Uber AI Solutions Bounding Box Validation System

Discover how Uber AI built an ML validation system to automatically catch critical ID swaps and position jumps in video bounding box annotations, streamlining data quality for object tracking. Read More: https://lnkd.in/gSfvfS5Z #Uber #UberEngineering #MachineLearning

How to Build Your First AI Agent in Under 30 Minutes Your first autonomous AI teammate is closer than you think. This step-by-step visual guide shows how anyone can build a working AI agent in under 30 minutes — no heavy coding required. From choosing the framework to testing and deploying — everything you need to get started today. The age of personal AI teams has begun. Full guide in the image 👇 Ready to build your first agent? Tell me what task you want it to handle first. #AIAgents #NoCode #Automation #Productivity #AI

What if we’re thinking about AI agents the wrong way? Right now, we treat them like they're some kind of a feature. But they behave more like autonomous systems, consuming API dat and making decisions on their own. Which means they need something like a runtime control layer, something we haven't thought about it as far as I know. we need to know what they’re doing, control what they can access and audit how decisions are made Almost like Datadog + Okta, but for AI agents. I’ve started sketching what this could look like. Does this resonate, or am I overthinking it? #AIAgents #AIInfrastructure #EnterpriseArchitecture #AIGovernance #TechStrategy

This is not about another week of “look at all the tools.” OpenAI just flooded the zone, but the bigger pattern is not simply “more tools.” It's AI moving closer to actual work. → GPT-5.5 pushes deeper into complex coding, research, and business workflows. Workspace Agents move the custom GPT idea closer to repeatable team operations. Privacy Filter points to the boring but important layer most people skip, safer data handling before the model ever gets involved. → Meanwhile, Honor’s Lightning robot made the “AI is leaving the screen” conversation a lot harder to ignore. Open-weight models like Kimi K2.6 and Qwen 3.6 keep raising the ceiling for local and developer workflows. The pattern I’m watching: → Models are becoming work engines. → Workspaces are becoming context engines. → Robots are turning software progress into physical proof. The opportunity is not to chase every announcement. The opportunity is to ask which workflow should be tested first, what data is safe to use, and what guardrails need to exist before the pilot becomes production. That is the shift from AI Tourist to AI Operator. LOCK IN for LEVERAGE! #ArtificialIntelligence #FutureOfWork #AIAgents #BusinessAutomation #Robotics

What happens when AI agents move from experimentation to real-world execution? This escape room case study shows how teams used AI agents as force multipliers to accelerate development under tight timelines. It also highlights critical lessons around human ownership, workflow coordination and the limits of autonomous systems. Read the full article to explore how to balance speed with control when working with AI agents: https://buff.ly/tTCzuPy #AIAgents #PlatformEngineering

You can now run Claude Code entirely in your local terminal. Someone built claude-code-local to give you a private, local-first environment for Anthropic's terminal agent. - Run autonomous coding tasks locally. - Privacy-focused execution environment. - Zero-config setup for your terminal. 100% Open Source. — Repo: https://lnkd.in/dvrSrUJA If you want more practical AI gems and use cases, join our free newsletter with daily tutorials and latest news in AI: simplifyingai.co

Replit's autonomous AI deleted a customer's production database. This is the model that's supposed to replace your engineering team. The "tokens-for-engineers" math has three holes: → Tokens won't trend to zero. Jevons + capacity constraints + unconstrained agentic loops mean total spend grows faster than per-token cost falls. → Frontier AI still fails at real engineering. SWE-Bench Verified plateaus near 70%. Devin solved 3 of 20 real tasks in independent testing. Anthropic's own Project Vend showed Claude drifting in identity over weeks. The autonomous coding factory leaks. → Every session forgets. Agents don't accumulate scars. Senior engineers compress 20 years of failed paths into one sentence that saves weeks of elegant wrong work. Agents start every session at zero. The right call: leverage, not replacement. The right metric: judgment per token. Full blog post: https://lnkd.in/eSk-K3ze Deck attached. #AI #EnterpriseAI #DataLeadership

llms.txt Explained: The File Every Business Website Needs for AI Search Visibility A plain-text file called llms.txt is quietly becoming the robots.txt of the AI era. Here's what it is, why it matters, and how we use it at The Digital Hall to help businesses get cited in AI-generated answers....

Remember when AI just meant chatbots? Now it's folding laundry and navigating warehouses. We just published a breakdown of Physical AI—what it means, where it's showing up (warehouses, farms, healthcare), and why it's harder than traditional software AI. If you're curious about robots that learn rather than follow scripts: https://lnkd.in/gwjDiucW #Brahmastra #PhysicalAI #Artificialintelligence #Software

Most people are still thinking about AI as a "copilot"—a smart chatbot you just copy and paste text from. But the architecture is already shifting. The real unlock is treating AI as **infrastructure** 🏗️. By giving my development environment write access to external APIs (via the Model Context Protocol), my IDE is no longer just a code editor. It’s a command center. I don't just ask the AI for a code snippet; I ask it to draft, review, and execute workflows—like publishing this very post—directly from my terminal. The friction drops to zero when the AI can actually press the buttons for you. 🚀 #AI #DeveloperTools #SoftwareEngineering #FutureOfWork #AgenticWorkflows #MCP