Sara Bi

I wrote an article on how we translate user-generated content at scale at Mercari. It summarizes two years of work with various models, LLMs but not only, and how cost evolved, reducing it 100x over the period. I also go over non-AI features and user experience. https://lnkd.in/gbpQAQmX

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LambdaTest has officially rebranded to TestMu AI. 🚀 The Shift to "Agentic" AI is pivoting from being a standard test execution platform to an "Agentic Quality Engineering Platform."

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Cherrypick is an app that finds recipes, plans meals and orders groceries from supermarkets - with an AI twist. Helping 500k+ users eat better, it encourages healthy eating and reduces waste with thousands of AI recipes. Read the full story → https://lnkd.in/gSJAuRwN

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Grammarly isn’t just fixing grammar-welcome its agentic productivity fabric. With the acquisition of Superhuman and its earlier purchase of Coda, Grammarly is doing what Microsoft and Google haven’t fully pulled off yet—connecting where work happens (email, writing, collaboration) to where AI acts and the tools and processes your employees already use. • Start with ubiquity (Grammarly’s 30M+ daily users) • Fill the action gap with Superhuman (real-time, high-frequency decisions in email as one type of task execution) • Orchestrate the outputs in Coda (shared workspaces, structured knowledge, agent coordination ... and a contextual layer for coordination and memory) This isn’t just about “better writing.” It’s an architectural play for CDAOs and AI leaders to understand as they plan for AI-driven work transformation: 1. Intelligence is now a substrate of work as Grammerly works across your apps creating a new set of data that is largely invisible to IT. 2. Keep an eye on "shadow AI" as superhuman/coda will not just see emails, it will house strategic plans, roadmaps, customer data, etc. 3. Review how you acquire solutions as this stack has the potential to absorb countless "long-tail" AI use cases. Grammerly is moving: Start with ubiquity. Embed intelligent actions in the inbox. Orchestrate in the workspace. Your question is how to keep atop implications to your data-to-decision stack. What’s your take—will Grammarly become the agentic OS for knowledge work? Read more from Larry Dignan: http://bit.ly/44Jo8OV #AI #CDAO #ProductivityAI #AgenticWorkflows #DataToDecision #Grammarly #Superhuman #Coda #ConstellationResearch #AIPlatform

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Anthropic's Claude Sonnet 4.5 is coming to Glean this week. In addition to being the leading model for coding, our evals show that the model delivers significant improvements over its predecessor by efficiently solving 10% of previously unanswerable enterprise queries, thanks to optimized parallel tool calling and fewer planning iterations. See more details on our blog: https://lnkd.in/gXUEvGKW

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Meta reported our Q4 and full-year 2025 earnings last night. Our total revenue grew 24% year-over-year to $59.9 billion. This is what defined our platforms in 2025: ⬆️ Scale: More than 3.5B people now use at least one of our apps every day – including 2B+ daily active people on Facebook and close to that on Instagram. 🤖AI continues to enhance our services. In Q4, AI-driven optimizations led to a 7% lift in views of organic Feed and video posts on Facebook. ⏩ Video: Watch time on Instagram Reels in the US increased 30%+ YoY, and video time on Facebook grew double digits YoY in the US. 💬 AI + Business Messaging. We’re heavily integrating AI into business messaging to move beyond simple communication toward complex tasks. 🧵 Threads: As previously announced, we’re expanding ads on Threads to the remaining countries this month, including the EU. 🧠 What’s next in AI: “Personal superintelligence” is coming – AI that can understand personal context, including our history, interests, content, relationships, and preferences. We expect 2026 to be the year AI agents begin to meaningfully transform internal workflows and we’re already seeing strong signals including early productivity gains from agentic tools. Excited for what’s ahead for our CEE businesses!

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🚀 Reimagining Product Discovery at Scale As part of our 2025 reset, we ran dual-location discovery workshops for our stakeholders situated across 🇮🇩🇬🇧🇸🇬🇲🇾🇮🇳 to align cross-functional teams around a shared vision. Our prioritization lens🔎 • Impact/Urgency matrix ⚓️ • Strategic themes (time-boxed bets) ⚡️ • OKR alignment 📊 • Client urgency & revenue impact 💰 • Voice of customer across Sales, Ops, CS, and Partners 🏬 What this delivered: 💪🏻 ✅ Data-driven prioritization with an impact-vs-cost view ✅ Stronger alignment across hubs and functions ✅ A clear 2025 roadmap shaped with Engineering from day one ✅ Tighter collaboration rhythms for Product × Tech × GTM If you’re scaling discovery across locations and want to compare notes, happy to share playbook*. Comment - "Discovery", I will be happy to share it #productleadership #productdiscovery #roadmapping #productstrategy #crossfunctional #b2b #saas #orgdesign #uxresearch #engineering #innovation (*Views are my own. High-level methods only; no confidential details.)

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We’re bringing AppTweak Amplify back to APAC—and this one feels different. Two big realities shaping the conversations this year: First, ASO is no longer optional: With rising acquisition costs and more competition in the stores, your product page is directly impacting ROI. If it’s not optimized, you’re paying for it - literally. Second, AI is starting to change how growth teams operate: We’ll be introducing our new AI agent, built to help teams move faster on ASO, Apple Ads, surface opportunities earlier, and spend less time digging through data. We’re hosting across four markets, each with very different dynamics. Register here: 🇰🇷 Korea: https://lnkd.in/eCbWM_QN 🇻🇳 Hanoi: https://lnkd.in/e_ZPAbJ2 🇮🇳 Bengaluru: https://lnkd.in/eQEssNW3 🇯🇵 Japan: https://lnkd.in/ewHhBJT3 If you’re working on mobile growth, this will be a practical session.

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In just 90 days, Shutterstock delivered 115+ PB of content while reducing storage and delivery costs—with predictable global performance. - https://lnkd.in/gGZAJW9k

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When we were planning the Productboard Spark public beta, our initial instinct was to release it quietly. Save the bigger push for when we hit GA. But we kept coming back to the same question: why are we holding back? So we made a different call. We decided to go big, to talk openly about what we were building, and to bring people along for the ride as we were doing it, not after. That's what building in public means to me. It's not a campaign tactic. It's a mindset shift that touches everyone at the company. Product, engineering, marketing, people, finance—everyone sharing how they're using Spark, what they're learning, what's surprising them. The whole journey, not just the highlight reel. Here's what that actually looks like in practice: Make it everyone's job, not just marketing's. Every person at Productboard regardless of team, was asked to share how they use Spark in their day to day. Not polished campaigns. Just real, honest usage. Use it as a feedback engine. We're refining our messaging week over week based on what's actually landing — not waiting on a quarterly research cycle or lengthy user testing. The community tells you fast. Let it replace the blank page. One of my favorite examples: I used Spark to synthesize everything our CEO has written about AI into a cohesive narrative. What would have taken weeks of back and forth took a fraction of the time. When we put it in front of him, nothing felt out of place. Start small if it feels uncomfortable. Building in public isn't natural for everyone. It doesn't have to be an elaborate post or a big thought leadership piece. You build the muscle over time. From a product marketing perspective, this has been genuinely energizing. We're getting real feedback in real time. We're building relationships with the product management community, people who deeply understand the value of iterating in the open. I've done more traditional launches before. The kind where you hold everything close and wait for the perfect moment. There's a logic to that approach. But in a space moving as fast as AI is right now, I think there's more to be gained from showing your work than from waiting until it's polished. We're still learning. And honestly, that's kind of the point.

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🚀 Big news for Adobe Commerce developers and partners! As we prepare for the GA of Adobe Commerce as a Cloud Service (ACCS) and Adobe Commerce Optimizer (ACO) this June, we’re excited to announce that the Commerce Integration Starter Kit v2.0.0 is now live and fully compatible with both platforms! The Starter Kit serves as a foundation for building integrations faster and more reliably on ACCS and ACO. Whether you're launching new apps or migrating existing ones, this release helps you accelerate your journey with updated authentication, improved API clients, and streamlined setup for cloud environments. Making your Apps compatible with PaaS, ACCS, and ACO is now even simpler. 🔑 Key highlights: - Full support for ACCS and IMS-based authentication - Updated API clients - Updated environment configuration and migration guidance ⚡ Start building today: 👉 Release notes: https://lnkd.in/dmVQ5-Ph 👉 Docs and migration guide: https://lnkd.in/dR6EdDJA Have feedback or questions? Feel free to open a GitHub issue or join the conversation in our #app-builder-starter-kit channel on the Community Slack workspace. Let’s build what’s next together! 🌟 #AdobeCommerce #ACCS #ACO #AppBuilder

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Proud to see BigCommerce featured as a platform partner in Stripe’s newly announced Agentic Commerce Suite. This collaboration will give merchants an easier path to agent-driven discovery and checkout, without needing to rebuild their catalogs or rework their backend systems. It is a major step toward making agentic commerce real and accessible for the industry. 👉 Take a moment to read Stripe’s full announcement: https://lnkd.in/ganux9Gf

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Investors take note. The Sass-pocalypse is overly sold off. Innovation and AI adoption will look like this going forward. Time tested platform and capablities, like Intuit, combined with agentic orchestration. Both pieces create the big wins for customers.

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WordPress eCommerce Landscape is Going to Change in 2 hours 🔥 Zero transaction fees. 3x faster checkouts. Built-in subscription management. One plugin instead of fifteen. FluentCart is about to save you thousands while making your store faster.

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AI monetization across the world is ramping up in ecommerce. Ever heard of Shoppee Group? I hadn’t but they posted stellar 22% YoY growth in Q2, reaching $28.6 billion across Southeast Asia and Latin America. Growth is driven by AI-fueled ad tools like Shopee Live Ads and GMV Max. My take: AI powered seller tools are transforming ecommerce and innovation is heating up.

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This recent a16z article by Jason Cui and Jennifer Li on "Context Layers" affirms our company mission: https://lnkd.in/gURRJ9aa It's a great read. Anyone trying to deploy agents in the enterprise needs to read this. 𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗠𝗲𝘁𝗮𝗱𝗮𝘁𝗮 𝘁𝗼 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 The primary bottleneck for Enterprise AI isn’t model capability - it’s the missing architecture between raw data and agentic action. The "Context Layer" is the new competitive primitive. It sits between raw data and LLMs to provide the business logic, definitions, and "tribal knowledge" required for autonomy. It translates technical schemas into a format agents actually understand, ensuring they use authoritative metrics for reasoning. Traditional semantic layers from the BI era were passive abstractions designed for human-centric dashboards. A modern context layer must be agentic. It must be tool-aware, multimodal, and capable of self-correction. 𝗔 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗹𝗮𝘆𝗲𝗿 𝘁𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝗺𝗼𝗿𝗲 𝘄𝗶𝘁𝗵 𝗹𝗲𝘀𝘀 This is exactly what we are solving for at App Orchid Inc. While the market discusses the modern context layer as a concept, we have built the industrial-grade implementation with some added benefits beyond what a16z describes. ◆ 𝗦𝗲𝗹𝗳-𝗕𝗼𝗼𝘁𝘀𝘁𝗿𝗮𝗽𝗽𝗶𝗻𝗴 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗚𝗿𝗮𝗽𝗵: App Orchid will automatically identify business objects and semantics, generating descriptions and mapping structural relationships in a knowledge graph. This context graph can enrich itself with use. ◆ 𝗧𝗿𝗮𝗶𝘁-𝗕𝗮𝘀𝗲𝗱 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗮𝗴𝗲𝗻𝘁𝘀: We encode "Traits" (e.g. geospatial, time-series) that make agents answer common business questions with better fidelity. ◆ 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗣𝗼𝗿𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: By decoupling business logic from the storage or presentation layer, your AI doesn't lose its context if you migrate your data warehouse or switch BI tools. ◆ 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: We encode access and track interactions with data for transparency, auditability and governance. Read more about how we do it here: https://lnkd.in/gwFVcEfv 𝙎𝙤𝙢𝙚 𝙌𝙪𝙚𝙨𝙩𝙞𝙤𝙣𝙨 𝙛𝙤𝙧 𝙩𝙝𝙚 𝘾-𝙎𝙪𝙞𝙩𝙚 • Does your AI understand your "business vernacular" or just your SQL schema? • Is your business logic hard-coded into fragile prompts or is it a portable, governed asset? • Can your context layer ingest unstructured documents as easily as a structured table? If you aren't solving for context, you aren't building an AI strategy. You’re just buying expensive toys. #EnterpriseAI #ContextLayer #AgenticAI #AppOrchid #KnowledgeGraphs #MCP

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The way customers want to talk to brands is changing fast. Twilio’s new Conversational AI survey shows how builders are rethinking automation for real connection. Read the full report and chat with our interactive agent → https://bit.ly/448VnKK

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