Microsoft Copilot leads in big enterprises, startups adopt new AI tools

Google recently released the most comprehensive roadmap yet for building AI agents, and it’s impressive! Most teams are still figuring out how to move from a GPT-style prototype to a real, production-grade agent that can reason, act, and scale. Google’s new Startup Technical Guide for AI Agents outlines clear patterns and architectures for doing exactly that. Of course, everything must be tested in real-world use cases. But it provides a strong foundation for the next wave of agentic systems. Key takeaways: - Agent Development Kit (ADK): Build, test, and deploy production-ready agents fast. - Model Context Protocol (MCP): A universal standard that makes agents and tools interoperable. - Agent2Agent (A2A): Agents can now talk, delegate, and collaborate across workflows. - Agentic RAG: Combines reasoning and retrieval for grounded, verifiable intelligence. - Vertex AI Agent Engine: Deploy, monitor, and scale agents without managing infrastructure. - AgentOps: A framework to test, audit, and secure agents before launch. AI agents are no longer a feature. They’re becoming the infrastructure layer for how modern startups build, automate, and scale. #AI #Agents #Startups

🚨 Google just dropped the AI Agent Technical Guide ,and it’s a goldmine for PM's and Startups. Here’s the summary 👇 The guide breaks down how to go from AI prototype to production-grade agent, basically how to build autonomous systems that don’t just chat, but think, plan, and act. 🔹 Core idea: AI agents are the next evolution of software, powered by large language models, tools, and grounding in real data. 🔹 What’s inside: How to build custom agents using Agent Development Kit (ADK) No-code orchestration with Google Agentspace Connecting everything with Model Context Protocol (MCP) and Agent2Agent (A2A) Ensuring reliability and safety with AgentOps Using RAG, GraphRAG, and Agentic RAG to make agents factual, not fictional 🔹 Why it matters: Startups can now automate complex workflows, integrate live data, and deploy at scale on Vertex AI Agent Engine, without reinventing the infrastructure wheel. The message is clear: The future of AI isn’t about prompts. It’s about autonomous problem-solving systems that run your business logic. If you’re building in AI, this guide is your blueprint. #AI #GoogleCloud #AIagents #LLM #Startups #AgenticAI #Automation

Ever notice how most AI feels like a goldfish brilliant, but it forgets everything five minutes later? Enter #Supermemory, a memory layer built by 19-year-old Dhravya Shah and now backed by Google execs. In plain English: it helps AI apps remember key facts, past actions, and user preferences across sessions so they stay consistent and get smarter over time. Think of it like a smart notebook behind your chatbot or agent. It quietly grabs useful bits from chats, files, and tools, then brings them back at the right moment. Developers plug it in via an API; users just feel continuity without re-explaining the same context. I like this because long-term memory is the missing piece for agents. The space is crowded vector databases, memory wrappers, and big models adding built-in recall but a focused, developer-first layer (plus a vote of confidence from Google leadership) could win on simplicity and speed. The real test will be privacy, consent, and safe forgetting. Would you trust an external memory in your AI stack? What should it remember by default and what should it forget forever? #AI #Startups #AITools

🚀 AI News Roundup - October 16, 2025 Here are the top AI developments from TechCrunch this week: 💰 FUNDING HIGHLIGHTS: • Viven (by Eightfold co-founders) raises $35M for AI digital twin technology • Liberate secures $50M at $300M valuation for AI-powered insurance solutions 🤝 MAJOR PARTNERSHIPS: • Meta partners with Arm to scale AI infrastructure efforts • Microsoft inks massive AI infrastructure deal with Nscale • OpenAI teams up with Broadcom on AI hardware development 🆕 PRODUCT LAUNCHES: • Anthropic releases new "Haiku" model version • Google launches Veo 3.1 video AI and adds it to Flow editor • Spotify introduces text messaging for AI DJ • Google Meet debuts AI-powered makeup filters • Firefox integrates Perplexity's AI search engine 🌍 GLOBAL EXPANSION: • Google announces $15B investment in Indian AI infrastructure hub The AI revolution continues to accelerate across industries - from workplace productivity to entertainment and infrastructure. What AI development excites you most? #AI #ArtificialIntelligence #TechNews #Innovation #Startups #MachineLearning #TechCrunch

Think cutting-edge AI tools are only for startups? Think again. KPMG Audit is harnessing agentic AI to drive innovation in one of the most regulated industries.

Phi-3 Mini: Microsoft's Small Model, Big Impact Microsoft just dropped Phi-3 Mini, an open-source language model delivering powerful AI with lower resource requirements. Learn why compact models are game-changers for developers and startups pursuing innovation on the edge. Read full article here: https://lnkd.in/dXfxSSm5 #MicrosoftAI #Phi3Mini #OpenSourceAI #MachineLearning #EdgeAI #DeveloperTools #TechTrends #Innovation #AIDevelopment

Dag. Superhuman went HARD at the AI market here. "Here's what nobody will tell you at those AI conferences. Based on what we're seeing in the market, most companies would generate better returns by putting their AI budget in index funds. The rush to implement AI has created a bubble of wasted capital that makes the dot-com era look disciplined." The thing is...I agree. But, you can't create progress without breaking a few eggs. The dot com bubble sucked, but it also gave us some of the greatest companies of today (Salesforce, Google, Amazon, Priceline, eBay...just to name a few). Most of what is being built today, won't exist tomorrow. But we're creating the competitive environment that will create the next generations companies. Some of which, we don't even know of yet. So, get back in the arena and try some things. Maybe you're the next Bezos. https://lnkd.in/eee8dEV6

The power of AI adoption is undeniable! OpenAI has revealed a list of 30 customers who have processed over one trillion tokens through its models, showcasing the widespread integration of AI in various industries. Key highlights: - Global Tech Leaders: Companies like Duolingo, Shopify, Canva, Salesforce, and Zendesk are leveraging OpenAI's technology to drive innovation. - AI-Native Startups: Firms like Cognition, OpenRouter, CodeRabbit, and Harvey are pushing the boundaries of AI adoption. - Custom Workflows: Many companies are building tailored workflows around OpenAI's APIs, while others are embedding GPT-powered copilots into their core products. This list underscores the significant role trillion-token users play in shaping AI infrastructure worldwide. What are your thoughts on the impact of AI on businesses and industries? --

https://lnkd.in/eMZgKPm7 The company, backed by major investors including Microsoft, presented itself as a technological unicorn: an AI-powered platform capable of building software with minimal human intervention. Its flagship product, Natasha, was marketed as a neural network capable of designing, coding, and deploying apps in record time. Builder.ai’s implosion highlights a broader pattern in the tech industry: the rapid infusion of capital into AI ventures with minimal scrutiny.