Vitalik Buterin outlines how Ethereum can intersect with artificial intelligence, focusing on privacy, decentralization, and governance. He argues for practical applications rather than pursuing artificial general intelligence, emphasizing tools for trustless AI interactions and economic coordination among AI agents.

This whitepaper discusses how AI is changing the way platform engineering operates, focusing on the need for better governance and delivery models. It highlights the importance of automation and intelligence in managing infrastructure at scale, offering insights for teams involved in platform management.

This article discusses RegScale's Continuous Controls Monitoring platform, which automates governance, risk, and compliance processes. It highlights features like automated evidence collection, rapid certification, and AI-driven risk management to improve efficiency and reduce costs.

This article outlines various security risks associated with AI agents and their infrastructure, including issues like chat history exfiltration and prompt injection. It emphasizes the need for a comprehensive security platform to monitor and govern AI operations effectively.

This article introduces Agent Bricks, a platform that creates AI agents tailored to specific business needs using company data. It emphasizes the importance of accuracy and continuous improvement through automated evaluations and human feedback. The content also covers guides for getting started with AI agents and assessing an organization’s readiness for AI implementation.

This article outlines ten predictions for platform engineering by 2026, focusing on the integration of AI, improved developer experience, and robust governance. It highlights the need for platforms to evolve in response to rising demands for security, cost management, and compliance, ultimately reshaping the skills required for platform teams.

This article outlines Lloyds Banking Group's digital transformation using FeatureOps to improve delivery and governance. Daniel Woollery discusses shifting from isolated usage to an enterprise-wide capability while managing legacy systems and scaling operations. Attendees will gain insights into integrating FeatureOps into broader enterprise strategies.

This article outlines Zeta's approach to building a composable, scalable lakehouse architecture that integrates diverse data sources. It details how they manage data efficiently across multiple accounts while maintaining governance and flexibility for AI-driven workloads.

This report reveals findings from 1,150 IT leaders about the current state of automation and AI in organizations. It highlights the gap between potential and actual use of agentic AI, emphasizing the need for better orchestration and governance to scale these technologies effectively.

This article explains how Agent Bricks creates tailored AI agents using your business data. It highlights features like automated evaluations and continuous accuracy improvements, helping organizations deploy effective AI solutions without extensive trial and error.

This article introduces Agent OS, a framework for managing autonomous AI agents using a kernel architecture. It emphasizes policy enforcement to ensure safe and controlled execution of agent actions, replacing reliance on prompts with deterministic checks. The framework allows developers to define and enforce safety policies directly.

AWS has introduced a Responsible AI Lens and updated its Machine Learning and Generative AI Lenses within the Well-Architected Framework. These updates aim to help professionals design and manage AI systems with a focus on ethics, risk management, and operational best practices.

The article discusses the importance of treating AI agent memory as a critical database, emphasizing the need for security measures like firewalls and access controls. It highlights the risks of memory poisoning, tool misuse, and privilege creep, urging organizations to integrate memory management with established data governance practices.

The article contrasts two approaches to improving the world in the context of AI governance. It discusses Jim Moylan's simple innovation in car design as an example of effective, low-effort solutions compared to complex international treaties that often fail. The author argues for favoring practical tools over bureaucratic agreements.

This article covers Agent Bricks, a platform that creates AI agents tailored to specific business data. It emphasizes improving accuracy through automated evaluations and human feedback, helping organizations deploy effective AI solutions quickly.

This article discusses how Agent Bricks helps organizations create high-quality AI agents using their own data. It emphasizes the importance of accuracy, continuous improvement through human feedback, and provides resources for understanding AI agent implementation.

This article discusses Agent Bricks, a service that creates AI agents tailored to specific business data. It emphasizes the importance of accuracy and continuous improvement through human feedback and automated evaluations. The piece also highlights resources for organizations looking to adopt AI agents effectively.

This article discusses a webinar featuring insights from CIOs and CISOs at ASOS and Genesys about the challenges of responsible AI adoption. It highlights the findings of a Forrester study on AI trust issues within IT teams and the importance of orchestration for secure AI integration.

The article examines the security risks associated with the Model Context Protocol (MCP), which enables dynamic interactions between AI systems and external applications. It highlights vulnerabilities such as content injection, supply-chain attacks, and the potential for agents to unintentionally cause harm. The authors propose practical controls and outline gaps in current AI governance frameworks.

This article discusses a Forrester study on AI adoption challenges faced by businesses. It highlights that without orchestration, AI efforts become fragmented and ineffective, and emphasizes the importance of governance, visibility, and cross-functional alignment for IT leaders.

This article outlines the evolving role of data engineering as we approach 2026, focusing on the integration of agentic AI systems. It emphasizes the need for data engineers to create context-rich data products, manage active metadata, and design systems that support AI workflows.

This webinar discusses how engineering leaders can shift from using fragmented AI tools to a unified system that enhances productivity and governance. It emphasizes the importance of connected workflows as an operating model for scaling AI effectively within organizations.

Riff helps businesses streamline operations by integrating AI into workflows, focusing on real data from day one. IT ensures security and governance while domain experts build solutions that drive measurable outcomes. The platform offers scalable pricing and robust support for ongoing development.

This article discusses Agent Bricks, a platform that creates AI agents tailored to specific business data. It outlines how to enhance agent accuracy through automated evaluations and human feedback, plus offers resources for getting started with AI agents in organizations.

Organizations face significant challenges in scaling AI proofs of concept (POCs) into production, with nearly 40% remaining stuck at the pilot stage. The FOREST framework outlines six dimensions of AI readiness—foundational architecture, operating model, data readiness, human-AI experiences, strategic alignment, and trustworthy AI—to help organizations overcome barriers and successfully implement AI initiatives.

The article discusses the challenges posed by agentic artificial intelligences (AIs) in the context of the OODA loop—Observe, Orient, Decide, Act—framework. It highlights the complexities of integrating AI decision-making into human processes and the implications for security and governance. The author emphasizes the need for a deeper understanding of these interactions to ensure effective management of AI systems.

Recent acquisitions in the data and AI markets highlight a trend towards consolidation and the decoupling of storage and compute, emphasizing the importance of governance in managing multi-structured data. As organizations face governance fragmentation, the need for unified governance solutions becomes critical, with companies like Databricks and Collibra leading the charge towards more scalable and flexible governance architectures. The competition in the data and AI space is intensifying, driving innovation and efficiency in data management practices.