If you've worked in software in the past 18 months, you've heard the phrase. Agentic coding has gone from niche to mainstream faster than almost any term in the field — and like most terms moving that fast, what it actually means has gotten fuzzy.
We're a team that ships agentic systems for clients, and we run our own development on agentic tools. So here's a working definition, the way we use it day-to-day.
The short version
Agentic coding is software development where an AI agent — not just an autocomplete tool — drives multi-step changes across files. The agent reads the codebase, plans the edits, runs the commands, executes the tests, and reports back. You stay in the loop, but you're not typing every line.
Compare that to:
- Autocomplete / suggestion tools (GitHub Copilot, original Tabnine) — predict the next few tokens. The human types.
- Chat tools (ChatGPT, Claude in a browser) — answer questions and generate code blocks you copy in. The human pastes.
- Agentic tools (Claude Code, Cursor agent mode, Aider, Devin) — read your repo, plan changes across multiple files, execute commands, and verify. The human reviews.
The shift is from AI as a co-typist to AI as a collaborator that can move through the project on its own.
What an agentic coding session looks like
A real session might go:
- You describe what you want: "Add rate limiting to the /api/contact route. Use a sliding-window pattern. Add tests."
- The agent reads the relevant files: the route handler, existing middleware, test helpers.
- The agent plans: it tells you what files it will edit, what library it'll use, and what tests it'll write.
- You approve.
- The agent edits the files, runs the test command, sees a failure, reads the error, fixes it, re-runs.
- The agent reports: tests pass, here are the diffs, do you want to commit?
Total elapsed time: under five minutes for a task that would take a developer 30–60 minutes of focused work.
That's agentic coding. The key properties:
- Multi-file context. The agent sees the project, not just the open buffer.
- Tool use. The agent runs commands — tests, linters, type checks, git.
- Plan-and-execute. The agent commits to a plan before editing, so you can intervene early.
- Feedback loops. The agent reads its own output (errors, test failures) and corrects.
How it differs from "vibe coding"
You'll see vibe coding used as a near-synonym. The connotation differs slightly:
- Vibe coding leans into the velocity angle: shipping software fast, often experimentally, with AI as a multiplier.
- Agentic coding leans into the architecture angle: AI as an agent that does multi-step work autonomously.
Both describe the same workflow most of the time. Vibe coding is the marketing term; agentic coding is the technical one.
Why this is a discipline, not a hack
Agentic coding is being treated as a "let the AI write your code" magic trick in some corners of the internet. That's misleading and it produces bad software. Agentic coding is a discipline with practices:
Practices that matter
- Scope your prompts tightly. "Build a SaaS" gets you garbage. "Add rate limiting to /api/contact with a sliding window, using Upstash, with tests" gets you working code.
- Read the plan before approval. When the agent says "I'll edit these 4 files and add this dependency" — read it. That's your insertion point for steering.
- Run the tests yourself. Don't take the agent's word for it. If it says tests pass, run them in another terminal.
- Review diffs like code review. The agent's code is code. It needs review. Speed is not a substitute for judgment.
- Keep changes small. Smaller scopes = easier review = better outcomes. The temptation is to dump a huge task on the agent — resist it.
- Maintain a clean repo. Agentic tools work much better on clean, well-organized codebases. The discipline pays back in tool effectiveness.
Skip the practices and agentic coding becomes a fast way to produce confidently wrong code. Apply them and you ship 5–10x faster with quality intact.
What it's good at — and what it isn't
Agentic coding shines at:
- Type-system migrations (e.g., JavaScript → TypeScript, schema changes across many files).
- Mechanical refactors (renaming, restructuring, lifting state).
- Adding tests to existing code.
- Wiring up new endpoints in established patterns.
- Writing the boring parts of a feature (CRUD, forms, dashboards) once the data model is clear.
It struggles at:
- High-stakes architectural decisions. The agent will pick an answer; that doesn't mean it's the right one for your context.
- Performance tuning that requires deep understanding of the system.
- Security-sensitive code where the failure mode is severe.
- Genuinely novel design. It's pattern-matching against training data — by definition, it's better at the well-trodden than the unprecedented.
The right mental model: agentic coding is great at execution of known shapes, weaker at design of new ones.
Common questions
Not anytime soon. It changes what developers do — less typing, more reviewing, more design — but the role of "person who understands the system and decides what should be built" isn't going away. If anything, that role becomes more valuable because each decision now ships faster.
Claude Code is what we use day-to-day at Futur Labs for most agentic work. Cursor's agent mode is excellent for in-editor work. Aider is great for surgical refactors. The space is moving fast — the right answer in six months might be different.
Pick one tool. Use it on a small, well-scoped task in a project you know. Review every diff carefully for the first week. You'll build intuition for what to delegate and what to keep doing yourself. Don't start with a critical production change.
If you review it like code (because it is code) and reject sloppy work, yes. If you accept anything the agent produces because "it works," no. Agentic coding amplifies your code review standards — high standards in produce high standards out.
Where to go from here
If you're interested in how this changes building software at the company level, our AI Agent Development service covers the production side of agentic systems — including the same patterns we apply to our own development.
If you're hiring someone to do this work for you, our hire a vibe coder page is exactly that.
And if you want to dive deeper into the discipline, our follow-up post — The agentic coding guide — gets into the practical workflows in detail.