AI Driven Development: How I Work and Why You Should Hire Me
In the world of software development, AI is not a passing trend. It's a new way of working that, when applied correctly, multiplies a developer's capacity by 5, 10 or even more. I've been doing it deliberately and systematically. Let me tell you how, and why that matters for your project.
What is AI Driven Development?
AI Driven Development (AIDD) is not simply asking a chatbot to write code. It's a work philosophy that integrates AI at every stage of the development cycle:
- Design and architecture: I use AI to explore options, detect risks before starting, and validate technical decisions.
- Implementation: Tools like Cursor, Claude Code, or Copilot accelerate code writing with real project context.
- Testing and QA: I automatically generate test cases, mocks, and fixtures, covering more scenarios in less time.
- Review and refactoring: AI detects duplicated code, technical debt, and improvement opportunities that a human eye might miss.
- Documentation: Changes are documented almost in real time, without friction.
The result: fewer bugs, more speed, higher quality coverage, and a developer who can do the work of a team in certain contexts.
How I Do It in Practice
1. I work with agents, not just autocomplete
I don't use AI as glorified autocomplete. I work with agents that understand the full project context: the stack, architectural decisions, established patterns, and client requirements.
Tools I use regularly:
- Claude Code: for complex refactoring tasks, feature creation, and code analysis
- Cursor: for contextual editing and inline generation within the IDE
- Claude API: to build custom automations within my clients' projects
2. I iterate fast with context
Every prompt I send carries context: relevant files, technical constraints, project conventions. This prevents AI from generating generic code that needs to be rewritten. The output is code that fits from the first iteration.
3. I always supervise
AIDD doesn't mean delegate and forget. It means working as a team with AI while I maintain technical judgment: I review every generated code fragment, understand what it does and why, and make the important architectural decisions.
AI amplifies my capabilities. I bring the judgment.
4. I automate the repetitive to focus on what adds value
Regression tests, test data generation, component scaffolding, API documentation: everything that can be automated, I automate. That frees me to think about user experience, scalability, what really matters for the client's business.
Why This Matters for Your Project
If you hire a developer who doesn't use AI (or uses it superficially), you're paying for hours of manual work that could be drastically reduced.
If you hire me, you get:
Real speed, not promised speed
I launch functional MVPs in days, not weeks. Complex features that used to take entire sprints are now delivered in working days. That translates to less cost for you and less time to market.
Sustained quality
AI doesn't replace quality: it enhances it. By automating testing and review, the code I deliver has greater coverage and less technical debt than that produced with traditional methods.
Adaptability
I work with diverse types of projects: from local business websites to enterprise AI integrations. AIDD allows me to enter unfamiliar stacks faster and propose solutions aligned with the state of the art.
Transparency and communication
I explain what AI is doing, what decisions I make, and why. No black box. The client understands what they are receiving.
A Concrete Example
I recently developed a document management system with AI for a client. The architecture, generation of main components, unit tests, and technical documentation were completed in less than one week.
With a traditional team, the same project would have required 3 or 4 weeks just in the initial phases. The difference is not magic: it's method.
What Kind of Projects Make Sense to Hire Me For?
AIDD adds the most value when:
- The project has a tight deadline and needs speed without sacrificing quality
- AI integration is required as a product feature (chatbots, agents, automations)
- The client wants a functional MVP to validate before investing in a large team
- There is accumulated technical debt slowing down product evolution
- Documentation or testing is needed that the current team doesn't have capacity to address
Conclusion
AI Driven Development is not the future. It is the present for developers who want to deliver more value, faster, and with higher quality.
If you have a project that requires this level of capability, I'd love to talk with you.