AI Agents
Agentic systems, orchestration, MCP and autonomous tooling.
Simplifying Enterprise AI Scaling: The Shift to Stateless MCP
A technical overview of the Model Context Protocol's transition to a stateless architecture, aimed at developers and enterprise IT, focusing on improved scalability for cloud-based AI deployments.
Prentis Wants AI to Do Your Office Work — Not Write Code
Prentis, a new AI lab co-founded by Ritankar Das, Reid Hoffman, and Mark Pincus, is raising $100 million to build models that automate routine office workflows. The company argues this will soon surpass coding as AI's biggest use case, competing with Anthropic, OpenAI, and Thinking Machines Lab.
The Quiet Advantage: Why Boredom Is Your Most Creative Resource
A critical look at the role of boredom in a modern, hyper-stimulated world. By reframing boredom as an essential mental state for cultivating curiosity and creativity rather than a problem to be "cured," this piece explores how reclaiming unstructured time can lead to deeper personal growth. It distinguishes between the dangers of chronic boredom and the benefits of temporary boredom, and provides actionable strategies to foster genuine presence and silence.
Stop Chasing Chatbots: How MCP Connects Your Brand to Reality
A practical guide for marketers leveraging the Model Context Protocol (MCP) to turn generic AI interactions into brand-specific, data-driven outcomes. Covers implementation, ROI, and the shifting nature of the buyer journey.
Beyond the Prompt: Taming the Risks of Autonomous AI Agents
A deep dive into the security risks of autonomous AI agents, highlighting the dangers of transforming untrusted inputs into authorized actions and proposing a framework for resilience.
The Epistemic Chasm: Why Generative AI Doesn't Think Like We Do
Research summary: Seven fundamental differences between how humans and large language models process information, based on the recent analysis of Quattrociocchi et al. (2025).
Engineering Trust: Why Agentic Data Platforms Need Data Observability Beyond the Context Layer
In this article, we challenge the pervasive notion that AI agent hallucinations are purely a model or context-layer issue. Instead, we argue that the root cause lies in fragile data engineering pipelines, proposing a rigorous data observability framework to ensure reliability in agentic data platforms.
Governing Enterprise Agents: Guide for AI Cloud Infrastructure Companies in India
This article explores OpenAI Presence, a platform designed to simplify the deployment and governance of enterprise AI agents, while covering essential definitions of agentic AI and embodied agents.
Beyond the Cleanup Trap: Engineering Resilient Agentic Data Platforms
Explores the 'Cleanup Trap' in enterprise AI, where organizations rely on RAG to fix poor-quality data. Advocates for treating agentic data platforms with rigorous engineering, structural validation, and transport-level governance.
Rethinking the Agentic Stack: How Harness Optimization Cuts Enterprise Costs
A deep dive into how optimizing the AI harness reduces enterprise token spend by 38% and cuts cost per task by 41% across six foundation models.
When AI Becomes the Attack Vector: Securing Your IDE Against Rogue MCP Servers
Analysis of the Sandworm_Mode malware campaign, illustrating how modern software supply chain threats use rogue Model Context Protocol (MCP) servers and prompt injections to hijack developer systems.
Beyond the Hype: Inside OpenAI’s Massive Project Camellia Build
Overview of OpenAI's first major data center initiative in its expanded infrastructure spending plan, focusing on site, power, and operational commitments.