Agents
What Is Agentic Coding? How the Loop Works in Cursor
Agentic coding is building software by directing AI agents instead of writing every line yourself. You give an agent a goal; it plans the work, edits code, runs commands and verifies the result while you guide and review. In Cursor that means Agent mode for the task, Plan mode when you want the approach first.
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What is agentic coding?
Cursor's own definition is short: building software by directing AI agents instead of writing every line yourself. You give an agent a goal, and it plans the work, edits code, runs commands, and verifies the result while you guide and review.
The word that carries the weight there is "verifies". An autocomplete suggests and stops. An agent runs the thing it just wrote, reads what came back, and keeps going. That is the whole difference, and it is why the review burden moves from the keystroke to the diff.
Your job shifts from producing lines to setting the goal and judging the result. The agent does not remove the review step; it moves it to the end and makes it bigger.
This is covered hands-on in Agent Mode Foundations — 6 short modules, free to read.
How does agentic coding work?
The loop starts with a prompt that describes the goal and any constraints. From there the agent uses tools to search code, edit files and run the terminal, and it reads each result before deciding its next step. That read-then-decide step is what makes it a loop rather than a single generation.
Cursor is explicit about the input that most changes the output: grounding the prompt in real files and patterns produces better results than describing the change in the abstract. Point at the code you mean. If you want to review the approach before any code is written, run it through Plan modeA mode that makes no edits: it researches the codebase and produces an editable plan you review before any code changes. Press Enter for the full definition. first.
- Stage
- Prompt
- What the agent does
- Reads the goal and constraints you wrote
- Where you come in
- Name the files and patterns, not just the outcome
- Stage
- Tool use
- What the agent does
- Searches code, edits files, runs the terminal
- Where you come in
- Set run modes and approvals you are comfortable with
- Stage
- Read result
- What the agent does
- Reads each tool result before its next step
- Where you come in
- Watch for a loop that keeps retrying the same thing
- Stage
- Plan modeA mode that makes no edits: it researches the codebase and produces an editable plan you review before any code changes. Press Enter for the full definition.
- What the agent does
- Produces the approach before writing code
- Where you come in
- Review and correct the plan while it is still cheap
| Stage | What the agent does | Where you come in |
|---|---|---|
| Prompt | Reads the goal and constraints you wrote | Name the files and patterns, not just the outcome |
| Tool use | Searches code, edits files, runs the terminal | Set run modes and approvals you are comfortable with |
| Read result | Reads each tool result before its next step | Watch for a loop that keeps retrying the same thing |
| Plan modeA mode that makes no edits: it researches the codebase and produces an editable plan you review before any code changes. Press Enter for the full definition. | Produces the approach before writing code | Review and correct the plan while it is still cheap |
The loop as described at cursor.com/help/ai-features/agentic-coding.
How did coding agents get here?
Cursor frames the arrival in three steps, and they are worth reading as a widening of scope rather than three separate products. Each step holds more context and runs longer than the one before it.
- 1Tab autocomplete handled repetitive edits one suggestion at a time.
- 2Synchronous agents could hold more context and run longer, so developers directed them through prompt-and-response loops.
- 3Autonomous agents now take on larger tasks over hours with less direction.
The demand curve is public: Cursor reports agent usage has grown more than 15x in the past year, and tracks the shift across millions of developer sessions in its Developer Habits Report. Cursor's own read of what comes next is agents that run for hours and coordinate with each other, up to codebases that keep improving with little intervention.
The three steps above are shipped behaviour. Self-improving codebases are Cursor describing where it thinks this goes. Treat them differently when you plan a rollout.
What is agentic engineering?
Cursor uses a second term for the organisational half of this: agentic engineering, which it describes as the industry working out what software engineering looks like when most code is written by coding agents and systems need to be redesigned to take advantage of AI.
It is framed as an evolution of existing practice rather than a replacement, aimed at cutting drudge work and moving engineer time toward higher-value tasks. The example Cursor gives is on-call: speeding up debugging and incident triage so engineers find the root cause faster.
How do I start agentic coding in Cursor?
The starting move is smaller than the term suggests. Open Agent modeCursor's full-capability mode: the AI can read the codebase, write and edit files, move them and run terminal commands. Contrast with Ask mode, which is read-only. Press Enter for the full definition. and describe a task in plain language - the agent overview is the reference for what it can reach. Two escalations exist from there, and picking between them is mostly about task size.
- A normal task
- Agent modeCursor's full-capability mode: the AI can read the codebase, write and edit files, move them and run terminal commands. Contrast with Ask mode, which is read-only. Press Enter for the full definition.. Describe it in plain language and review the diff.
- Larger work
- Plan modeA mode that makes no edits: it researches the codebase and produces an editable plan you review before any code changes. Press Enter for the full definition. first, so you review the approach before the agent builds.
- Long-running work
- Cloud AgentsAgents that run in a Cursor-managed virtual machine, check out the repo, do the work and open a pull request, then shut down, with no load on your laptop. Press Enter for the full definition., so it keeps going while you do other things.
Cursor's recommended entry points for each size of task.
Frequently asked questions
What is agentic coding?
Building software by directing AI agents instead of writing every line yourself. You give an agent a goal, and it plans the work, edits code, runs commands and verifies the result while you guide and review.
How is it different from autocomplete?
Autocomplete suggests the next edit and stops. An agent uses tools to search code, edit files and run the terminal, and reads each result before choosing its next step. Cursor describes autocomplete as the first of three steps, followed by synchronous agents and then autonomous ones.
How do I get better results from an agent?
Ground the prompt in real files and patterns rather than describing the change in the abstract, and use Plan mode on anything larger so you can review the approach before code is written.
How fast is adoption growing?
Cursor reports that agent usage in Cursor has grown more than 15x in the past year, and tracks the shift across millions of developer sessions in its Developer Habits Report.
Sources & last verified
Cursor ships frequently. Facts verified against primary sources on July 27, 2026.
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