Engineering posts about Artificial Intelligence
Curated summaries and key learnings for engineers working with Artificial Intelligence.
AI readiness in telecommunications
The article explores the paradox of AI adoption in telecommunications, where despite high executive interest, many initiatives fail to scale due to issues surrounding data quality and governance. It...
Building an Enterprise Agent Platform: Enforcing Identity, Data, and API Governance
The article discusses the challenges enterprises face in deploying AI agents while maintaining effective governance across identity, data, and APIs. It emphasizes the need for a unified governance...
Agent Fabric Context Catalog and the Future of AI Governance
The article explores the challenges of AI governance in the context of modern autonomous agents that operate beyond traditional application boundaries. It highlights the integration of Salesforce's...
Databricks context engineer associate: the industry’s first certification for reliable AI agent systems
The article introduces the Databricks Certified Context Engineer Associate certification, the first of its kind aimed at enhancing the reliability of AI agent systems through effective context...
How Salesforce Built an AI Security Agent for Autonomous Threat Triage
The article outlines how Salesforce developed the SATA agent, an AI-driven system designed to enhance cybersecurity by autonomously triaging threats across complex environments. It highlights the...
From manual to autonomous: how AI agents are transforming electric grid operations
The electric utility industry is facing unprecedented operational challenges due to increasing demand and aging infrastructure, necessitating the adoption of AI agents to enhance grid reliability and...
Securing MCP: A Control Plane for Agent Tool Execution
The Model Context Protocol (MCP) is emerging as a standard for AI agents to access tools, but it lacks governance mechanisms to ensure secure execution. This article outlines the risks associated...
What the design-to-code loop unlocks
The article explores the evolving relationship between design and code facilitated by AI technologies, particularly within the Figma platform. It emphasizes how AI is transforming traditional...
Addressing HR's widening capacity gap with AI
The article outlines the pressing challenges faced by HR departments in the wake of increasing demands and limited resources, highlighting the widening capacity gap exacerbated by post-pandemic...
How Informatica Built a Multi-Agent AI System to Reduce Data Workflows from Months to Days
Informatica's CLAIRE system represents a significant advancement in enterprise data management through a multi-agent architecture designed to streamline complex workflows. By integrating multiple...
The AI Scaling Gap Hiding in Digital Native Companies
The article analyzes the current state of AI operational maturity among digital native companies, highlighting a significant gap between AI deployment and full embedding across business functions....
LLM Vs AI: A Practical Guide to Differences, Use Cases, and Tools
This article serves as a comprehensive guide to understanding the distinctions between large language models (LLMs) and the broader field of artificial intelligence (AI). It outlines the scope, core...
Built In, Not Bolted On: What AI-Native Actually Means in Cybersecurity
The article explores the paradigm of AI-native applications in cybersecurity, emphasizing the importance of integrating AI capabilities directly into the core architecture of security solutions...
AI App Development: Guide To Building AI-Powered Apps
This article serves as a detailed guide for developers looking to build AI-powered applications, emphasizing the importance of structured planning and execution. It outlines the phases of AI app...
Real-Time Decisioning for AI Agents: Why you Need a Customer Context Layer First
The article explores the evolving landscape of marketing technology, emphasizing the shift from traditional martech stacks to a composable canvas where AI agents operate on shared data. It introduces...
Introducing Genie Agent Mode
The article introduces Agent mode, a new feature in Genie that enhances data analysis capabilities by allowing users to ask complex questions and receive meaningful insights. Agent mode operates...
Agents that remember: introducing Agent Memory
The article introduces Agent Memory, a managed service designed to enhance AI agents by providing them with persistent memory capabilities. This service addresses the challenge of context management...
Capacity Efficiency at Meta: How Unified AI Agents Optimize Performance at Hyperscale
The article outlines Meta's innovative Capacity Efficiency Program, which leverages a unified AI agent platform to enhance performance optimization across its infrastructure. By automating the...
8 AI and data trends shaping financial services in 2026
The article outlines eight key AI and data trends that are expected to transform the financial services industry by 2026. It emphasizes the necessity for firms to operationalize AI effectively,...
What is Agentic Analytics?
Agentic analytics represents a paradigm shift in data analysis, leveraging autonomous AI agents to continuously monitor data, generate insights, and trigger actions. This approach moves beyond...