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Ai Era
Editor’s pick

Agentic AI

The ability to understand, design, use, and supervise AI systems that can pursue goals through multi-step planning, tool use, state, and action rather than responding only with one-off generated answers.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Agent Management

The ability to assign work to AI agents, set operating boundaries, monitor performance, review exceptions, and improve the human-agent system over time while retaining clear accountability for outcomes.

Signal 10/10low automation risk
Open skill guide
Ai Era

AI Agent Orchestration

The ability to coordinate models, agents, tools, data, memory, control flow, and human checkpoints so complex AI-enabled work proceeds through the right steps with reliable handoffs and bounded autonomy.

Signal 9/10low automation risk
Open skill guide
Ai Era

Multi-Agent Systems

The ability to design and reason about AI systems in which multiple specialized agents coordinate, delegate, critique, or hand work to one another under an explicit interaction and control model.

Signal 9/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Workflow & Process Redesign

The ability to rethink an end-to-end workflow around the complementary strengths of people, AI, automation, data, and controls instead of inserting AI into an unchanged process.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Evaluation & Benchmarking

The ability to design repeatable tests that measure whether an AI system is accurate, useful, safe, reliable, efficient, and fit for a specific real-world purpose.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Governance

The ability to establish decision rights, policies, evidence, oversight, and accountability so AI is selected, built, used, monitored, and retired in ways consistent with organizational goals and acceptable risk.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Risk Management

The ability to identify, analyze, prioritize, treat, monitor, and communicate risks created or amplified by AI across its technical, human, business, and societal context.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

AI Security

The ability to protect AI-enabled systems from adversarial manipulation, data exposure, unsafe tool use, compromised dependencies, excessive permissions, and other attacks across models, applications, agents, and their surrounding infrastructure.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

Vector Databases & Embeddings

The ability to represent meaning as numerical vectors and design retrieval systems that store, index, filter, compare, and retrieve those representations effectively.

Signal 9/10low automation risk
Open skill guide
Ai Era
Editor’s pick

LLMOps

The discipline of operating language-model applications reliably through versioning, evaluation, deployment, observability, security, cost control, feedback and continuous improvement.

Signal 10/10low automation risk
Open skill guide
Ai Era
Editor’s pick

Model Context Protocol (MCP)

The ability to design, build, secure and operate integrations using the open Model Context Protocol that connects AI applications with tools, resources and external systems.

Signal 9/10medium automation risk
Open skill guide

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