#AI Engineering
19 articles with this tag
Build Dumb AI Loops That Ship with Chris Parsons
Chris Parsons of Cherrypick discusses how to build effective AI loops and products by focusing on simplicity and iteration.
AI Engineers: Context is the New Code
Patrick Debois outlines the 'Context Development Lifecycle' for AI agents, emphasizing that 'context is the new code' and detailing the process from generation to observation.
Building Better AI Agents: The Eval Platform Challenge
Phil Hetzel of Braintrust discusses the challenges and best practices for building effective evaluation platforms for AI agents, emphasizing a systems-level approach.
Matt Pocock on LLM Planning: "Don't Bite Off More Than You Can Chew"
Matt Pocock, AI expert, shares insights on effective LLM planning, highlighting the 'smart zone' vs. 'dumb zone' and the power of multi-phase plans with the 'grill-me' skill.
Anthropic, NEC Team on AI Workforce
Anthropic and NEC are joining forces to build Japan's largest AI engineering workforce, deploying Claude AI across 30,000 employees and developing specialized AI products.
AI Needs Fundamentals: Matt Pocock on Code Quality
Matt Pocock emphasizes that AI in coding requires solid software fundamentals, clear design concepts, and a shared language to avoid common pitfalls and produce quality code.
AI Agents: The Next Application Layer?
Vercel CTO Malte Ubl discusses the rise of AI agents as the next application layer, exploring their impact on software development, infrastructure, and the future of AI innovation.
7 Skills for Effective Agent Engineering
IBM AI Engineer Bri Kopecki outlines 7 key skills for building effective AI agents, emphasizing system design, tool integration, and reliability beyond basic prompt engineering.
Simon Podhajsky on "Cognitive Exhaust Fumes"
Simon Podhajsky discusses 'Cognitive Exhaust Fumes,' advocating for read-only AI observers to analyze personal data and reveal cognitive patterns, contrasting this with riskier AI agents.
IBM AI Engineer on AgentOps: The Future of AI?
IBM AI Engineer Bri Kopecki discusses the emerging field of AgentOps, crucial for managing AI agents, highlighting key metrics for observability, evaluation, and optimization.
Allen Park & Swyx on AI, Noodles, and Scaling
Allen Park of Humanloop and Swyx discuss AI development and cooking, sharing insights on building reliable AI and tackling the Dandan Noodles challenge.
IBM Experts Unpack AI Agent Interoperability
IBM's Anna Gutowska and Martin Keen discuss the Agent-to-Agent Protocol (A2A) and Model Context Protocol (MCP) for enabling AI agent collaboration.
Context Engineering: The Graph-Powered Evolution of AI Context
Anthropic's Opus 4.5: Redefining AI Capabilities and Efficiency
The Unseen Architect: How AI Can Engineer a Future of Zero Bugs
Tenex: The 10x Shift in AI Engineering Compensation
The Quest for AI Engineering's Standard Model
The State of AI Engineering: Insights from Amplify's 2025 Report with Barr Yaron
The State of AI Engineering: Insights from Amplify\'s 2025 Report with Barr Yaron
\n \"Evaluation/evals\" stands as the single most painful aspect of AI Engineering today, a stark revelation from Amplify Partners\' recent 2025 AI Engineering ...