What is Agentic Coding?
An AI coding agent is a program that works on a software project step by step. Given a task, it reads the relevant code, makes changes across several files, runs commands such as tests, looks at the results and tries again until the task is done.
This is different from simple code suggestions, where an AI tool proposes the next few lines while a developer types. An agent takes the actions itself. So the important questions become: what is it allowed to do, and who checks the result? In our process, a developer sets the limits and reviews every change.
Where it needs care
- Security: agents can write code with weaknesses, just as people can.
- Code quality: code that works isn’t always easy to maintain.
- Secrets and private data: the agent sends the code it reads to the AI provider. Passwords and keys must stay out of reach.
- Hidden instructions: text in a file or web page can try to trick an agent (“prompt injection”).
- Over-trusting the output: AI can be confidently wrong.
Why businesses use it
Prototypes sooner: a working first version to test an idea before you commit a bigger budget.
More tests: agents can write automated tests (small programs that check your code still works), which makes later changes safer.
Refactoring: tidying up older code without changing what it does, even across many files.
Documentation: explaining how existing code works and keeping notes up to date.
Less repetitive work: routine changes, such as updating libraries, so developers spend more time on harder problems.
Our team uses a range of AI tools, including Claude, Codex, DeepSeek and Grok, and we choose the one that suits the task. Coding agents such as Claude Code (opens in a new window) have permission settings (opens in a new window) that control which actions need a person’s approval, and can block the agent from reading files such as passwords and keys. We set these up before an agent works on your code.
What we do for you
Supervised building: our developers use coding agents for suitable tasks and review every change.
Code review: we check code for bugs, security weaknesses and readability, whether a person or an agent wrote it.
Test setup: automated tests and checks that run on every change, so mistakes are caught early.
Safe settings: permission rules, no access to passwords and keys, and a separate test environment for the agent.
Adding agentic tools to your team’s workflow.
Team training and guidelines: what to use agents for, what not to, and how to review their work.
Is it right for you?
A good fit if
- You want a prototype or new feature sooner, and can test it properly.
- Your developers spend a lot of time on tests, documentation or routine changes.
- You have older code that needs tidying or upgrading.
- You use code review and version control (such as Git), or want us to set them up.
Maybe not if
- Safety-critical systems, such as medical or industrial control software, without strict review and testing.
- Teams with no code review process. Agents make mistakes, and someone has to catch them.
- Your contracts don’t allow code to be sent to an outside AI provider.
- You want software built with no developer involved. We don’t work that way.
How we work
Talk
We learn what you want to build, and what code and data the agent may see.
Plan
We split the work into small tasks and agree the review and test rules.
Build
The agent does suitable tasks; a developer reviews every change, and tests and security checks run before release.
Support
We fix issues, keep tests up to date and adjust the guidelines as you go.
Questions we get asked
Something else on your mind? Ask us.
How is agentic coding different from AI code suggestions?
Code suggestions propose the next few lines as a developer types. A coding agent works on a whole task: it reads the code, changes several files and runs tests to check its work.
Is AI-written code safe to use?
Not automatically. Like any code, it can contain bugs or security weaknesses. That’s why a developer reviews every change and automated tests run before anything goes live.
Will our code be used to train AI models?
It depends on the tool and plan. For Claude Code, Anthropic says it doesn’t train its models on code sent under commercial terms (Team, Enterprise and API plans) unless the customer opts in. We check the terms of any tool we use before it works on your code.
Can the agent see our passwords and keys?
It shouldn’t. We keep secrets out of the code and set rules that block the agent from reading those files. Claude Code, for example, lets you deny access to specific files.
Does it replace developers?
No. A developer decides what to build, checks the work and takes responsibility for it.
Are you a partner of any AI company?
No. We are independent and choose tools that fit the job.
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Claude, Claude Code, Codex, DeepSeek and Grok are trademarks of their respective owners. Mammoth Digital is not affiliated with or endorsed by any of them.
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