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Non-Deterministic Loop Engineering: Progettare sistemi di Agentic AI affidabili nell'era dei loop
Paperback
Series: Sviluppo Software Non Deterministico, Book 4
Publisher: Independently Published
Published: Jul 22 2026
Pages: 250
Weight: 0.75
Height: 0.53 Width: 6.00 Depth: 9.00
Language: Italian
NON-DETERMINISTIC Loop Engineering
Progettare sistemi di Agentic AI affidabili nell'era dei loop
I sistemi di intelligenza artificiale stanno superando il modello della singola richiesta. Oggi possono pianificare, utilizzare strumenti, recuperare informazioni, modificare file, eseguire test, correggere errori e continuare a lavorare con una supervisione umana limitata.
Ma l'autonomia senza controllo non è ingegneria.
NON-DETERMINISTIC Loop Engineering, quinto volume della serie NON-DETERMINISTIC, presenta un metodo pratico per progettare sistemi di Agentic AI capaci di operare in modo persistente senza rinunciare ad affidabilità , responsabilità e controllo umano.
Il libro sposta l'attenzione dal singolo prompt all'intera struttura operativa che circonda il modello: obiettivi durevoli, stato esterno, verifica indipendente, tentativi limitati, budget, osservabilità , autorizzazioni, ripristino ed escalation.
Invece di considerare l'agente come un esecutore affidabile, ogni risultato generato viene trattato come una proposta che deve essere verificata attraverso prove esterne prima che il sistema possa proseguire.
Nel libro scoprirai come:
- distinguere prompt engineering, context engineering, harness engineering e loop engineering;
- progettare loop delimitati da condizioni esplicite di completamento e arresto;
- separare il Maker, che produce il lavoro, dal Checker, che lo verifica;
- utilizzare gli errori reali come feedback invece di ripetere tentativi alla cieca;
- scegliere tra contesto fisso, memoria persistente, retrieval e strumenti;
- isolare agenti concorrenti tramite Git worktree e regole di assegnazione;
- definire limiti di token, tempo, costo e numero di tentativi;
- proteggere test, policy e altri strumenti di verifica da manipolazioni opportunistiche;
- distinguere la correttezza tecnica dall'autorizzazione ad agire;
- progettare l'escalation umana come un esito previsto e riuscito del processo;
- valutare il costo per risultato accettato, non semplicemente il costo delle chiamate al modello;
- realizzare loop di AI locali su infrastrutture controllate;
- scegliere il meccanismo minimo necessario per affrontare ogni concreta modalità di errore.
Il volume affronta anche le conseguenze organizzative del lavoro agentico: l'evoluzione dei ruoli tecnici, le nuove responsabilità di governance, il rischio di impoverire la formazione dei professionisti più giovani e la necessità di gestire i sistemi autonomi attraverso prove verificabili invece che attraverso il semplice monitoraggio delle attività .
I capitoli pratici approfondiscono il Ralph Loop, le architetture di inferenza locale, le pipeline di verifica, i pattern operativi, le politiche di retry, i controlli di sicurezza, il coordinamento tra più loop e un case study completo sull'assistenza clienti che riunisce l'intero metodo in un'unica applicazione.
Questo non è un libro su come costruire agenti capaci di operare senza persone.
È un libro su come rendere una maggiore autonomia compatibile con la disciplina ingegneristica.
Per architetti software, responsabili tecnici, team di piattaforma AI, sviluppatori senior, dirigenti tecnologici e professionisti che progettano sistemi agentici destinati alla produzione.
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