Where they help
- Scaffolding screens, API clients and CRUD
- Writing and expanding tests
- Refactoring and renaming
- Explaining unfamiliar code
- Drafting documentation and migration scripts
Where they need supervision
- Authentication and authorisation
- Data models and migrations
- Payment and personal-data flows
- Performance-critical paths
- Anything touching secrets or production systems
Hidden costs
| Cost | How it shows up |
|---|---|
| Review time | Engineers must read and understand generated code |
| Rework | Plausible but wrong code found late |
| Security fixes | Missing access checks or exposed secrets |
| Maintenance | Inconsistent patterns across files |
| Tool and API spend | Subscriptions and usage charges |
How we use them
- Engineers write specs and plans; tools draft code.
- Everything is reviewed, tested and scanned.
- Security-sensitive parts are written or checked by senior engineers.
- We pass the time savings on through fixed-price packages such as a full ERP with mobile app delivered for a manufacturing plant at $650.
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Frequently asked questions
Do AI assistants make projects cheaper?
Often for well-defined work, but only if review and testing are kept; otherwise costs return as rework.
Can a non-developer replace an engineer with AI tools?
For prototypes, sometimes; for production systems you still need engineering judgement.
Is AI-generated code lower quality?
It can be, which is why review, tests and security checks matter.
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