Guide · Updated October 2026
AI coding tools write plausible code quickly. Plausible is not the same as correct, secure, or right for your system. As the cost of producing code falls, the review becomes the place where quality is decided.
What the tools are good at
- Boilerplate and repetitive code.
- First drafts of well-understood patterns.
- Scaffolding tests.
- Translating between languages and frameworks.
- Explaining unfamiliar code.
Used for these, they save real time. The risks appear when a draft is treated as a finished change.
Where the risks sit
Code that looks right and is wrong
Generated code tends to handle the common path well and miss the edges: empty inputs, time zones, concurrency, partial failures. It compiles, it reads cleanly, and it is wrong in a way only someone who knows the domain will notice.
Security gaps
A model reproduces common patterns, including common mistakes. Missing authorisation checks, unvalidated input, secrets placed in code, and permissive defaults all look normal in a diff.
Dependencies
Suggestions can include packages that are outdated, unmaintained, or do not exist. Every new dependency deserves a human decision.
Fit with the system
A tool sees the file in front of it, not the history of the codebase. It will duplicate a helper that already exists, ignore a convention, or pick an approach that fights the architecture.
Data and licensing
Know what leaves your environment in prompts, and what your organisation's policy says about generated code. These are decisions for the company, not for each engineer.
What a senior review adds
- It asks whether the change should exist at all.
- It reads for authorisation and data handling, not only style.
- It checks that the tests test the behaviour, not the implementation.
- It holds the architecture of the whole system in mind.
- It puts a named person behind the result.
A process that keeps the speed
- Treat AI output as a draft from a fast junior colleague.
- Keep changes small enough to review properly.
- Require tests with every change, and read the tests.
- Run static analysis, dependency scanning, and secret scanning in the pipeline.
- Give authentication, payments, and data access a second reviewer.
- Write down which tools are allowed to see which code.
The cost question
AI assistance lowers the cost of producing code. It does not lower the cost of being wrong in production. Teams that keep their review standards get the speed without the incidents. We look at the numbers in AI-assisted software development in 2026: cost, speed and quality.
Where TechMaven stands
We are a senior-led studio, and the team that scopes a project is the team that ships it. Review by experienced engineers is how the work is done, with or without AI tools in the loop. For AI features inside a product, see RAG vs fine-tuning and our AI solutions page.