Mo (Mohamad) Afshar

This episode of Sequoia Capital's "Crucible Moments" series offers a fascinating look into MongoDB's journey from a startup to a cloud platform powerhouse. It takes us through the company's journey, from when our founder, wight Merriman, created a product in 2007 that developers adored and then overcame the challenges of scaling it, to the shift from on-premise software to Atlas, our developer data platform. Today, as we approach $2 billion in annual revenue, I'm proud to say that MongoDB has evolved into much more than a niche database. We're now a comprehensive data platform that puts its developers first and is constantly learning and evolving to meet the vision of our customers. Dive into the insights from Dwight Merriman, Dev Ittycheria, and Tom Killalea, taking you through the company's most critical moments and decisions. #MongoDB #cloudcomputing #developers

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Check out our blog series on tools (function calling)! We have posted part 1 of Friendli Tools, our state-of-the-art function calling with LLMs! #tools #functioncalling #llm #friendli #friendliai

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My session on "Debiasing the Data Lifecycle" from the recent PyTorch Conference is now live! It's a quick 11-minute video. Check it out and let me know what you think 😃 #pytorch #dataBias #womenInData

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Great insights into Gen AI adoption and trends, especially this: “ 1/ Generative AI has found screaming product-market fit in its first few breakout use cases: 🥇 Code copilots (51% adoption) - e.g., All Hands AI, Codeium, Harness 🥈 Support chatbots (31%) - e.g., Aisera, Decagon, Sierra 🥉 Enterprise search (28%) - e.g., Glean, Sana 2/ The foundation model landscape is shifting: …Anthropic doubled its enterprise share from 12% to 24% while OpenAI slipped from 50% to 34%. Closed-source models remained dominant vs open-source models (e.g., Llama) with 81% market share. “ #genaitrends

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As companies go multi-cloud in their deployments, we need stand alone MLOps/LLMOps solutions that can deployed across vs being dependent on any one platform. As developers use multiple code generators, we will need security solutions that go across all of them to support developers. As businesses use multiple LLMs/AI models/APIs across the enterprise, we will need stand alone solutions to help identify, implement, and secure data and use cases. These are great opportunities to build next gen independent large software companies.

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Some good perspective on how AI changes SaaS. Vertical Saas is here, horizontal SaaS is challenged. https://lnkd.in/gQQnPYPE

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Cool day. Llama 3.1 405B released this AM. CentML has it hosted live this afternoon (try it out below 👇). CentML also optimized it for higher throughput and lower latency based on its preferred compute stack. Planning to build with Llama 3.1 and beyond? CentML might save you millions (on top of what Meta is saving you), and help you deliver best-in-class experiences for your users.

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Stumbled upon this great little gem of a podcast episode from LinearB with Mark Robinson at Plaid "The Rise of Cloud Costs, and How to Optimize Them": "There’s a million little blind alleyways where you're spending money without realizing it. You might think, 'Someone set it up, it must be right,' only to find out it’s not. Amazon, for instance, charges a lot for networking fees. By default, they route all your S3 traffic externally, which incurs those fees. But if you flip this one little toggle to route it internally, it’s such a huge change. It’ll save you a fortune, especially if you use a lot of S3." I highly recommend checking this resource out: https://lnkd.in/g-aBJbEH

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Question for our friends in FinOps: Does software spending make it harder for you to run forecasts? The variable nature of SaaS licenses—especially based on the number of seats or usage—obscures visibility into associated costs. For companies managing a broad portfolio of SaaS applications, these variable costs can get complicated… fast. Here’s how our flexible, easy-to-deploy SaaS license management solution can help: ✅Monitor SaaS usage and costs to streamline forecasts ✅Analyze usage patterns to scale services up or down and pay only for what you use ✅Easily manage SaaS subscriptions in compliance with regulations and internal policies Get the transparency you need and eliminate the SaaS license costs that you don’t. #FinOps #FinanceOperations #SaaSLicenseManagement #SoftwareLicenseManagement #SoftwareLicense #Software #SaaS #ITServices

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Inevitably, tools enabling multi-agent orchestration are set to take center stage in the race to empower #B2B #enterprises to tackle tomorrow's most pressing challenges. These solutions offer dynamic frameworks that allow #AIAgents to interact autonomously in a harmonious flow, solving real-time challenges across departments. Such #innovations are redefining how organizations approach complex problem-solving, enabling AI systems to collaborate and adapt with unprecedented precision. Emilia David of VentureBeat shares an increibly insightful discussion with Amazon's Matt Garman, who explains AWS’s rationale for launching a multi-agent builder on Bedrock. Garman notes: "While a single agent can be useful, more complex tasks, like performing financial analysis across hundreds or thousands of different variables, may require a large number of agents with their own specializations." He adds:"However, creating a system that can coordinate multiple agents, share context across them, and dynamically route different tasks to the right agent requires specialized tools and generative AI expertise that many companies do not have available." With this move coming into play shortly after adding Anthropic's Claude 3.5 Haiku and the upgraded Sonnet 3.5 models to #Bedrock, AWS enters a highly competitive arena alongside Microsoft and Google. Microsoft's recent Magentic-One enables orchestrated collaboration between specialized agents, directed by a central orchestrator capable of dynamic planning and error recovery. Meanwhile, Google Cloud’s Vertex AI has consistently pushed the boundaries of generative AI by managing complex AI workflows and fostering multi-agent collaboration. This not only underscores that #AIAgents are one of the fastest-growing subsegments in #AI but also offers an exciting glimpse into the next generation of #enterprise #workflows. In my view, although it may take some time until it reaches full potential, this evolution will create a need for entirely new roles for us humans within organizations—ones dedicated to guard railing, managing, and orchestrating these intricate systems, much like a maestro conducting a grand opera. Autonomous agent collaboration is poised to reshape the #enterprise #AI landscape of today, driving innovation and coordination to the forefront of tomorrow’s solutions. #AI #AIAgents #Enterprisesolutions #AICapital #Google #AWS #Microsoft #VertexAI #Bedrock #MagenticOne #GCP #GoogleCloud #GenAI

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We've saved our customers $2.3M with a single AWS fixer. Here's how: BACKGROUND: Many companies are still using GP2 EBS volumes, unaware of the massive cost-saving potential in migrating to GP3. DISCOVERY: Our CloudFix team analyzed GP2 vs GP3 EBS volumes across customer accounts. What we found was striking. SOLUTION: We implemented our GP2 to GP3 fixer - a simple, automated change with profound impacts. RESULTS: $2.3M in customer savings to date Up to 35% reduction in storage costs per customer Performance boost: GP3 performs as well as or better than GP2 Increased operational flexibility with GP3's decoupled IOPS and throughput TAKEAWAY: Small technical optimizations can drive massive organizational savings. Are you leaving money on the table with your AWS spend?

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We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

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I think we're seeing the dawn of a new post-SaaS industry. Back in 2010s cloud ushered in SaaS and with it many new jobs and hugely valuable companies created. Today, we've seen the release of very early versions of this with Microsoft's 'autonomous agents' layer, Anthropic's new screen control capabilities and AgentForce from Salesforce. But if you look at the startups and early adopters we're seeing much more interesting activity. I spoke with Daniel of Relevance AI about how some customers are thinking about creating the role of an ‘AI Workforce Manager’– someone who is responsible for managing not people but AI agents in the business. When your customers are thinking about creating a new job to manage your software you know you’re onto something important! I wrote a few thoughts on what 'AI Agent Manager' might be and if this might signal a new market. 🔗 https://lnkd.in/gaqZn5C3

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Download our comprehensive VC contact list of #SanFrancisco Gain access to 275+ VC firms, 2100+ professionals, and 1600 emails. Get all the essential details: firm names, websites, stages, and more https://payhip.com/b/idx8b #startup #startups #venturecapital #funding #vc #privateequity

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AI advancements are transforming ITSM, incident response, and QA, enabling context-aware autopilot workflows that optimize efficiency, precision, and user experience. As complexity meets automation, the potential for disruption is immense! Felicis In this post, Tobi Coker and I share more context about the solutions in these spaces and how they are used: ITSM: Atomicwork Console Fixify Espressive Moveworks Ravenna Serval Risotto (YC W24) XOPS Incident response: with100x.dev Cleric DeductiveAI Flip AI Resolve AI Traversal.com QA: Heal.dev Meticulous Momentic Octomind QA.tech Ranger mobile.dev Spur (YC S24) https://lnkd.in/gR9AkrxN

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When the theme's a delight, we double our insight! We covered a lot of topics on creating a differentiated and winning GTM strategy for AI companies in this conversation with Poorvi Vijay. - Positioning and differentiation - Building a brand beyond the product - Focusing on ICP - Marketing channels - Hiring the right talent - Pricing to balance value and cost - How to get POCs going - and more.. :)

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SYNTASA + GOOGLE CLOUD = SUCCESS! Our synergistic collaboration with Google cloud holds immense potential for groundbreaking achievements. As you can see, the Google Cloud hat and Syntasa t-shirt symbolize the union of our expertise and shared vision. This strategic alliance is deeply ingrained in Syntasa's DNA, and we eagerly anticipate delivering remarkable solutions that redefine industry standards. Stay tuned for exciting updates as we embark on this transformative journey together, leveraging the power of innovation to drive impactful change. #success #genai #google #googlecloud #syntasa

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