Autocomplete suggests text that you accept or reject. An agentic coding tool takes a goal, then reads files, edits them, runs commands and can open pull requests on its own. The difference matters for security because agents act with your permissions, so they need approval rules, credentials control and review.
Definitions
- Autocomplete: inline suggestions while you type. A human accepts every change.
- Chat assistant: a conversation in the editor that answers questions and proposes snippets. A human still applies the change.
- Agentic tool: software that runs a loop of reading, deciding, acting and checking, using tools such as file edits, shell commands, web fetches and connected servers.
GitHub describes its cloud coding agent as working on one branch at a time, opening one pull request per task, within the repository named at the start, in an ephemeral cloud environment. Local agents in a terminal or editor run on your machine with your user's access instead.
Comparison
| Aspect | Autocomplete | Chat assistant | Agentic tool |
|---|---|---|---|
| Who applies the change | You | You | The tool |
| Can run commands | No | Usually no | Yes |
| Credentials reachable | None directly | None directly | Whatever the session has |
| Main risk | Data in context, weak suggestions | Same, plus pasted secrets | Actions, injection, excessive agency |
| Control to use | Data rules, review | Data rules, review | Permissions, sandbox, scoped tokens, review |
Why autonomy changes the risk
OWASP lists excessive agency among the top risks for LLM applications, meaning too much functionality, permission or autonomy given to a model. It also lists prompt injection first, where hidden instructions in content the model reads change what it does. An autocomplete tool reading a hostile file produces a bad suggestion you can see. An agent reading the same file might run a command.
What to ask before enabling agents
- What can it run without asking?
- Which credentials does it inherit?
- Does it work in a sandbox or on a developer laptop?
- Where do its changes land, and who reviews them?
- What logs exist for what it did?
Try it yourself
Click through it at your own pace, or open it full screen.
Watch the assistant call tools in the demo and note each step where an approval or permission rule could apply.
Quick check
Is a chat assistant an agent?
Not by itself. It becomes agentic once it can run commands, edit files or call tools without you applying each change.
Do agents need a separate policy?
They need extra rules for actions, credentials and approvals, which can live as a section in the main policy.
Safeguard offers agent identity and MCP Guardrail for agent access, and a free scan at gold.safeguard.sh/scan.
Sources
Last reviewed: 19 October 2026.
