Talking about Artificial Intelligence is relatively simple. Every day, new tools, more advanced models, and professionals appear explaining all the incredible things we supposedly can do by applying AI.
However, there is a quite big difference between talking about Artificial Intelligence and using it to build a real product, thus turning an idea into reality. Conceiving in this way a product that has users, that solves a problem, that automates processes, that needs to evolve, and that, furthermore, must keep working when technology does not behave exactly as you expected.
Precisely for that reason, I created Palomiteros, a project that began as a different way to recommend movies and has ended up becoming a digital ecosystem where Artificial Intelligence, product design, automation, film reviews, SEO positioning, and business models converge.
It is because of all this that Palomiteros is not just a movie website. It is a research and innovation project about an overcrowded sector, such as the movie world, but conceived from a different perspective where innovation and product design make the true difference in how things are done to position oneself in this market.
This is why Palomiteros is an example extracted from my personal research laboratory in the world of AI that has become an example of applied innovation and a clear demonstration of how I apply all my capabilities to turn any idea into reality through functional and tangible solutions.
What is Palomiteros?
Palomiteros is a platform designed to help you find what movie to watch.
It seems like a simple problem, but if you think about it, you have surely experienced more than once spending half an hour browsing catalogs, switching platforms, and reading synopses only to end up watching something you had already seen.
The problem is not that movies are lacking. The problem is that we have too many options and very few tools that understand what we actually feel like watching at any given moment.
Therefore, Palomiteros does not limit itself to showing a list of popular titles. Its recommender uses Artificial Intelligence to interpret what a person is looking for and turn a more or less open request into a meaningful selection of movies.
You can ask for a story to watch with family, an intense movie for a Saturday night, a little-known production, or something similar to a work you have especially enjoyed.
The important thing is not solely that the system finds movies.
The important thing is that it is capable of understanding a human need expressed in our own words.
Furthermore, with Palomiteros I have created all the necessary solutions to manage everything related to the generation of expert film critique content for the website itself and for social networks with a single button, in order to have a scalable product manageable solely by myself.
An AI solution that starts with a real problem
When talking about incorporating Artificial Intelligence into companies, many times people start with the technology. And I experience quite a few conversations in my day-to-day life that begin with any of these phrases:
- “We want to use AI.”
- “We have to build an agent.”
- “We need a chatbot.”
However, no one seems to have done a proper product design exercise that allows defining clearly what problem wants to be solved.
With Palomiteros, I followed the opposite path. First, I identified a rather everyday problem: choosing a movie has become a surprisingly frustrating experience. Accessing catalogs on platforms like Netflix and HBO becomes increasingly complex when deciding what to watch.
In fact, I am a huge cinephile, one of the few (I think) remaining today who still prefers the physical format over platforms and who is always looking forward to discovering new movies to watch.
It was from these needs and my passion for innovation, research, and the ability to turn ideas into reality that I started exploring how I could use Artificial Intelligence to reduce that friction in a simple way and thus help people make a decision on what movie to watch, while helping myself discover new movies for my collection.
And this is one of the most important points. Palomiteros was not born to prove that I was capable of integrating an AI inside a webpage. It was born to solve a problem using AI wherever it could provide a differential capability.
And this is also the mindset I apply when working on any business project: first we understand the problem, then we design the experience, and finally we choose the necessary technology to make it possible... (and not the other way around).
From movie recommender to expert digital movie ecosystem
One of the most interesting things that happen when developing a product is that you start by trying to solve a specific problem and, as you move forward, you discover new needs and opportunities.
In Palomiteros, the recommender was the starting point, but it soon became clear that recommending a movie was only part of the experience for anyone in the process of searching for a movie to watch.
People also want to understand why that movie is worth watching, discover related titles, consult selections and thematic guides, and know on which platforms they can find each of those contents.
This caused Palomiteros to progressively evolve to incorporate features such as:
- An Artificial Intelligence-based movie recommender.
- A catalog of film analysis and reviews.
- Editorial guides on genres, actors, directors, and platforms.
- Tools to search and filter content.
- Information on where a movie can be watched depending on the country.
- Automated and human-supervised content generation editorial processes.
- Systems to transform contents into formats adapted for different social media formats.
- Different connection pathways between recommendation, content, and business.
And most importantly, none of this appeared all at once.
The product has been built incrementally, identifying needs, creating small solutions, testing them, and learning from the results.
It is, in essence, the same philosophy I apply when developing a minimum viable product: advancing as much as possible while reducing uncertainty in the process instead of trying to build a gigantic and supposedly perfect solution from day one.
In fact, Palomiteros is imperfect; like any good project, it is a little plant that needs to be watered day by day, and only a creative, innovative, and strategic mindset is capable of watering that plant in the most appropriate way. Up to the day of writing these lines, AI has not solved everything related to everyone's personal criteria.
Where is the Artificial Intelligence of Palomiteros really located?
The most obvious thing would be to think that the AI is exclusively in the recommender.
However, its true value lies in how it participates in different parts of the product without trying to control the entire system.
Artificial Intelligence helps understand requests, generate proposals, structure information, and speed up certain editorial processes. But around it exists a whole system of rules, data, validations, and tools that allow turning its responses into a consistent experience.
This is one of the most important lessons that the development of Palomiteros has given me and which is applicable to any company:
A professional Artificial Intelligence solution is not simply a call to a model. It is the entire system you build around it so that capability is useful, controllable, and sustainable.
AI can propose, interpret, or write, but there are decisions that must be solved with structured data, others through rules, and others that need a lot of creativity, strategy, and human criteria.
Knowing how to separate those responsibilities is a fundamental part of the work.
Using AI well does not consist of using it for everything. It consists of knowing how to mark exactly the boundary where it provides value and complements the human being.
The importance of maintaining human criteria
One of the risks of generative Artificial Intelligence is assuming that everything it produces is ready to be published or used.
In Palomiteros, AI allows speeding up an important part of the work, but the contents can be (and in fact are) reviewed and modified by a person.
Guides can be edited, movies can be added, removed, or reordered, and the generated content can be adapted when the editorial criteria deem it necessary.
This allows combining the speed of Artificial Intelligence with the experience and responsibility of a human editor.
The goal is not to replace human criteria, but to multiply its capability.
A person no longer has to start every task from a blank page, but still retains control over the final result.
This balance is especially important in business projects. Automating a process should not mean giving up understanding it nor losing the ability to intervene when necessary.
Designing with the mindset that things might not go well
A technological demonstration is usually prepared so that everything works perfectly for a few minutes.
A real product does not have that privilege or that space.
In a system like Palomiteros, different information sources and automatic processes intervene which may take longer than expected to give a response, reach a limit, or be temporarily unavailable, and that must also be taken into account when designing the solution.
Therefore, an essential part of the work consists of designing what happens when something fails.
If a secondary task cannot be completed, the user should still receive the useful part of the experience. If information changes frequently, it should not be turned forever into static content. If a process takes too long, it must be able to be split, resumed, or executed without blocking everything else.
These are decisions that normally do not appear in the most superficial conversations about Artificial Intelligence but determine whether a solution can be used in a real business.
Building products with AI also means knowing how to manage errors, costs, response times, and dependencies.
The spectacular part of Artificial Intelligence attracts attention. The invisible part is what keeps the product running.
Palomiteros is also an editorial system
Another lesson learned from the project has been understanding that generating content is only the beginning.
That content must be able to be found, reviewed, updated, and reused.
A film guide can be useful inside the blog, participate in Google search results, and subsequently become a visual piece for social networks. A review can provide editorial value, help the user decide, and connect with other areas of the product.
All of this forces us to think of content as part of a system and not as a succession of isolated texts.
Artificial Intelligence allows automating processes and speeding up production, but it is product design that ensures that production is done intelligently and makes the very system created for managing the entire product an asset in itself for any company that wants to manage its content on the internet and its social networks in a simple way.
This difference is especially relevant for any company thinking of using generative AI. Creating hundreds of contents is of little use if afterwards no one can organize, maintain, or integrate them into their business processes.
From content to business model
Palomiteros was not conceived solely as a technological experiment either.
From its initial evolution, I have worked to connect the utility offered to the user with potential paths for economic sustainability.
When a person discovers a movie, the product can help them locate where to watch it or find related alternatives. Some of these interactions can become affiliation opportunities or future collaboration avenues with platforms and companies in the sector.
But the order is important.
First, utility is generated. Then, it is identified how a part of the created value can be captured.
Trying to monetize an experience that does not yet solve any problem well is usually a quite effective way to ensure no one wants to use it.
Palomiteros allows me to experiment not only with Artificial Intelligence, but also with acquisition, content, positioning, automation, and digital business models.
That is why I consider it a product and not simply a movie website. In fact, the very content and social media manager that I have created underneath perhaps has more value than the resulting output itself which can be seen through the website.
Palomiteros is just another example of my way of working
Palomiteros concentrates a good part of the disciplines I have developed during my professional career.
On one hand, there is product design work: detecting a need, understanding the user, defining a value proposition, and turning it into a simple experience.
On the other hand, there is an innovation component: exploring technological capabilities, combining them in different ways, and finding opportunities that were not evident at the beginning.
There is also a deep application of Artificial Intelligence, not only as a response generator, but as part of a broader solution connected with contents, automations, data, and business processes.
And, finally, there is execution.
Because an idea does not generate value for being interesting. It generates value when someone is able to turn it into a reality that can be used, tested, and improved.
I did not create Palomiteros to prove that I know how to make a movie website. I created it because cinema was a perfect context to experiment with problems that also appear in many companies:
- Information overload.
- Difficulty in making decisions.
- Costly editorial processes.
- Content difficult to maintain.
- Dependency on manual tasks.
- Constantly changing information.
- Social media maintenance.
- Need to connect user experience and business results.
The concrete solutions change from one sector to another, but many of the challenges are surprisingly similar.
Being an expert in applied AI implies knowing how to turn ideas into systems
Knowing an Artificial Intelligence tool can be learned relatively quickly. In fact, I do not consider myself an expert in AI tools. Honestly, I am not able to keep up with the pace at which new services based on this technology appear.
What I do know is how to use it to build a product that provides value to users and the business while combining different technical solutions based on AI (or not) to address the different business objectives that any company might have.
For this, it is fundamental to understand the business where AI wants to be applied and my product design methodologies, design an experience, organize information, control risks, and maintain a coherent vision while the project evolves.
As I explain in my article on how to use Artificial Intelligence in companies, the difference is not solely in writing better prompts. The real difference lies in knowing how to direct different capabilities toward a specific objective.
Palomiteros is the visible result of that way of working.
Behind what could seemingly be a movie recommender and a film review blog exists a product that combines Artificial Intelligence, design, automation, content, human supervision, and business vision.
And all this is not a theoretical presentation about everything that could be done with AI in a company. Palomiteros is a project that is already running.
A laboratory to keep building
Palomiteros continues to evolve because a digital product is never completely finished.
Each new need allows exploring a solution. Each problem forces revising a decision. Each improvement opens possibilities that were not evident in the previous version.
That is precisely what interests me the most about building products and services: turning initial uncertainty into something tangible and using real learning to decide what the next step should be that brings value to users and the business through technology and, in this case, Artificial Intelligence.
Palomiteros is a "simple" example that aims to represent my way of understanding innovation applied to business and process automation, and that allows me to validate to what extent it is true that the businesses of the future can be managed by a single person thanks to the use of AI.
It is not about chasing every new technological trend nor adding Artificial Intelligence to any process just because it is trendy.
It is about observing a problem, imagining a solution, and gathering the necessary capabilities to make it a reality.
If you want to better understand everything I have explained here, I invite you to try Palomiteros. Since I believe the result explains my work better than any list of tools or this entire post, although, honestly, now you will see that "simple" website understanding a bit better everything behind it.
Although if what truly interests you is applying this way of working to your company and you want someone to help you integrate Artificial Intelligence into your business, you can connect with me on LinkedIn and we can evaluate your specific case.
