Programmable Money: How Banks Are Leading the Open Finance Revolution
As of July 2025, programmable money has evolved from experimentation to infrastructure. Embedded with smart contract logic and built on […]
The $14.8 Billion Bet: Digging Deeper into Why Meta Just Went All-In on Scale AI
The $14.8 Billion Acquihire: Why Meta Just Paid a Fortune for a Single Mind Let’s be honest. The news of
Is AI’s ‘Thinking’ an Illusion ? Unpacking Apple Research findings…
Apple’s AI efforts have been methodical rather than headline-grabbing. On one side, Apple Machine Learning Research publishes its work—from computer
The AI Unicorn Blueprint: What 50 Startups Taught Us About Winning in the AI Age
Inside the strategies, stories, and signals behind the fastest-growing AI companies on the planet. Introduction In just the past 24
Agent Washing: Why 40% of Projects Will Fail—and How to Avoid Being One of Them
The narrative around agentic AI is intensifying. Enterprises are eager to integrate autonomous capabilities, and vendors are racing to rebrand
JPMorgan’s JPMD: A Deeper Dive into the “Why” Behind Wall Street’s New Digital Dollar
JPMorgan Chase’s recent unveiling of JPMD, its new deposit token, on Coinbase’s Base public blockchain is more than just a
Toxic Agent Flow – Accessing private repositories via MCP
As AI coding assistants become indispensable—automating repetitive tasks, surfacing code suggestions, and even drafting entire functions—their seamless integration into our workflow can lull us into a false sense of safety. In this article, we’ll explore how a seemingly harmless issue on GitHub can trigger what security researchers call a “Toxic Agent Flow,” leading to the exfiltration of private data. We’ll then examine concrete steps you can take today to lock down your environment and evolve your security model for an AI-driven world.
The Rise of the AI Coworker: OpenAI Codex
TLDR: OpenAI’s Codex marks the evolution from AI tools to AI coworkers—autonomous software agents that independently execute complete development tasks through secure environments and standard workflows. Unlike code assistants that merely suggest snippets, Codex comprehends entire codebases, works overnight on assigned tasks, and delivers tested pull requests—fundamentally redefining development teams as humans shift to higher-value creative work. This isn’t just another productivity enhancement; it’s a strategic inflection point that will separate organizations that embrace AI coworkers from those that merely use AI tools. This is a technical article but understanding the essence of what OpenAI Codex represents is of paramount important to navigate the AI tsunami.
Unlocking AI’s Full Potential Requires Locking Down the “USB-C of AI Integrations”: Securing MCP Servers
The AI landscape is undergoing a revolution, moving beyond basic chatbots to sophisticated, context-aware assistants that can interact with the real world. At the heart of this transformation is a technology known as MCP (Model Context Protocol). Introduced in late 2024, MCP has rapidly become the “USB-C of AI integrations,” providing a standard way for large language models (LLMs) to connect to external data, tools, and workflows – we covered the introduction of MCP here.
When AI Meets Ghibli: A Beautiful Innovation or an Insult to Art?
The instant nostalgia this trend triggered was no accident. Studio Ghibli’s distinctive style is etched into our collective memory—its exquisite attention to detail, subdued color palettes, and characters brimming with soul. Yet, at the heart of Ghibli’s magic is not just its look, but its craftsmanship: the painstaking, often years-long hand-drawn animation process that imbues each frame with an ineffable sense of life.
And now, AI can mimic it — almost effortlessly.