"Amazon Quick Suite: A Revolutionary AI Platform for Unified Data Querying"

Amazon Web Services (AWS) announced Quick Suite today! Research – Quick Research accelerates complex research by combining enterprise knowledge, premium third-party data, and data from the internet for more comprehensive insights. Business intelligence – Quick Sight provides AI-powered business intelligence capabilities that transform data into actionable insights through natural language queries and interactive visualizations, helping everyone make faster decisions and achieve better business outcomes. Automation – Quick Flows and Quick Automate help users and technical teams to automate any business process from simple, routine tasks to complex multi-department workflows, enabling faster execution and reducing manual work across the organization. https://lnkd.in/geUAQH5Q

What used to take 18 months with a full dev team can now take shape over a weekend. But most are celebrating the wrong part. OpenAI just dropped AgentKit, an Agent Builder, a platform where your AI model, workflows, and integrations live in one place. Everyone’s talking about “easier automation (replacing Zapier, n8n, and more).” But they’re missing the real unlock. This isn’t just about tools. It’s about who gets to build now. ✅ A solo founder can prototype an enterprise workflow over breakfast. ✅ A domain expert (no code) can turn deep knowledge into systems. The barrier didn’t lower. It vanished. We’re entering collaborative intelligence, where AI agents work together not in isolation. One agent handles queries. Another analyzes patterns. Another optimizes execution. While you sleep, your workflow evolves. These are not just tools. They’re systems that think. What this unlocks: - Industry experts become infrastructure builders - Domain knowledge becomes your moat - Specialized vertical systems beat generic tools - Products built with compliance-first design win premium markets The next frontier: → Monitoring agent decisions → Compliance frameworks + audit trails → Marketplaces for domain-specific agent templates → Systems to explain, observe and govern agent logic This is the AWS moment, infrastructure on top of infrastructure. The game hasn’t ended. The playing field just grew 1000×. Held back by tech constraints? That’s gone. Sitting on domain expertise? This is your time. Ready to turn knowledge into autonomous systems? Let’s build the next layer together.

The Rise of IDPS: A New Era of Developer Productivity The past decade gave us IDEs (Integrated Development Environments). Now, a new generation of tools is emerging IDPS: Intelligent Developer Productivity Suites. These aren’t just code editors. They’re AI-native environments that integrate: - Context-aware code generation - Real-time debugging with natural language - Seamless cloud deployment & CI/CD setup - Personalized recommendations based on your coding style Think of it as GitHub Copilot meets Notion, meets AWS Console, in one unified workspace. Companies like Cortex.dev, Replit, and Sourcegraph are already moving in this direction. But the real game-changer is what’s coming next: AI systems that understand your entire codebase, team patterns, and project goals, acting like a full-stack co-engineer. The impact? Developers spend less time juggling tools and more time shipping. Teams go from “maintaining code” to “accelerating innovation.” As we move into 2026, expect “IDPS” to become a core category in enterprise and startup stacks alike.

We Didn’t Monetize Our AI Platform. Yet. Some parts are ready for production. Some still need work. That’s exactly why we didn’t turn it into a paid platform. The AI Agent Bus runs multi-context workflows across tools, APIs, people, and models. Developers can use it today. It’s real, it’s fast, and we use it ourselves every day. But turning it into a polished PaaS? That’s a different game. The core engine is strong—but the UI still has miles to go. So instead of slapping a price on it, we open sourced it. Not because we’re naive about business but because we’re serious about what we’re building. If we’re going to offer it later as a product, it needs to earn that place. Not fake it. It needs a community. Open source lets us ship what’s useful now and keep improving what isn’t. Some say that’s leaving money on the table. We think it’s just building with integrity. See more at https://lnkd.in/ggFTRew8

From Code to Context: The Next Webstack Is Agent-Aware Post Content: Web development is no longer about static architectures — it’s about living frameworks that understand, learn, and adapt. 🌐⚙️ This week’s innovations are reshaping that idea completely: 🚀 Amazon Bedrock’s AgentCore MCP simplifies building agent-ready components with runtime and identity management built-in. 🧩 Workato’s Enterprise MCP connects LLMs like ChatGPT, Claude, and Gemini through 100+ managed servers. 💬 Slack’s real-time search API lets apps tap into team conversations securely to build context-aware AI tools. Meanwhile, accuracy-focused APIs like Melissa’s Cicero remind us that the web’s future isn’t just smart — it’s precise. Because what good is an intelligent app if it’s based on flawed data? The modern webstack is becoming a conversation between humans, data, and AI — and developers are the translators. #WebDevelopment #AgenticAI #FullStackDev #MCP #ModernWebstack #AIintegration

Please, stop over-engineering internal enterprise tools. You don’t need micro-frontends, TypeScript, and 14 Docker services to validate a workflow. You need clarity of 𝘀𝘁𝗮𝘁𝗲, precision of 𝗲𝘃𝗲𝗻𝘁𝘀, and a loop of 𝗳𝗮𝘀𝘁 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸. Most internal tools don’t fail because of bad design. They fail because teams spend weeks building scaffolding before learning if the flow even works. Here’s what I’ve learned building them: 𝗖𝘂𝘁 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗲𝗮𝗿𝗹𝘆 ↳ You don’t need three languages for one prototype. ↳ A single Python codebase can own logic, UI, and backend, without context drift. 𝗗𝗲𝘀𝗶𝗴𝗻 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗵𝗲 𝗲𝗻𝗱𝗽𝗼𝗶𝗻𝘁𝘀 ↳ Internal tools aren’t APIs, they’re 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴 𝘪𝘯 𝘮𝘰𝘵𝘪𝘰𝘯. ↳ Model each user action as an event that mutates state in real time. 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗯𝗲𝗮𝘁𝘀 𝗽𝗲𝗿𝗳𝗲𝗰𝘁𝗶𝗼𝗻 ↳ If a stakeholder can’t test it soon, you’ll keep guessing. ↳ Deploy early, collect reactions, then harden what matters. 𝗖𝗼𝗱𝗲 𝗼𝗻𝗰𝗲, 𝗿𝗲𝗮𝘀𝗼𝗻 𝗼𝗻𝗰𝗲 ↳ When your UI and logic share the same language, ↳ You spend less time translating and more time shipping. I recently tried 𝗥𝗲𝗳𝗹𝗲𝘅, which embodies this philosophy, 𝘀𝘁𝗮𝘁𝗲𝗳𝘂𝗹, 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲, 𝗮𝗻𝗱 𝗿𝘂𝘁𝗵𝗹𝗲𝘀𝘀𝗹𝘆 𝘀𝗶𝗺𝗽𝗹𝗲 For teams that value speed over ceremony. Here’s what stood out to me: ↳ 𝗣𝘂𝗿𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗲𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲 Write both frontend and backend logic in one language. ↳ 𝗖𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗦𝘁𝗮𝘁𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Your app’s state lives in Python and syncs to the UI automatically. ↳ 𝗘𝘃𝗲𝗻𝘁-𝗱𝗿𝗶𝘃𝗲𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 define events that update state in real time. ↳ 𝗪𝗲𝗯𝗦𝗼𝗰𝗸𝗲𝘁-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗿𝗲𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆 instant client updates without manual wiring. ↳ 𝗕𝘂𝗶𝗹𝘁-𝗶𝗻 𝗨𝗜 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 (𝟲𝟬+) buttons, tables, forms, charts. ↳ 𝗢𝗻𝗲-𝗰𝗼𝗺𝗺𝗮𝗻𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝘀 𝚛𝚎𝚏𝚕𝚎𝚡 𝚍𝚎𝚙𝚕𝚘𝚢 to share a live link or self-host in CI/CD. ↳ 𝗢𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗮𝗻𝗱 𝗲𝘅𝘁𝗲𝗻𝘀𝗶𝗯𝗹𝗲 customise, self-host, or integrate with your existing stack. Try Reflex Here: https://lnkd.in/gYzPrcxp Internal tools don’t scale through complexity They scale through clarity, when 𝘀𝘁𝗮𝘁𝗲, 𝗲𝘃𝗲𝗻𝘁𝘀, 𝗮𝗻𝗱 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 move in one direction. ♻️ Repost this to help your network upskill

I found a 100% open-source alternative to n8n! (16k stars, runs locally, powered by local LLMs) Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. Key features: - Real-time workflow execution - Connects with your favorite tools - Works with local models via Ollama - Intuitive drag-and-drop interface using ReactFlow - Multiple deployment options (NPM, Docker, Dev Containers) Sim outshines n8n with: - An intuitive interface - State-of-the-art copilot for faster builds - AI-native workflows for intelligent agents I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Tech stack: - Sim.ai (YC X25) to build the workflow - Firecrawl for web search The video below depicts the final chatbot produced in a few minutes. You can also find all the details in Sim's GitHub repository, linked in the first comment. ____ Find me → Avi Chawla Every day, I share tutorials and insights on DS, ML, LLMs, and RAGs.

The article explores the crucial role of trust in the era of AI agents, highlighting how Docker empowers developers to build and deploy secure software. I found it interesting that over 20 million developers are already leveraging Docker for safe software delivery. As we advance in AI, how can we further enhance the trustworthiness of our software solutions?

Each year, Google publishes a report analyzing trends in software development (The DORA - DevOps Research and Assessment - Report). This year's was titled "State of AI-assisted Software Development" and focuses on the growing role of AI in this field. Georg Lindsey, CGNET CEO, gives us a summary of their findings in his blog post this week. https://lnkd.in/dN3t4UBj

New Claude Sonnet 4.5 Just Broke EVERY Limit We Knew (So Powerful It’s Scary) Claude Sonnet 4.5 just shocked the dev world — this AI coded for 30 hours straight without losing focus. It built full apps end-to-end, crushed benchmarks like SWE-Bench Verified and OSWorld, and is already integrated into GitHub Copilot, Office 365, and Chrome. Anthropic even dropped a full Agent SDK, giving developers the same tools they use internally. With state-of-the-art results, new memory systems, native VS Code support, and enterprise-grade safety, Sonnet 4.5 isn’t just another update — it feels like the first AI developer that never quits. 🦾 What You’ll See: • Claude Sonnet 4.5 coding 30 hours nonstop without breaking focus • Benchmark jumps: SWE-Bench Verified, OSWorld, and more • New Claude Agent SDK with VMs, memory, and agent coordination • Deeper integrations with GitHub Copilot, VS Code, Chrome, and Office 365 • Anthropic’s safety and alignment framework (AI Safety Level 3) in action • Why this release might change how developers and enterprises work forever ⚡ Why It Matters: This isn’t just faster code generation — it’s an AI that works like a real teammate, handling projects over days, integrated everywhere, and backed by $500M ARR already. Claude Sonnet 4.5 might be the closest thing yet to a tireless AI colleague. https://lnkd.in/dJFBJd-c