mAIo Assistant

A traditional résumé is static.

It lists experience, projects, and technologies, but it rarely shows how someone thinks, which problems they have solved, or how they made decisions throughout their career.

For recruiters, there is another challenge: after reviewing dozens or even hundreds of résumés, they still need to understand whether what is written there reflects knowledge that has actually been applied in practice.

That idea led to the mAIo Assistant: a way to turn my professional journey into an interactive experience.

A portfolio you can talk to

Instead of forcing every visitor to browse the same pages and consume information in the same order, mAIo starts with a question.

A recruiter may want to learn about my professional experience.

A developer may be more interested in the projects I have built.

Someone else may simply want to know which technologies I have worked with.

The idea is to let each visitor explore my journey based on what they actually want to discover.

The result is an experience somewhere between a résumé, a portfolio, and a conversation.

Why not simply start with AI?

When I started the project, it would have been relatively easy to place an AI model behind a text box and allow any kind of question.

But making an application like that publicly available would also mean accepting some problems from day one.

Every conversation could generate costs. Answers could move outside the context of my portfolio. A large number of requests could consume unnecessary resources. And the availability of the application would depend on external services.

So I decided to start in a different way.

The first version of mAIo works with a controlled set of topics related to my professional journey. The system tries to understand what the person wants to know and presents a response prepared for that context.

That makes the conversational experience possible without depending on generative AI for every interaction.

Simple first, intelligent when necessary

That decision ended up defining one of the most important ideas behind the project:

not every question needs AI to be answered.

If someone asks about my professional experience, projects, or main skills, much of that information is already known.

There is no reason to use a more expensive and unpredictable solution when a simpler approach can answer well.

AI becomes more useful when the question requires interpretation, combination of information, or a response that was not previously anticipated.

That is where the project can evolve into a hybrid experience.

Evolving without becoming dependent

The evolution of mAIo includes allowing more open-ended questions and using the content from my own knowledge base to find relevant information before producing an answer.

But there is an important difference: this layer should expand the experience, not become an absolute dependency.

If an external service is unavailable, reaches a limit, or has a problem, the controlled part of mAIo can continue answering the questions it already understands.

In other words, adding Artificial Intelligence should not mean making the application less reliable.

AI as part of the product

mAIo started as a different way to present my résumé, but it also became an exercise in how I think about products that use Artificial Intelligence.

For me, adding AI to a product does not simply mean connecting a model and sending every question to it.

It means deciding where AI really improves the experience and where a simpler solution is still the better choice.

That is probably the idea that best represents this project.

mAIo was not created just to prove that it is possible to put a chatbot inside a portfolio.

It was created to explore a different question:

what if, instead of just reading my résumé, you could talk to it?