Agentic AI = the next evolution of business systems From: Static AI Reactive workflows To: Autonomous systems Real-time learning Proactive decisions Impact: • Faster execution
• Smarter automation
• Better decisions at scale The shift is simple:
AI is no
AGENTS
-
Agentic AI: The Next Evolution of Business Systems
By
–
-
AI agent monitors news aggregation for latest updates
By
–
I built an AI agent that monitors it for me: https://
alignednews.com/ai All the AI news in X. Soon I will have a much better news monitor -
Multica Makes Coding Agents Accessible to Non-Technical Users
By
–
Turn coding agents into real teammates! Multica is a native desktop app that brings coding agents like Claude Code, Codex, and OpenCode to non-technical users through a visual interface. Here's the problem with coding agents today. 95% of knowledge workers can't use them. Not
-
Top AI Stories: Anthropic, OpenAI Exits, Coding Agents, New Tools
By
–
Top stories in AI today: – Anthropic rolls out Claude Design
– The Rundown Roundtable: Our AI use cases
– Run a free coding agent on your laptop
– Three OpenAI leaders exit amid reshuffle
– 4 new AI tools, community workflows, and more -
Winning Enterprise AI Strategy: Intelligent Systems Over Model Access
By
–
My view is simple: The winners in enterprise AI will not be the companies with access to the most models. They will be the ones that build the best intelligent systems around them. If you want the full breakdown, watch the video and tell me what part of your AI stack you are
-
Models as Components: The Infrastructure Behind AI Agents
By
–
My biggest takeaway: Models are becoming components, not products. What matters now is the system around them: → runtimes
→ memory
→ tool access
→ orchestration
→ secure execution environments That is what turns a model into an agent, and an agent into something the -
Enterprise AI strategies behind: shift from models to reasoning systems
By
–
Most enterprise AI strategies are already behind. Not because they picked the wrong model, but because they are still thinking at the model layer. The real shift is happening one level up, where AI becomes a system that can reason, use tools, retain context, and execute work
-
AiScientist: Long-Horizon AI Research Agent for ML Tasks
By
–
/5 Long-horizon AI research agents are mostly a state-management problem. Reasoning well for the next turn is not enough when ML research demands task setup, implementation, experiments, debugging, and evidence tracking over hours or days. This paper introduces AiScientist, a
-
Cursor and NVIDIA Build Multi-Agent System Optimizing CUDA Kernels 38%
By
–
/3 Cursor builds multi-agent system that optimizes CUDA kernels with 38% average speedup. Cursor, working with NVIDIA, develops a multi-agent system that writes and optimizes CUDA kernels automatically. In a three-week run across 235 real problems, the system improves
-
Strix GitHub and Shared Academic Paper
By
–
Strix GitHub:
https://github.com/usestrix/strix Paper:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6372438
…