IntermediateAgentic AI
Always-on agents
An always-on agent is an AI assistant that runs on a provider's servers and starts by itself at a set time or when something happens, even while your computer is off.
AI Dictionary
Agentic AI
Glossary of AI concepts, explained simply
29 concepts
Agentic AI
29 concepts
Intermediate
BeginnerAgentic AI
Information agents
Information agents are AI assistants in Google Search that follow a topic for you and send a summary when something changes; Google announced them in May 2026.
IntermediateAgentic AI
Managed agents
A managed agent is an AI agent that runs on the AI provider's servers: you describe the task, tools and rules, and the provider handles the computer and the access keys.
IntermediateAgentic AI
Multi-agent systems (MAS)
In a multi-agent system several AI agents share one task, each doing its own part, which helps with large tasks that split into pieces and costs more to run.
AdvancedAgentic AI
Self-evolving agentic models
Self-evolving agentic models are AI agents that learn from their own work: they change their notes, tools, code or training data and test whether that helps.
IntermediateAgentic AI
AI orchestration
AI orchestration connects several AI steps, such as recognising a question, searching your documents and writing an answer, into one process that runs in the right order.
IntermediateAgentic AI
Binex
Binex is a free, open-source tool from one developer that runs a chain of AI steps on your own computer and records what each step received, produced and cost.
IntermediateAgentic AI
CoDream
CoDream lets a team of AI agents learn from a failed task: they discuss what went wrong and pass the lesson to the teammates who are weakest at that kind of task.
IntermediateAgentic AI
Galactic
Galactic is an open-source Mac app by one developer that lets several AI coding assistants work on the same project at once, each in its own copy of the code.
IntermediateAgentic AI
ITBench-AA
ITBench-AA is a test from May 2026 in which AI agents must find the cause of IT outages in Kubernetes systems; at launch the best model scored 47%.
IntermediateAgentic AI
JobBench
JobBench is a May 2026 test that scores AI agents on 130 work tasks that professionals most want to hand off; at launch the best agent reached 45.9%.
IntermediateAgentic AI
Kairos in Claude Code
Kairos is the codename of an unreleased Claude Code feature, found in leaked code in March 2026, that would tidy up the AI's memory in the background.
BeginnerAgentic AI
Chatbot compared with an AI agent
A chatbot answers your questions in a conversation; an AI agent carries out a task for you in steps, with tools such as your email or order system.
IntermediateAgentic AI
Agent evaluation
Agent evaluation tests whether an AI agent really completes the tasks you give it, such as a refund, by checking both the end result and the steps it took.
BeginnerAgentic AI
Agent operational memory
Agent operational memory is a set of text files with an AI agent's rules and lessons, read at the start of every session so you need not explain them again.
IntermediateAgentic AI
Agentic AI
Agentic AI is AI that carries out a task on its own: it plans the steps, uses software such as email or an expense system, checks the results and asks when it gets stuck.
IntermediateAgentic AI
Agentic RAG
With agentic RAG, an AI agent searches in steps: it decides what to look for, checks whether the results answer the question and searches again if they do not.
IntermediateAgentic AI
Agentic engineering
Agentic engineering is building software with AI coding agents that write and test the code, while a developer decides what to build and checks the result.
BeginnerAgentic AI
AI agent
An AI agent is software that carries out a task on its own: it plans the steps, uses tools such as your email or order system, and asks you when it is unsure.
AdvancedAgentic AI
Belief-action decoupling
Belief-action decoupling splits an AI agent in two: one part keeps a short list of what it knows and how sure it is, the other picks the next step from that list.
IntermediateAgentic AI
Context compression for AI agents
Context compression keeps what an AI model has to read short, by summarising or removing old material, so long tasks stay affordable and the model keeps its focus.
AdvancedAgentic AI
Dynamic cognitive scaffolding
Dynamic cognitive scaffolding means an AI agent works out for each task how to split it into steps, instead of always following the same fixed recipe.
IntermediateAgentic AI
Function calling
Function calling lets an AI model ask your own software to do something, such as look up an order or check stock, and then answer with the real result.
AdvancedAgentic AI
Inference-time co-evolution
Inference-time co-evolution, a research idea from May 2026, lets a team of AI agents improve how it works together while in use, without retraining the AI model.
IntermediateAgentic AI
Prompt chaining
Prompt chaining gives an AI model a task in small steps one after another; each answer is the input for the next, so every step is simpler and easier to check.
AdvancedAgentic AI
Proof-derived authorization
Proof-derived authorization lets an AI agent do a risky action only after independent checks approve a recorded reason, with a temporary key for just that action.
AdvancedAgentic AI
Test-time co-evolution
Test-time co-evolution, a research idea from May 2026, lets a team of AI agents improve while in use by learning who is good at what, without retraining the model.
IntermediateAgentic AI
Real-world agent reliability gap
The real-world agent reliability gap is the difference between how well AI agents score on popular tests and how reliably they do real work, time after time.
IntermediateAgentic AI
Trajectory refinement
Trajectory refinement improves an AI agent's plan by comparing it with what happened when the agent carried it out, and repairing the steps that went wrong.