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Microsoft just launched a free course on Agentic AI 👇👇 https://lnkd.in/d5VdJemc This “AI Agents for Beginners” course offers 10+ lessons that take you from concept to code. You’ll get hands-on with frameworks like Semantic Kernel, Agentic RAG, multi-agent systems, and more.

Two weeks since we published our Tau2 benchmark findings, and the response from the AI community has been incredible. The Hacker News discussion highlighted something crucial: smaller models aren't just less capable versions of flagship models. They need to be communicated with differently. Our experiment proved it: 22% performance boost on GPT-5-mini – just from restructuring how we communicate with the model. Success rate jumped from 55% to 67.5%. Cost per conversation dropped slightly. No model changes. No additional training. Just structured prompts with clear decision trees, binary conditions, and explicit verification steps. The takeaway isn't that GPT-5-mini suddenly became more powerful – it's that structured communication unlocked its potential. For full methodology and before/after policies available in our GitHub PR, check out the blog post (link in comments).

This Microsoft course offers a comprehensive journey from concept to code, focusing on the essential aspects of constructing AI agents. Here's what you can expect to learn: - Understanding AI Agents and their functionality - Exploring the Framework Semantic Kernel - Implementing design and planning patterns for agents - Utilizing tools, RAG, and multi-agent systems - Strategies for deployment, enhancement, and enhancing agent memory Get ready to delve into the world of AI with these 10 informative videos. #AI

Curiosity used to be limited by bandwidth. Now it scales. With millions of support tickets each year, asking new questions used to take days of manual analysis. Today, AI helps us surface insights in minutes, making it easier for teams across OpenAI to explore trends, spot issues, and learn faster. This story is part of OpenAI on OpenAI - showing how we use our own technology to solve real challenges. Watch the full story below.

Companies like OpenAI are revolutionizing how companies can operationalize AI for real, measurable growth. For service-based SMBs, the key is seamless integration that respects existing systems and amplifies your teams core capabilities. Approaching new technology in this way allows us to turn AI into a growth engine rather than just a novelty . This evolution demands business leaders shift focus from experimenting with AI to architecting practical, industry-specific AI solutions that drive clear ROI. How prepared is your business to move from AI curiosity to AI maturity in 2025? If you’re ready to take the next step towards building tailored, scalable AI solutions that deliver measurable impact, let’s connect.

Your CRM is doomed. SalesForce? gone HubSpot? Adios. for that matter... MS Word? White Out'd MS Excel? Cut n pasted to oblivion PPT? Fade to black think I'm wrong? remember the database tool that was once embedded in Win?(MS-Access) yeah, it's like that heck, Windows will be gone. Who needs an OS when there is an LLM? ....how long until all functionality is inherent in YOUR LLM. by "YOURs" i mean, the one that is created by you, ad hoc, not a centralized, SaaS company. and by YOURs I mean for Your business; not every single one in your industry.(all your competitors) We won't need a Ka-billion$$ IT project. All we need as decision makers, is curiosity. Remember what that is? - this one, small conversation, illustrates the end of CRMs, the end of business consulting firms, the end of an entire cottage industry built on 'decoding' output and data created by your overly complicated, one-size-fits-all, shrink wrapped/$5 a month as long as you live, 1990s based, software company. this clip is only 2 minutes long play it again and listen once it clicks - push your curiosity into 'embodied Ai' - your walking(or rolling), talking CRM, ERP, DTP, H/R, A/P, A/R, Email...you get the idea. oh and see, I told you so.

🚀 Discovered this interesting project: Fine-tune Gemma 3 270M and run AI models on-device! It helps developers deploy AI-powered applications efficiently by fine-tuning a pre-trained model for specific use cases. 💻 This solves the problem of slow cloud-based processing and limited control over AI models. 👀 Check it out: https://lnkd.in/djMX2Ta3 👇

The ADK codebase can be awful. I mean, why does the method meant to initialize a session for a Vertex AI session accept a session ID in its definition but never use it? Instead, it scolds you for using it, even though it's defined in its schema? It tells you, "I know I said you can use it, but this is a dead end." Since the codebase is still young, it's possibly a placeholder. More work still needs to be done, especially on documenting the usage of emerging features. The documentation was sufficient when it launched, but now it's insufficient.

Train LLMs locally with zero setup! (100% open-source) Your favourite fine-tuning library just got better—now it comes as a Docker image! 🐳 This solves any dependency or environment issues you may have had. Just pull the image, run the container, and go! 🚀 The best part? Every pre-made Unsloth AI notebook is included out of the box. Link to the Docker image in the first comment! ____ Share this with your network if you found this insightful ♻️ Follow me (Akshay Pachaar) for more insights and tutorials on AI and Machine Learning!