEs who have sold to the ICPs you are targeting. If you have a product for developers, find someone who’s sold into that persona. If you have a RevOps tool, Marketing, etc. Ask for them to explain what’s unique about the persona they have experience with. -Company size experience. Early stage startups buy from each other. That’s part of the fun of a startup - the community and supporting each other. It’s a fast-paced transactional selling environment easily managed through PLG or an SMB sales motion. If you want to sell to enterprise, you need someone with that experience. It’s totally different momentum and skillset of navigating enterprise. Examples are powerful here. Ask them to describe a deal from start to finish and highlight what actions they took and who on their team was involved. Founders are busy. This list is simple and obvious but it will help you quickly screen for the skillset you need before you interview. I’d suggest even including questions on your job application. Looking at LinkedIn it seems each open role is getting hundreds of applicants within days so to save your sanity take an extra 10 min and include some open ended questions about this stuff on the submission form. Too many founders hire inexperienced sellers who are the wrong fit in terms of skillset -  prioritizing budget over effectiveness. As a result they hire someone who is cheap but does not perform. Think about other creative ways to hire an experienced sales executive or GTM leader and compensate more on commission percentage and equity than base salary. Al Rey and I are talking about this topic and other GTM challenges faced by Seed Founders at our event in June. Check it out here:

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Navigating AI with the Maturity Model in Revenue Organizations Over the last several weeks, I've been crafting a conceptual framework at RevShoppe, focusing on AI integration within revenue teams. Drawing on discussions with Manny Medina to refine my ideas, we've developed an AI maturity model that offers a structured framework, segmented into four progressive quadrants, each representing a unique blend of human and AI involvement. This model isn't merely about adopting AI; it provides a lens through which organizations can initially approach and think about AI integration. It addresses essential questions such as "How do I introduce AI into my sales organization?", "When is the right time to consider AI for my business?", and "Where can AI deliver the most significant impact, ROI, or improvement in sales efficiency?" In a field quickly becoming crowded with emerging "AI companies," this framework aims to guide your strategic planning and initial considerations for effectively integrating AI within your organization. Each quadrant not only signifies the level of AI integration but also guides organizations on the pathway from initial adoption to full autonomy.  Think of this 2x2 as both: ▶ A roadmap on how to get the most out of AI in the GTM organization ▶ A maturity model to figure out how advanced your organization is in harnessing the full power of AI and getting the benefits of efficiency and productivity (as well as understanding AI’s capabilities today) The model is to be consumed in a Z pattern beginning with Human-Led, Human Assisted where most organizations are today, moving through AI Assisted to AI-led, and eventually shifting full workflows to AI making more time for the human seller and managers to do the things we are uniquely competent at. This approach ensures that your organization can adapt as AI becomes capable of handling more complex functions, seamlessly transitioning tasks from human to machine as the technology advances. Over the next 4 posts I will be getting into the details of what each of the 4 stages mean, what it takes to progress from one to the next, and how to measure the impact of AI maturity and adoption in your organization In the meantime, I would love your feedback breaking down AI maturity with this framework. #AI #AIMaturity #RevShoppe #Salestransformation

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Product-Market Fit and Trust: Why the CEO and the rest of the C-Suite Must Rally Behind the CMO Last week, I shared in a post (https://lnkd.in/gV-tuPRP) a matrix exploring the critical relationship between Product-Market Fit (PMF) and Trust in B2B. These are two fundamental aspects at the core of marketing's mission. Today, I'm highlighting why these CMO-led initiatives demand active support from CEOs and the entire C-suite. A new report from CMO Huddles, "Underground Recession: The Hidden Strain on B2B CMOs" (https://lnkd.in/gTR7qb8C), shows tough realities like budget cuts and longer deal cycles. These symptoms point to deeper, strategic marketing challenges that impact the entire organization. My hypothesis is that B2B companies are struggling with foundational marketing challenges in PMF and/or customer trust. Here's why: ► Profitability Shift - "Growth at all costs" to sustainable profitability requires reassessing PMF. ► Evolving Buyer Expectations - B2B buyers prefer known entities and peer recommendations. ► AI Innovation - Rapid tech advancements need company-wide support, especially addressing data privacy concerns. Remember that just as we can't out-exercise a bad diet, we can't out-campaign a bad product-market fit. C-suite leaders must rally behind marketing to address PMF and trust-building. No company is immune; even tech giants are reassessing. Some key reasons to revisit PMF include: ► AI Integration ► Upmarket Expansion ► Augmenting with Product-Led Growth ► Regulatory Changes ► Post-Pandemic Market Evolution Marketing leaders are driving these critical conversations but need full C-suite engagement. The PMF and Trust matrix illustrates marketing's strategic impact on the entire business. Where does your company truly stand on PMF and Trust? How is your entire C-suite collaborating with marketing to adapt to these seismic B2B shifts? Note: I built the dynamic product-market fit vs trust matrix below using natural language with Claude Sonnet 3.5 artifacts. #MarketingStrategy #ProductMarketFit #CustomerTrust #AI #CMO GrowthPath Partners

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Ever since we launched SHAKTI, every quarter we write a letter to our LPs = Each letter includes an update on the portfolios, the GP's (our) view on the zeitgeist, an interview with a portfolio CEO and an interview with a TITAN = So far, we have 16 such letters = it's been on our "to do" list to share these publicly (i am lazy) = then Google comes along to save lazy people like me (thank you NotebookLLM) = here's a 10 min podcast summarizing our journey since Dec/2020 with the 16 LP letters as source = if you wanted to know what we are about, this is a pretty good place to start = https://lnkd.in/db7K2TrT cc SHAKTI

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Interesting concept to rename rounds by milestones. But "Series Client Expansion Extension" just doesn't have the same ring to it 😋 . Maybe we can start incorporating it into a descriptor to add context, "Series Seed Extension: client expansion." #startups #venturecapital

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