30 terms
Definitions in this topic
- Agentic AIAdvisor agentAdvisor agent explained: a working agent consulting a stronger model on demand, and how it differs from a supervisor.
- Agentic AIAgent autonomyAgent autonomy is how far an AI agent can act without asking a person. How to grant it per task and action, and which actions still need approval.
- Agentic AIAgent delegationAgent delegation: how a supervisor agent hands a bounded task to another agent, what the brief must specify, and when control returns to it.
- Agentic AIAgent handoffAgent handoffs explained: transferring control and context between specialist agents or from AI to a person.
- Agentic AIAgent harnessAgent harness explained: the runtime that adds tools, memory, approvals, and a working loop around an LLM.
- Agentic AIAgent middlewareAgent middleware explained: shared logging, security, retry, and validation logic around agent and tool execution.
- Agentic AIAgent sessionAn agent session is one bounded AI agent run with its own messages, tool results and ID, kept apart from memory so the work stays resumable and auditable.
- Agentic AIAgent skillsAgent skills explained: reusable procedures that give AI agents specialized knowledge without filling every prompt.
- ProductionAgent state machineAn agent state machine models the states an AI agent can be in and the events between them, making approval, retry, recovery and failure explicit in code.
- Agentic AIAgentic AIWhat agentic AI is, how it differs from a chatbot or basic automation, and when a company should build one.
- Agentic AIAgentic engineeringWhat agentic engineering means, how it differs from vibe coding, and the workflow of specs, harnesses and verification that makes agents productive.
- Agentic AIAgentic workflowAgentic workflow explained for business leaders: how it differs from a rigid script, and where the human gate sits.
- Agentic AIAI agentAn AI agent is an LLM system that plans steps, calls tools and checks results toward a goal: how it differs from a chatbot and what it needs to run safely.
- Agentic AIBackground agentA background agent runs outside the chat interface and reports back later. Why unattended jobs need durable status, cancellation, time limits and alerts.
- Agentic AICoding agentCoding agents explained: how they inspect repositories, edit code, run tests, and prepare multi-step changes.
- Agentic AIDeep agentsDeep agents explained: the planning, subagent, and filesystem layers that let an agent finish long, multi-step tasks.
- Agentic AIDeep research agentsDeep research agents explained: the plan, search, read, iterate loop, how they differ from RAG pipelines, and where their reports still need verification.
- ProductionFull-duplex voice AIFull-duplex voice AI explained: simultaneous listening and speaking, natural interruption handling, echo control, and turn coordination.
- Agentic AIHarness engineeringWhat harness engineering means, how it differs from prompt and context engineering, and what a production agent harness contains.
- Agentic AILong-running agentA long-running agent continues a task across hours, days and restarts by storing state outside the model, resuming from checkpoints and keeping evidence.
- Agentic AIMulti-agent systemsMulti-agent systems explained: when splitting one agent into several actually pays off, and the patterns that make it work.
- Agentic AIOrchestrator-worker patternThe orchestrator-worker pattern explained: how delegation and result assembly work, and its main failure modes.
- Agentic AIParallel agentsParallel agents explained: when concurrency helps, how to prevent shared-state conflicts, and the rules we run our own parallel agents under.
- Agentic AIPlanner-Executor PatternPlanner-executor pattern explained: one agent plans the steps, another executes them, and the checks we run on every plan before an agent acts.
- Agentic AIPrompt chainingPrompt chaining explained: how gated sequences of LLM calls work, when to use them, and how they differ from agents and chain-of-thought.
- Agentic AIReAct AgentReAct agent explained: the reason, act, observe loop behind tool-using AI agents and the controls it needs in production.
- Agentic AISubagentsSubagents explained: what isolation actually buys you, and when delegating a task to one is worth the overhead.
- Agentic AISupervisor AgentSupervisor agent explained: how one agent routes work to worker agents, when the pattern pays off, and the rules we follow in our own multi-agent runs.
- Agentic AIVibe codingWhat vibe coding is, where the Karpathy-coined practice works, where it breaks, and how it differs from disciplined agentic coding.
- Agentic AIVision agentVision agents explained: visual input combined with planning and tools, common uses, and the grounding controls needed before action.