Abhinav Asthana

ambaricloud: 108 recipes. 🥭 https://lnkd.in/gS6fuAtu Ravi Kiran Gurram Anil Koripelly Bhushan Lakhe Raja Purkayastha When this recipe e-book was first published on January 1, 2025, our goal was to give engineers, architects, and data practitioners a hands-on guide to Apache Iceberg. In the months since, the pace of change has been remarkable. Platforms such as Snowflake, Databricks, Dremio, RisingWave, ClickHouse, Cloudera, Lakekeeper, Trino Software Foundation, and Amazon Web Services (AWS) have delivered significant new integrations, and Apache Iceberg itself has reached version 1.10.0, introducing capabilities that reshape how practitioners interact with the format. To reflect this momentum, we are undertaking a ground-up rewrite. Our priorities include: ✅ Iceberg 1.10.0 alignment and deprecation cleanup – removing outdated recipes that no longer reflect best practices while upgrading all demos, examples, and exercises to incorporate the changes introduced in Iceberg 1.10.0. For example, Snowflake’s support for catalog-linked databases to external catalogs makes earlier object integration recipes obsolete. ✅ Ecosystem validation – testing and refining recipes across Databricks, Snowflake, Dremio, and AWS to ensure seamless interoperability with Iceberg 1.10.0. We expect this rewrite to take two to three months. Once complete, this edition will provide readers with a technically accurate, future-ready reference for Iceberg 1.10.0 and its surrounding ecosystems--Snowflake, Databricks, Dremio, RisingWave, ClickHouse, Cloudera, Lakekeeper, Trino Software Foundation, and Amazon Web Services (AWS) Please 🕺 suggest 🔪 comment 🥃 recommend ✅ Spark Variant ---Iceberg1.10.0 spports now. https://lnkd.in/gBmaNrPH

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Jyoti Bansal joins Mudassar Malik for the Season 4 premiere of The Builders Playbook to share an honest look at scaling without losing quality, speed, or accountability. They dig into Jyoti’s journey from engineer to founder, the investor question that pushed him to go all-in on AppDynamics, and the lessons he brings to building at Harness today. You’ll hear about: ✓ Turning one focused use case into a platform. ✓ Harness’s “startup within a startup” model. ✓ Why small, AI-enabled teams move faster. 🎧 If you’re building or scaling, this one’s packed with practical takeaways: https://lnkd.in/g3Y9P3rF

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The first mover advantage in a regulated top down ecosystem (you know which all I’m talking about - money, data, identity, travel and food, bills, health records) is often achieved by the person/company who is/was very close to the think tank (often the one who co-wrote the specification) which made them top down. It’s impossible to beat this with innovation and effort, as they simply are a result of favoritism. It often takes decades to shake them down of their pedestal.

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On the latest episode of Embracing Erosion I sat down with Suyog Deshpande, Co-Founder & CEO of Webless (a Fluvio Ventures portfolio company). Before starting Webless, Suyog spent years at Amplitude, Salesforce, and Samsara - shaping products and GTM strategy at scale as a product marketing leader. That perspective is now fueling one of the boldest bets in tech: 🏗️ rebuilding the web for LLMs. Instead of optimizing for clicks and SEO, Webless imagines an agentic web -where sites are designed to interact directly with AI models and agents. We dug into: - What an LLM-native web could actually look like - How companies can prepare to be LLM-ready - What metrics will matter beyond pageviews and clicks - Why safety and trust are core to agent-driven experiences - Lessons Suyog brings from “big tech” into this transformation If you’re curious about how discovery, trust, and value exchange will evolve online, this one’s worth your time. Link to the full episode in the comments 👇

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🚀 The Chariot: A Startup Story 1️⃣ The Perfect Start Startup horses pull a single chariot. Everyone joins the harness at the same moment — aligned strength, shared purpose. Founders steady on the reins. Early customers trusting the motion. Stride synced. Weakness covered. Progress effortless. 2️⃣ When the Terrain Shifts Horses slow. Some drop out. A new charioteer may appear, demanding speed. Pressure rises. Motivation dips. Trust cracks. Yet the chariot must move — customers expect it. 3️⃣ The Hidden Cost Slow down → risk collapse. Speed up → risk burnout. The journey reveals everything the starting moment conceals. 4️⃣ The Uncomfortable Truth You can’t evaluate every variable before joining. You don’t know: • how many customers will jump in • how fast their load will grow • when teammates will fall out • when leadership changes mid-journey • how unpredictable the terrain becomes 5️⃣ The Discipline That Keeps You Alive Once harnessed, continuous evaluation becomes mandatory. Never assume the load, the team, or the terrain will stay constant. Alignment is not a one-time act — it’s a recurring adjustment. Prepare for customer load increases early, not when you’re already collapsing under it. 6️⃣ What a Horse Must Understand • Your endurance in real conditions • How much drag you can cover without breaking • How much pressure you can absorb from the driver • The moment the cost of pulling exceeds the value of the journey 7️⃣ The Core Principle Choose wisely when you can. Re-evaluate relentlessly when you must. The beginning is beautiful. The truth appears only in the miles ahead. 🔍 Before — and during — any journey: • Inspect the chariot • Understand the horses beside you • Track customer load as it grows • Watch how charioteers behave under pressure • Study the terrain you’re on, not the one you were promised ❓ What do you look for before — and while — riding the chariot?

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Most people who buy Clay stop using it within a week. Not because it's hard to learn - because they open it and have no idea what to build. We kicked off Module 1 of GTM Engineering School last week with Yash Tekriwal 🤔 from Clay's team. He nailed the core problem right out of the gate: 60-70% of AI GTM work happens outside the tool. He calls it the "imagination gap" - the distance between what's actually possible with these tools and what most people settle for. Here's what settling looks like: pull a list, enrich with email and job title, generate an AI cold email, send it. If that took you 20 minutes to build, your competitors built the same thing in 20 minutes too. That's not a competitive advantage. That's a commodity. The teams winning with Clay are doing something different. They're brainstorming creative data points before they ever open the tool. Two examples from the session that stuck with me - a warehousing software company analyzing satellite images of parking lots to estimate warehouse capacity and prioritize outreach. A healthcare company estimating hospital bed counts by crawling building square footage because hospitals don't publish that data. Nobody else has those signals. That's the advantage. Yash walked the class through a simple framework to get there. You can do this in Claude or ChatGPT in 15 minutes before you touch Clay: ▸ What is the exact pain your product solves? ▸ Who feels that pain most acutely right now? ▸ What titles and roles would you actually want to reach? ▸ What data points - beyond the ones everyone else uses - would tell you someone is a great fit? That last question is the whole game. Don't settle for "raised a Series B" or "hiring for sales." Think about what a human researcher would look for with unlimited time. That's what you should be automating. Do this before you open Clay. The blank canvas stops being intimidating when you walk in with a blueprint.

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People often ask - why is Vapi developer-first? Early at Vapi, I pushed to build a simplified platform- abstract the complexity, design clean interfaces, and make it easy for PMs to adopt. With abstraction, we were also more enterprise-friendly. Nikhil completely disagreed. He pushed for exposing everything - logs, models, transparent pricing. He argued developers would eventually demand that level of control once they saw how hard voice AI really is. At the time, I wasn’t convinced. But the market proved him right. Developers wanted more control, they got smarter, they taught themselves the voice stack and got opinionated about every part of it. They’re debugging brittle APIs at 2 AM and deciding whether your platform feels like an extension of their stack or a black box they can’t trust. Developers decide if we will survive. That’s why Vapi is, and will always be- developer-first.

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Moving fast is easy when you’re small, but harder when you’re building at global scale. Prashant Verma's recent conversation with ETGCCWorld looks at how Harness is structured to handle both with its “startup within a startup” model giving teams real ownership over features and outcomes. That structure shows up clearly in the work happening out of India, where teams are building products like AI SRE and resiliency testing to help companies manage production environments more effectively. If you’re interested in how global engineering teams stay nimble as they grow, this is a good read. Read the full article: https://lnkd.in/gPKBhZ8U

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Jyoti Bansal joins Mudassar Malik for the Season 4 premiere of The Builders Playbook to share an honest look at scaling without losing quality, speed, or accountability. They dig into Jyoti’s journey from engineer to founder, the investor question that pushed him to go all-in on AppDynamics, and the lessons he brings to building at Harness today. You’ll hear about: ✓ Turning one focused use case into a platform. ✓ Harness’s “startup within a startup” model. ✓ Why small, AI-enabled teams move faster. 🎧 If you’re building or scaling, this one’s packed with practical takeaways: https://lnkd.in/enrHvuU3

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