At #Workflow26, Sigma Product Evangelist Katrina Menne and Field CTO Greg Bonnette walked attendees through the BUILD framework, Sigma's recommended approach for designing AI Apps. At a high level, BUILD breaks application design into five core components: B — Business Objective U — User Workflow I — Input Design L — Logic & Data Model D — Distribution & Adoption Using this framework, you can make sure the AI Apps you build get strong adoption and drive real outcomes in production. Learn more in the session recap blog: https://lnkd.in/gn6YPrRX
Sigma's BUILD Framework for AI App Design with Katrina Menne & Greg Bonnette
This title was summarized by AI from the post below.
More Relevant Posts
-
AI Builder brings an intelligent copilot directly into the Sigma workbook—helping teams build, design, and refine AI-powered apps through natural conversation. Describe the workflow you need, and AI Builder assembles the structure, logic, and interactions in minutes. Check out this demo from our December product launch on demand here: https://lnkd.in/e9jnw3Tc #SigmaProductLaunch
-
AI tools are making it easier than ever to generate software prototypes. In minutes, founders can build landing pages, dashboards, and even full MVPs. But there’s a growing challenge many teams are facing: Moving from AI-generated prototype → production-ready product. Once a product grows beyond a few components, common issues start appearing: • repeated bug loops • context loss between sessions • broken functionality after updates • infrastructure and security complexities The real question is no longer “Can AI build apps?” It’s “Can AI ship them to production?” At MelcorSoft, we work with founders and teams to transform AI-generated prototypes into stable, scalable products. Because building the first version is only the beginning. If your AI-built MVP is stuck, we’d be happy to help!
-
Introducing our fastest-growing launch to date: 𝐭𝐡𝐞 𝐀𝐈 𝐁𝐮𝐢𝐥𝐝𝐞𝐫 𝐏𝐫𝐨𝐠𝐫𝐚𝐦. 🚀 Most teams still use AI as a chatbot. Prompt in, answer out, the end. You’re not most teams. This three-week program is built to turn AI into part of your actual workflow. You’ll build real systems that: - automate recurring research, reporting, and communication - move work across your tools without manual handoffs - trigger on their own and keep running in the background The program runs as a five-level progression: Level 1: automate core tasks across research, writing, and analysis Level 2: build agents that handle multi-step workflows Level 3: deploy systems that run on triggers Level 4: coordinate multiple agents within a single workflow Level 5: add memory and feedback loops to improve performance Each level is taught live, with direct feedback on what you’re building. Designed for non-technical operators across product, operations, marketing, and GTM teams. The first cohort starts April 21 and is filling quickly. Check it out here: https://ai.joinleland.com/
-
-
𝐘𝐨𝐮𝐫 𝐧𝐞𝐱𝐭 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐠𝐚𝐢𝐧 𝐰𝐨𝐧’𝐭 𝐜𝐨𝐦𝐞 𝐟𝐫𝐨𝐦 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐀𝐈 𝐭𝐨𝐨𝐥, 𝐛𝐮𝐭 𝐟𝐫𝐨𝐦 𝐜𝐡𝐚𝐧𝐠𝐢𝐧𝐠 𝐡𝐨𝐰 𝐲𝐨𝐮𝐫 𝐭𝐞𝐚𝐦𝐬 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐀𝐈. Shift operational tasks to AI agents, stay in control and cut waste through an industrialized Software Factory. Our latest E‑book shows how to: - Embed AI safely across the SDLC - Reduce scope & technical waste with "ROI by Design" - Scale an AI-enabled workforce across teams and regions 👉 Explore the AI‑native workforce chapter. https://lnkd.in/epfFKzrP
-
-
New product update: Embedded Explore 📊 Give your customers AI driven analytics. Delight your users with the ability to query their own data live. Teams are using Querio to let their customers explore things like pricing, logistics, and product usage directly inside their product. So, what is Explore? It brings analysis and storytelling into the same place, so insights don’t get lost between queries, charts, and presentations. We’re also laying the groundwork for a new chat mode that will make Explore far more accessible to non-technical users. 𝗪𝗵𝗮𝘁 𝘄𝗲 𝘀𝗵𝗶𝗽𝗽𝗲𝗱 𝗿𝗲𝗰𝗲𝗻𝘁𝗹𝘆... -𝗣𝗶𝗰𝗸 𝘆𝗼𝘂𝗿 𝗺𝗼𝗱𝗲𝗹 Use Opus and Sonnet 4.6, or the full Gemini suite, with live visibility into model availability. -𝗦𝗵𝗶𝗽 𝘄𝗶𝘁𝗵 𝗤𝘂𝗲𝗿𝗶𝗼 Embed a full Explore via iframe, or build your own UI with our new v2 API and multi-turn conversations. -𝗕𝗼𝗮𝗿𝗱𝘀 𝗹𝗲𝘃𝗲𝗹 𝘂𝗽 View mode keeps things clean for your audience, while new layout tools give builders control over how the story flows. We’re shipping fast while building toward a more conversational Explore experience, where anyone can explore their data without writing SQL. Drop us a comment or message if there are features you'd love to see next. More soon 👀
-
-
🚨 BREAKING: Anthropic just released their the exact Skills library their own engineers use internally. It gives you direct access to the lug-and-play components you can install instantly. And it works everywhere, Claude Code, API, SDK, and VS Code. → Pre-built patterns for multi-step automation → Excel + PowerPoint generation out of the box → File handling and document workflows 100% Open Source. -- Repo: https://lnkd.in/d4pV-jbf If you want more practical AI gems and use cases, join our free newsletter with daily tutorials and latest news in AI: simplifyingai.co
-
-
🚀 Week 1 of My AI Automation Journey — And My Mind Is Already Changing Last week I officially started my AI Automation Bootcamp with Loubby AI and DivVerse Labs. To be honest… I was excited but also a little overwhelmed stepping into this space. Automation always sounded like something complex — something only developers or big tech teams could do. But this week completely changed how I see it. We didn’t just talk about tools. We talked about real business problems and how automation can actually solve them. I started understanding that automation is not about replacing people. It’s about freeing time, reducing mistakes, and allowing businesses to focus on growth instead of manual tasks. We explored tools like: • Zapier • Airtable • Make • n8n And learned practical things such as: ✔ How to spot repetitive tasks that waste time ✔ How to think in triggers and actions ✔ How to map simple workflows before building ✔ How to test and improve automations step-by-step 💡 One realization that really hit me: Most businesses are sitting on opportunities to automate — they just don’t know where to start. Simple things like: • Capturing leads automatically • Sending follow-up messages • Onboarding customers smoothly • Managing internal approvals These small systems can make a huge difference. Right now I’m still learning. Still building. Still figuring things out. But I’ve decided to share this journey openly — the wins, the challenges, and the lessons. If you’re a business owner, founder, or just curious about automation, follow along. This is only the beginning. Let’s build smarter systems together 💡 #LoubbyAIAutomationBootcamp2026 #AIAutomation #NoCodeTools #WorkflowAutomation #BuildInPublic #LearningJourne
-
AI agents work best when their knowledge is organized like a workspace they can inspect and navigate. Coding tools like Claude Code, Cursor, and Codex do this well. Analytics tools mostly don't yet. There's still real work to do before agentic analytics can reliably serve business users. One topic I want to see across data conferences this year: how companies are actually deploying trusted AI analytics agents to non-technical stakeholders. Less demos, more trenches stories from teams who've put this in front of real users.
-
“Rapid Tech Trends…” isn’t hype—it’s your next 48 hours. 3 trends making practical upgrades ship fast: 1) AI copilots → first drafts of copy, flows, QA checks 2) Low-code stacks → pages + forms + automations live same day 3) Feature flags + lightweight analytics → ship, measure, adjust (no guessing) Speed + adaptability + one metric. What would you ship by this time tomorrow? https://lnkd.in/gQFQms-C #SmallBusiness #MarketingOps #ProductDesign #NoCode #AIForBusiness #Growth #LeadGen #Momentum #ShippedNotPerfect
-
-
AI ladder journey anyone? Interesting graphic here from Sean Where’s your org planning to be on this ladder And where will it actually get too? Lots of companies still at the discovery / scoping stages #data #ai #hiring #recruitment
Manager, Data Integration & Analytics at Tri-State G&T with expertise in Business Analytics and Data Science.
There’s an obvious progression playing out in enterprise AI for the next 5–10 years. And most companies are stuck at the first and least valuable phase. 𝐏𝐡𝐚𝐬𝐞𝐬: 𝟏). 𝐀𝐩𝐩-𝐥𝐞𝐯𝐞𝐥 𝐋𝐋𝐌𝐬 • LLMs inside individual apps • Isolated, per-app experiences • Mostly UI upgrades and not system changing 𝟐). 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐋𝐋𝐌 𝐥𝐚𝐲𝐞𝐫 • Centralized interface across company data + systems • Retrieval + light tool use • Still human-driven orchestration 𝟑). 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐠𝐞𝐧𝐭𝐬 • Plan and execute multi-step workflows • Call tools, APIs, and internal systems • Maintain state across tasks • Partially autonomous 𝟒). 𝐄̲𝐦̲𝐞̲𝐫̲𝐠̲𝐢̲𝐧̲𝐠̲: 𝐀𝐝𝐚𝐩𝐭𝐢𝐯𝐞 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 (𝐎𝐩𝐞𝐧𝐂𝐥𝐚𝐰-𝐬𝐭𝐲𝐥𝐞) • Learn from outcomes (success/failure loops) • Improve task execution over time • Begin shifting from “tool” → “operator” 𝟓). 𝟓–𝟖 𝐲𝐞𝐚𝐫𝐬: 𝐖𝐨𝐫𝐥𝐝 𝐦𝐨𝐝𝐞𝐥 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 • Internal representation of how the business actually works • Simulation + planning before execution • Moves from reacting to actually reasoning and making decisions • This is where things start to get a little scary What’s nice about all of this is that architecturally, it all builds on the same foundations. You focus on strong foundations now, you’re set for the future.. The kicker is most companies have been putting off foundations for years and are still barely at the starting line.
-
