First in a three-part series inspired by the roundtable we organized with nine Mobile Development and AI Professionals.
For many mobile developers, there’s a specific moment when AI stopped being a curiosity and turned into part of the job. Stefano Mondino, an iOS developer at Synesthesia for the past fourteen years, tells the story with a hint of irony: “Back in December, I never imagined I’d end up at an AI roundtable — I was pretty skeptical. Then, starting in January, everything changed for mobile.” It wouldn’t be the first time Mondino got it wrong: back in 2007, he wrote off the iPhone as a passing fad too. “Looking back, it was pretty easy to see how that story was going to end,” he admits.
To take the measure of just how deep this shift runs, Bitrock gathered nine leading voices for a virtual roundtable: Android, iOS, Flutter, React Native, and Kotlin Multiplatform developers, joined by two AI specialists.
This first piece tackles a question that’s simple to ask but harder to answer: what does AI actually mean today for app developers, and how should they be putting it to use?
No Longer a Novelty, but a Daily Habit
The first takeaway is that AI has worked its way into everyone’s workflow — only the degree varies. Some rely on it like a chatbot, others let it run as an autonomous agent, and others just use it to quickly get their bearings in unfamiliar code. Marco Gomiero, Principal Android Engineer and Google Developer Expert, is one of the most extreme cases: “I haven’t written a line of code myself in over a year. We use it constantly, at work and on side projects alike. I’ve never been happier.”
Some teams are already going all-in on fully “agentic” development. Carlo Lucera, Flutter Team Lead at Pivotal Technologies, described a shift his team was living through at that very moment: “We’re moving on from the usual chatbot-in-the-IDE setup toward full agentic development, where our job becomes reviewing pull requests and fixing the code.”
The Metaphor Trap: Junior, Senior, or Intern?
One of the liveliest debates centered on a gut-level question: does AI act more like a junior teammate, a senior consultant, or an intern who occasionally messes things up? The group’s answer, pretty much in chorus, was that none of these labels quite fit — it all comes down to how the tool is steered.
Federico Nessi, an iOS developer at Bitrock, comes up with the sharpest analogy: “Think of it as a Formula 1 car — insanely fast if you know how to handle it, but you really need to know what you’re doing.” Stefano Mondino, who says he’s never been comfortable personifying models, would rather picture it as “a keyboard typing at breakneck speed” — one that needs to be set up just right before it writes what you actually have in mind.
The AI specialists bring the conversation back down to technical reality. Mauro Marinello, Data Scientist and Product Owner at Radicalbit (part of the Fortitude Group product portfolio), cuts straight to the point: “A model is nothing more than a token generator. Whether it behaves like a junior or a senior comes down entirely to how well we prompt it.“
The Real Engine Is Context
And that’s really the crux of it. AI’s value doesn’t come from the model itself, but from the quality and structure of what you feed it. “Picture the model as a box of information,” Marinello explains. “The more organized that information is, the better the output. Type ‘build me a diet app’ and nothing else, and you’ll get junk. But bring in skills, hook it up to an MCP server, and take the time to write a solid system prompt — and everything changes.”
His colleague Marco Riva, AI engineer at Fortitude Group, shares an example worth pondering for anyone new to these tools: the exact same model, with the exact same setup, can produce wildly different results depending on who’s behind the keyboard. “Hand it to someone with zero development background versus a seasoned expert, and you’ll get completely different outcomes. How much value you get out of the tool depends on how skilled you are.”
The Starting Point
If there’s a single thread running through this first conversation, it’s this: AI has cranked up speed dramatically, but it hasn’t moved the center of gravity an inch. What still decides the outcome is the skill of whoever’s using it, and how carefully they set the context. It’s an extraordinarily fast keyboard — but somebody still needs to know what to type.
The next two installments dig deeper: why agents tend to “gravitate toward” certain frameworks and what that means for tech choices going forward, and why — even with all this automation — human expertise and soft skills are still what really sets people apart.
Three-part series — Watch the Roundtable again
Speakers: Federico Monti (MOLO17), Stefano Mondino (Synesthesia), Carlo Lucera (Pivotal Technologies), Marco Gomiero (Airalo / Google Developer Expert), Federico Nessi (Bitrock), Emanuele Maso (Bitrock), Alberto Dallaporta (Novalab), Mauro Marinello (Fortitude Group), Marco Riva (Fortitude Group).
Moderator: Samantha Giro, Mobile Manager at Bitrock.