Third in a three-part series inspired by the roundtable Bitrock organized with nine Mobile Development and AI Professionals.
Having looked at how AI has made its way into mobile development and how it behaves across different frameworks, one question still looms largest: what does this actually change for people and for businesses?
On this topic, the Bitrock roundtable offered its deepest reflections — along with a few honest concerns.
Risk Number One: The “Yes-Man” Trap
The biggest danger isn’t technological — it’s an attitude. Get used to clicking “yes” on every AI suggestion without understanding what’s happening behind the scenes, and you turn into what the group called a “yes-man.” That behavior, warns moderator Samantha Giro, Mobile Manager at Bitrock, can become the real source of bugs: not seeing what you’re doing, or why, is a serious problem.
Carlo Lucera, Flutter Team Lead at Pivotal Technologies, ties this to understanding “why” something works: if a junior gets used to only reviewing generated code, then when the AI hallucinates or suggests an outdated pattern, “they don’t have the critical tools to catch it.” Human expertise on the framework, he concludes, remains the difference “between an app that holds up and one that breaks at the first system update.”
How Do You Train Juniors in Such a Fast-Moving World?
This is where the deepest concern surfaces. Alberto Dallaporta, founder of the consulting firm Novalab, raises an issue every company has to reckon with: “It’s genuinely hard to figure out how to grow people, when in six months they do a tenth of what we used to do in six months.” His advice to newcomers today is blunt: start from the basics of native code and platform knowledge anyway — permissions, platform-specific behaviors, the differences between iOS and Android — while cultivating curiosity and soft skills.
Emanuele Maso, an Android developer at Bitrock, echoes this, urging people to never let go of the drive to understand: “You still need that curiosity. If there’s a piece of code I don’t get, I ask the AI to explain it to me, because I want to understand things regardless.” For those just starting out, he suggests going deep on one technology, getting really good at it, and only then branching out: “The rest comes almost for free after that.”
Federico Nessi, an iOS developer at Bitrock, adds a valuable nuance. Before AI, learning meant spending hours tracking down why a bug happened — and that effort is what built expertise. “AI can shortcut that search, but my advice is to keep your curiosity alive: don’t just accept the solution, stay curious about why something works the way it does. That’s what gives you a real picture of how the machine works underneath.”
Client Expectations: Watch Out for the “Everything Free and Instant” Mindset
There’s also a chapter that touches the business side directly. Alberto Dallaporta, who deals with clients every day, describes a common and risky expectation: “A lot of people read sensationalist headlines and assume an app today costs half as much and takes half the time.” The reality is more nuanced: AI speeds up writing code, but that’s only a fraction of the project. “Requirements analysis, architecture, testing, UX design, and maintenance take the exact same effort as before, if not more, precisely because you need to validate what the AI produces.”
It’s the principle insiders sum up as “garbage in, garbage out.” Mauro Marinello, Data Scientist and Product Owner at Radicalbit (a solution within the Fortitude Group product portfolio) puts it well: AI doesn’t “think” about the business goal, it generates tokens on a probabilistic basis. “The role of the Product Owner, the analyst, and the architect becomes even more central: we’re the ones who have to set the boundaries the agent operates within. If the requirements are ambiguous, the AI will generate ambiguous code.”
One real example says more than a thousand explanations: the roundtable brought up the case of an influencer who had an AI “build” their own social network, only to end up with a hefty fine for mishandling privacy and GDPR compliance. Writing software — mobile or web — also means managing the lifecycle, data security, resource optimization, and regulatory compliance: skills AI doesn’t replace.
The Developer of the Future: A Director, Not a Keyboard Operator
If one line sums up the whole discussion, it’s from Marco Riva, AI engineer at Fortitude Group: “The focus needs to shift from pure code syntax to logic and architecture. Memorizing a language’s syntax matters less and less, because that’s exactly what AI does better and faster than we do. The developer of the future will increasingly be a director and a validator, and less and less a keyboard operator.”
A clear-eyed optimism prevails when it comes to the near future too. Stefano Mondino, an iOS developer at Synesthesia, is betting AI integration will become so natural it disappears entirely: “We won’t even talk about ‘using AI’ anymore — it’ll just be the standard way of coding, the same way today we don’t say ‘I’m using autocomplete.'”
The Takeaway
Mobile development is still here and it’s here to stay. AI won’t replace developers, because a well-built product is made by skilled people. The tool is incredibly powerful — but, as someone put it during the discussion, if you don’t know what to type, it just helps you break things faster.
The future rewards those who know how to ask the right questions, understand the why, and keep their curiosity alive — qualities no model, for now, can generate on our behalf.
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.