Agents and autonomy

Testing whether an agent completes real tasks correctly end to end, which is harder to measure than a single answer's quality.

A toolkit for building agents that supplies the loop, the tool connections and the memory, so each project does not rebuild them.

The point where an agent passes work to a person or to another agent, and the moment worth designing most carefully.

The repeating cycle an agent runs of deciding, acting and checking the result, continuing until the goal is met or a limit stops it.

The parts agents play in a multi-agent setup, typically one planning and delegating while others carry out the individual pieces.

An emerging way for agents from different vendors to talk to each other directly, aimed at the problem of tools that cannot cooperate.

A process where an AI decides the next step rather than following a fixed path, trading predictability for the ability to handle variation.

A point where a person must confirm before the process continues, placed where a mistake would be expensive rather than at every step.

How much an agent may do without asking, the setting that decides most of the value and most of the risk of using one.

An agent that operates a web browser to complete tasks on sites that offer no other way to reach them.

An AI that works on a codebase across many steps, reading files and making changes, rather than suggesting one snippet at a time.

An agent running in the background without anyone watching, which makes limits, logging and a stop control matter far more.

A single control that stops an automated system immediately, which is the thing to establish before autonomy is increased rather than after.

Facts an agent keeps across separate tasks and sessions, which makes it more useful over time and makes what it has stored worth being able to inspect.

Several agents working on one job with different responsibilities, which can help on large tasks and adds its own coordination problems.

A common agent pattern where the model alternates between reasoning about what to do and taking an action, using each result to decide the next step.

Confining what an agent can reach and change, so a mistake or a hijacked instruction is contained rather than loose in your systems.

The explicit list of what an agent is permitted to do, defined in advance so that anything outside it fails rather than being attempted.

A helper agent given one narrow piece of a larger job, keeping each part focused and its context manageable.

Splitting a large goal into steps small enough to act on, the step most agent failures can be traced back to.

What an agent holds while a task is in progress, which is separate from anything it remembers between sessions and is the first thing to fill up.