#Context Engineering
16 articles with this tag
Skills Are the New SDKs: Rethinking AI Agents
Elvin Aghammadzada of DataRobot argues that 'skills' are the new SDKs for AI agents, addressing context engineering challenges and the shift from 'friction' to 'fluency' moats.
Databricks Tackles Agentic AI Skills Gap
Databricks launches industry-first Context Engineer certification and AI-assisted training to address the growing agentic AI skills gap.
Marketers Must Own AI Context
Marketers must own their AI context layer to maintain brand differentiation, as shared models risk commoditizing unique customer insights.
Own Your Brand's AI Context
Brands must own their 'context layer', the unique data and intelligence that defines them, to maintain a competitive edge in the AI era.
Vincent Koc on Adaptive AI Evaluation
Vincent Koc of Comet ML discusses the limitations of static AI evaluation and the shift towards adaptive, intent-based methods for measuring AI agents.
IBM Master Inventor on AI's Contextual Bottleneck
IBM Master Inventor Martin Keen discusses how context is the key bottleneck for AI models, outlining four pillars of context engineering: connected access, knowledge layer, precision retrieval, and runtime governance.
Baz's Nimrod Hauser on Bending MCP Servers
Baz's Nimrod Hauser discusses best practices for integrating third-party tools into AI agents, focusing on curation, wrapping, guardrails, and tool composition.
Agentic AI Design: Beyond Screens, Into Systems
Context Engineering AI: The New Design Frontier
Agent Memory: The New Frontier of AI Reliability
AI's Codebase Conundrum: HumanLayer's Context Engineering Breakthrough
AI Agent Design: Trust, Context, and the Conversational Future
Autonomous AI Agent Security: Context Engineering's New Battleground
Evals Reimagined: Braintrust's Engineering Approach to AI Development
Beyond Prompts: The Rise of Context Engineering in Smarter AI Systems
