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  • Iterative Incremental #3 - Vibe Coding: My First Reaction and the Reasoning Behind It

    Iterative Incremental #3 - Vibe Coding: My First Reaction and the Reasoning Behind It
    2026/09/24
    When vibe coding went mainstream, my first reaction wasn't panic. It was curiosity. Then came a sharper question. The speed never bothered me. What bothered me was that not understanding the generated code had become part of the workflow, something you were supposed to accept.
    In this episode I talk through how I reasoned about it, based on years of XP and DevOps. TDD, refactoring and continuous delivery aren't rituals to skip: they're the brakes that make speed safe. Vibe coding takes out the understanding loop that comes before the tests. Public incidents showed what happens when understanding is treated as optional at the moments it matters most. This isn't an ideological stance against AI. I'm against using AI without discipline, and I wanted AI to help me carry the cost of discipline instead of skipping it.


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    23 分
  • Iterative Incremental #2 - What kind of engineer I want to be with AI?

    Iterative Incremental #2 - What kind of engineer I want to be with AI?
    2026/09/03
    🇮🇹 Che tipo di ingegnere voglio essere?
    Un anno fa ChatGPT era solo un taccuino per me — un posto dove ragionare ad alta voce, fare brainstorming, tenere un diario. Poi gli strumenti sono migliorati, l'hype è cresciuto, e ho sentito la spinta verso scorciatoie che non erano professionali. La domanda sbagliata era "dovrei usarlo o no?" Quella giusta ha cambiato tutto: che tipo di ingegnere voglio essere con questi strumenti? Questo episodio parla di quel cambio di prospettiva — e del perché la risposta non è un nuovo set di valori, ma amplificare le pratiche che già funzionano. Il "come" arriva nel prossimo episodio.

    🇬🇧 What Kind of Engineer Do I Want to Be?
    A year ago, ChatGPT was just a notebook for me — a place to think out loud, brainstorm, journal. Then the tools got better, the hype got louder, and I felt the pull toward shortcuts that weren't professional. The wrong question was "should I use this?" The right one changed everything: what kind of engineer do I want to be with these tools? This episode is about that shift — and why the answer isn't a new set of values, but amplifying the practices that already work. The "how" comes next.

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    17 分
  • Iterative Incremental #1 - Restarting on purpose

    Iterative Incremental #1 - Restarting on purpose
    2026/08/27
    Episode

    Iterative Incremental opens with a restart, not a comeback. After closing the Practical Handbook for Product Developers, I'm changing the object of study — not the practices. Same XP, Agile, Lean and DevOps foundations you know; new lens, focused on coding agents and what holds up under evidence rather than hype. No fixed runtime anymore: this episode takes exactly the space the thinking needs, which is the whole point of the new format.

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    14 分
  • The Weekly Pomodoro 25.13 - 🇮🇹 L'impatto dell'AI su come studiamo e come impariamo

    The Weekly Pomodoro 25.13 - 🇮🇹 L'impatto dell'AI su come studiamo e come impariamo
    2025/10/23
    🎙️ “L’AI non solo scrive, ma pensa (al posto tuo?)”
    Ogni settimana siamo sommersi da più contenuti di quanti ne possiamo leggere. E ora l’AI non si limita più a generarli — li sceglie, riassume e spiega per noi.
    In questo episodio esploriamo come l’intelligenza artificiale stia trasformando il modo in cui impariamo: dal passaggio da blog e corsi a feed generati dall’AI, fino ai nuovi modi di studiare, dialogare e insegnare con gli LLM.
    Scopriremo:
    • come il micro-learning e il “learning by chat” stanno cambiando la nostra attenzione e la profondità di comprensione;
    • dove si nasconde il trade-off tra velocità e riflessione;
    • perché ogni lettore oggi è anche autore — ma non sempre un buon insegnante;
    • e un mini-caso reale: un developer che impara solo tramite chat AI… cosa guadagna e cosa perde.
    Chiudiamo con una sfida: 📈 per 48 ore, traccia come impari — con e senza AI — e scopri dove nasce davvero la comprensione.
    🎧 25 minuti di pratica, curiosità e consapevolezza su come l’AI sta riscrivendo l’apprendimento.

    Seguimi su Linkedin: https://www.linkedin.com/in/daniele-scillia/

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    23 分
  • 🎙️ The Weekly Pomodoro 25.12 – 🇮🇹 L’AI nella programmazione risolve davvero il problema giusto?

    🎙️ The Weekly Pomodoro 25.12 – 🇮🇹 L’AI nella programmazione risolve davvero il problema giusto?
    2025/10/16
    L’AI scrive codice più veloce, ma… era davvero questo il problema? In questo episodio analizziamo i veri colli di bottiglia nello sviluppo software: comunicazione, delivery, debito tecnico e decisioni lente. Capiremo dove l’AI può davvero accelerare (testing, review, refactoring) e dove invece rischia di peggiorare la qualità. Chiudiamo con una sfida pratica: in 48 ore, mappa il collo di bottiglia più grande del tuo team — e portalo in retro o stand-up.

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    26 分
  • The Weekly Pomodoro 25.11 - 🇮🇹 Continuous Integration vs Delivery vs Deployment

    The Weekly Pomodoro 25.11 - 🇮🇹 Continuous Integration vs Delivery vs Deployment
    2025/06/26
    🚨 CI/CD ≠ Pipeline automatizzata
    E no… non sono solo nomi altisonanti per la stessa cosa. La maggior parte dei team sbaglia su questo punto.
    E questo porta a rilasci più lenti, build rotte e sviluppatori confusi. Ma una volta che ho capito davvero le differenze…
    Come si costruiscono l’una sull’altra…
    E come un concetto semplice—il Trunk-Based Development—sblocca tutto... 🚀 È stato lì che velocità e affidabilità di delivery sono esplose. Oggi, nel nuovo episodio del mio podcast Weekly Pomodoro, ne parlo nel dettaglio:
    → Cosa significano davvero CI/CD
    → E come implementarli in modo efficace Se anche tu hai mai annuito in riunione facendo finta di capire la differenza tra i tre... 👀
    O vuoi finalmente sbloccare la tua pipeline di delivery... Devi assolutamente ascoltare l’episodio di oggi!

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    24 分
  • Weekly Pomodoro 25.10 - 🇬🇧 LLMs or XP? What’s Really Boosting Developer Productivity

    Weekly Pomodoro 25.10 - 🇬🇧 LLMs or XP? What’s Really Boosting Developer Productivity
    2025/06/12
    🧠 It looks like LLMs are making devs 10x more productive.

    But something else might be... Over the past few months, I’ve been watching a pattern emerge.
    Devs rave about LLMs massively boosting their output. PMs boast about faster features. Founders post screenshots. VCs… well, they think they found the next gold mine. But when I zoomed in, something felt off.

    The devs getting the most value from AI agents aren’t doing anything “new.” They’re doing this instead:
    ✅ Writing tight, testable code
    ✅ Working in small, iterative steps
    ✅ Focusing on feedback and flow
    ✅ Getting clarity before coding
    ✅ Refactoring relentlessly

    Sound familiar? It should. That’s the original Extreme Programming (XP) playbook. And it’s looking more relevant now than ever—just wrapped in AI.

    🚀 So what’s really driving productivity here?
    → Is it the machine, or the mindset?
    → The assistant, or the agile habits? I


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    21 分
  • The Weekly Pomodoro 25.9 - 🇮🇹 Esperimenti con Cursor

    The Weekly Pomodoro 25.9 - 🇮🇹 Esperimenti con Cursor
    2025/05/29
    🚀 Are AI-assisted IDEs the future of development? 🤔

    In today's world, tools like Cursor are pushing the boundaries of what AI can do for developers. But... are they truly the game changers we’ve been waiting for?
    💡 After experimenting with Cursor in my daily development workflow, I’ve found some amazing advantages, but also some challenges.

    Here’s a sneak peek into my findings.

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    26 分