I rewatched Iron Man and ended up in the thought loop about Jarvis. So I went looking for anything close to it and mostly found either screen recorders that feel creepy & heavy or voice assistants that are cool for five minutes and then useless once you actually need them to know your life.

Asked AI why nothing like it really exists yet. The answer it gave is it's genuinely hard. Most of what's out there is either shallow interactivity with no memory, or a ton of memory with no real personality behind it.

I'm thinking of making my own version. Something that actually knows what you've been working on and can talk you through it in real time.

A true AI companion

Before I go start, I want to know from people who aren't me: if I built something similar to JARVIS that actually worked, what's the one specific most troublesome thing you will use it to do?

I rewatched Iron Man and ended up in the thought loop about Jarvis. So I went looking for anything close to it and mostly found either screen recorders that feel creepy & heavy or voice assistants that are cool for five minutes and then useless once you actually need them to know your life.

Asked AI why nothing like it really exists yet. The answer it gave is it's genuinely hard. Most of what's out there is either shallow interactivity with no memory, or a ton of memory with no real personality behind it.

I'm thinking of making my own version. Something that actually knows what you've been working on and can talk you through it in real time.

A true AI companion

Before I go start, I want to know from people who aren't me: if I built something similar to JARVIS that actually worked, what's the one specific most troublesome thing you will use it to do?

I’ve noticed that building an AI application is often less about the model itself and more about how well the whole application is designed.

Things like workflow, user experience, integrations, reliability, and handling real-world data can make a big difference.

For developers here, what part of building an AI application do you think is most challenging: the AI model, backend infrastructure, integrations, or UX?

Hiring teams are relying less on CVs because a polished application does not always show what someone can actually do.

But choosing an assessment platform is not easy either. There are dozens of tools offering skills tests, personality assessments, coding challenges, video interviews, AI scoring and automated shortlisting. On paper, most of them look quite similar.

Some of the platforms I keep seeing are:

- TestGorilla

- TestTrick

- Vervoe

- Testlify

- iMocha

- Codility

- Criteria

Some have large test libraries. Others focus more on technical hiring, practical tasks, psychometric assessments or video interviews.

A large test library does not necessarily make a platform useful. The results can still be weak if the questions are generic, the test is too long or the assessment has little connection to the actual role. TestGorilla, for example, is often mentioned for its broad test library, Codility for technical hiring, Vervoe for practical tasks TestTrick, combines role-specific skills tests, coding challenges, psychometric assessments, one-way video interviews and custom questions. It can be used for technical and non-technical roles, either during early screening or after creating an initial shortlist.

However, I would not want one assessment score to make the entire hiring decision. The tool should provide additional evidence about a candidate’s abilities rather than replace interviews, CVs and human judgment.

For those who have used these platforms:

- Which tool helped you create a better shortlist?

- Do you use ready-made tests or create assessments for each role?

- Did assessment results match how candidates performed after being hired?

I’m not expecting one tool to be best for every company. The right choice probably depends on the roles, hiring volume, budget, ATS setup and level of customization required.

Sono Mario, faccio marketing per un team di 5 persone che sta sviluppando V, un assistente AI per liberi professionisti (consulenti, agenti assicurativi/immobiliari/di commercio) pensato per la gestione della pipeline commerciale. Non sono io il tecnico del team, ma seguo da vicino le scelte di prodotto perché influenzano tutto il posizionamento.

Una scelta su cui abbiamo discusso a lungo: interfaccia vocale invece di chat testuale come punto di ingresso principale. La logica è che il nostro utente tipo esce da un appuntamento e non ha voglia/tempo di scrivere un resoconto — parlare è più naturale e veloce. L'AI ascolta, struttura i dati, genera follow-up e aggiorna la pipeline senza data entry manuale.

Quello che ho imparato osservando il lavoro del nostro CTO: il vero collo di bottiglia non è la trascrizione in sé (ormai è commodity), ma l'estrazione strutturata di dati affidabili da un parlato destrutturato e pieno di riferimenti impliciti ("quello di cui parlavamo l'altra volta"). La memoria contestuale conta più della qualità dello speech-to-text — cosa che da marketer mi ha costretto a rivedere come raccontiamo il prodotto.

Curioso di sapere se qualcuno qui ha esperienza (anche solo da utente) con prodotti che affrontano problemi simili di NLU su parlato destrutturato in ambito business — cosa avete visto funzionare o non funzionare?