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Matt Rappaport
Future Frontier Capital • 8K followers
Don't Build a Better Wheat Farm" - Why Defensibility Stakes Are Higher in Deep Tech Just published a new piece on my "Ignore the Confusion" blog, building on thoughtful insights from Eric Ver Ploeg at Tunitas Ventures about startup defensibility. Eric's core thesis: Too many startups pitch like wheat farmers - "huge TAM, slow incumbents, growing market, domain expertise" - but fail to think through long-term defensibility until it's too late. From a deep tech perspective, the stakes are even higher: ** Unlike software, deep tech founders must commit to defensibility strategies from day one - their funding depends on it ** Patent vs. trade secret decisions are often difficult to reverse and shape your entire competitive strategy ** Even "picks and shovels" providers (the tools that make industries more efficient) become commodities without proper moats The key insight that resonates: Defensibility can't be retrofitted. Whether you're building software or deep tech, your moat must be architected into the business model from the start. Thanks to Eric Ver Ploeg for sharing these insights on startup strategy and letting me build on his framework from a deep tech lens. Read the full post: https://lnkd.in/dEj_iF-Q #DeepTech #StartupStrategy #Defensibility #VentureCapital #Innovation
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Boris Sofman
Bedrock Robotics • 5K followers
We’ve raised $270 million in Series B funding for Bedrock Robotics to keep building the future of autonomous construction. This round was co-led by CapitalG, and the Valor Atreides AI Fund (Valor Equity Partners / Atreides Management, LP), with participation from Xora Innovation, 8VC, Eclipse, Emergence Capital, Perry Creek Capital, NVentures (NVIDIA venture capital arm), Tishman Speyer, Massachusetts Institute of Technology, Georgian, Incharge Capital Partners, C4 Ventures, and others—bringing our total funding to over $350 million. Thank you to Michael de la Merced and The New York Times for this morning's thoughtful coverage in Dealbook, linked in the comments below. The timing here matters. We're entering what may be the largest infrastructure buildout in history—data centers, energy systems, advanced manufacturing, and long-overdue modernization of roads and bridges. The capital and urgency is finally there, but construction needs nearly 800,000 workers over the next two years just to keep pace with today’s demands. This funding helps us scale our development and deployments, accelerating toward our first operator-less excavator work on partner sites this year. It's a first step toward a future where fully autonomous fleets could operate as coordinated systems, helping contractors take on more work and changing how they plan, staff, and build. Thank you to our investors, advisors, and industry partners building alongside us—and to the Bedrock team for enabling this enormous opportunity.
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AI Insider
17K followers
Phosphor Capital, founded by two-time YC alum Kulveer Taggar, has raised $34M across two funds to back startups emerging from the Y Combinator ecosystem. With 200+ YC companies already in the portfolio—including Circleback and Gumloop—Phosphor is doubling down on early-stage AI and software bets. Backed by Garry Tan, the firm brings founder-first energy to YC’s next wave of breakout startups. https://lnkd.in/eMP9scxT #VentureCapital #YCAlumni #AIStartups #EarlyStageFunding #FounderLed #SeedFunding #YCombinator
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John Melas-Kyriazi
Standard Metrics • 9K followers
We just shipped a few big upgrades to our VC/PE document management system at Standard Metrics. 📁 What started as a simple hub for board decks, financials, and cap tables has evolved into a standardized source of truth, with filtering, search, and custom labels built in. In light of the upcoming Aumni shutdown, we moved quickly and worked closely with new customers and prospects to design a more robust system for their documents going forward to support audits and more. (If that shift is affecting your firm too, we’d love to chat.) Check out the upgrades in action in the video below. We also wrote a quick blog post on why we built this, what’s launched, and what’s coming next: https://lnkd.in/dBmkD-Y5
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Shaun Johnson
9K followers
At AIX Ventures we have been focused on the application layer since we founded the firm in 2021. At that time we put together a simple framework to help us synthesize and discuss what we were seeing. In its simplest form, this is a measure of founder -> product fit (where the product now requires some level of AI nativeness) and founder -> market fit. The nuances are whether pure AI native teams can become commercial, and whether pure commercial teams can become sufficiently AI native. Now that the AI applications thesis is consensus and therefore very relevant, we're sharing this work. Many conversations I've had just this week, with VCs and founders alike, converge into a discussion of this framework. Just yesterday I was chatting with a fellow VC about this topic and they said "oh you were just in my previous partner meeting".
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Jordan Steiner, CFA
Developer Capital • 3K followers
"Build the event you wish existed" That's what we at Monadical did last week at #NYTW. We wanted an AI Engineers discussion for Engineers. There's always a lot of events out there for VCs to network, or for startups to learn about G2M, but very little on lessons learned from actual engineers in the field. So that's the event we hosted. Big thank yous to our awesome panel, Roy Pereira, Ben Cohen and Corey J. Gallon. Here's the key takeaways and the AI tools we're using. 🚀 All three panelists independently called AI Agents the most transformative LLM application they’ve used. They specifically called out Claude 3.5 Sonnet for its accuracy and reliability. 🪨 We dug into how LLMs are “jagged”, not general. They can be shockingly good at some tasks and completely fail at others. Everyone agreed: good evaluations are critical (and hard.) 🧪 Corey noted how public benchmarks and reality are two different things. Most public evals are saturated or gamed. ♊ Ben emphasized that AI projects are actually two projects: building the tool and building the evaluation process. 🧱 We explored how falling dev costs may impact startup defensibility and labor demand. Roy shared that founders are already shifting strategies in response. ⚒️ In a world of daily AI launches, the panel discussed how they decide what’s worth attention, and what’s just noise. They called out tools like Goose, Aider, Claude Code, and Monadical’s own Cubbi, which helps run agentic workflows safely in dev environments. (links in the comments). CTA: What would you want to hear in an AI Applied Engineering talk you attended?
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Jeffrey Evans
MANTIS Venture Capital • 2K followers
An often overlooked, yet highest-impact reality in venture capital right now: Software moats are near dead. AI-native tools and open-source models have removed much of the advantage from owning proprietary code or deploying complex infrastructure. A strong team can now quickly duplicate an existing software product or even stitch together a working product using off-the-shelf components and a week of hacking. This is changing everything. If software itself is at its least defensible position in history, then where does lasting value come from? We believe it now lies in things that are much harder to replicate: • Distribution channels with direct access to buyers • Network effects where each user improves the product's utility • Proprietary data that can't be easily sourced elsewhere • Deep customer relationships and trust • Strong brands that build community and emotional loyalty • Software-plus-hardware stacks creating complex technical moats Let me show you how this plays out in our portfolio: 1. 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧: Cloaked reached scale through a contrarian wedge into privacy-conscious Gen Z users who now onboard their entire households, flipping the legacy top-down model and powering growth to 130K paying customers with a path to $30M ARR. 2. 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 ���𝐟𝐟𝐞𝐜𝐭𝐬: Whop built a two-sided marketplace where every new creator listing brings more buyers, and every purchase draws more creators, creating a self-reinforcing flywheel that's powered billions in transactions across hundreds of thousands of listings. 3. 𝐏𝐫𝐨𝐩𝐫𝐢𝐞𝐭𝐚𝐫𝐲 𝐃𝐚𝐭𝐚: Pogo captures first-party purchase behavior and intent signals directly from users that are inaccessible to new entrants, positioning them to power the next generation of personalized AI commerce with a lean team. 4. 𝐓𝐫𝐮𝐬𝐭: Chainguard's CEO spent years earning the open source community's trust at Google, turning that reputation into the foundation for commercializing hardened enterprise-grade code and a company that is valued at over $3 billion. 5. 𝐃𝐞𝐞𝐩 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩𝐬: Dandy's fully-digital lab delivers crowns with such low remake rates that dentists save 30-45 minutes per patient and route their entire lab budget to them, tightening churn to under one percent. 6.𝐁𝐫𝐚𝐧𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: Superhuman's invite-only onboarding and white-glove support forged such emotional loyalty that users behave as volunteer sales reps, leading Grammarly to acquire them citing "cult-level engagement" as the real asset. 7. 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐌𝐨𝐚𝐭: AIM combines advanced software with proprietary hardware to transform earthmoving, embedding itself as mission-critical infrastructure that improves as it collects real-world data across mining and construction fleets. This shift is especially relevant in early-stage investing, where traditional software benchmarks like ARR or gross margin may no longer predict long-term strength. The venture playbook has changed.
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Village Global
25K followers
Stealth is not a long-term strategy. Aaron Harris built YC's Series A program and has helped founders raise billions. He argues that by Series A, building in secret means you're missing critical information on where investors are actually excited. Great founders decide if they truly need capital, run live-market reads, then jump into their fundraise when the wave is cresting.
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Christian Gonzalez, PhD
Planet A Ventures • 4K followers
MATERIALS! My take: The 2026 story is less about novelty and more about cracking scalability and cost. In Hack, I shared what I'm excited about this year: 🏭1. AI for Material Discovery (and cheaper manufacturing) Fewer candidates, faster iterations, and quicker validation cycles from concept to prototype. An obvious win is improving manufacturability - using models not just to find “best-in-class” materials, but to find materials that can actually be produced reliably and at lower cost. 🚜2. New Electrochemical Materials (efficiency-first pathways) Some chemical reactions for existing industrial processes are ready for a new spin: material and paired cell design innovation that boosts efficiency. The result? Better yields and lower energy intensity can be enough to change unit economics. A wave of scalable (and potentially local production!) technologies spanning fertilisers and chemical commodities, where scale and cost are everything, and where incremental efficiency gains can unlock big emissions reductions are reaching maturity. Added bonus to look for: replacing precious metals. 📈3. New Bio-Based Materials (scaling fermentation and biomaterials) Several companies appear close to the tipping point where process optimisation, feedstock strategy, and downstream processing finally align and are ready to commercialize. A massive win for the bioeconomy. Watch this space! Read the whole piece here! https://lnkd.in/ec8Tad4V
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