La tua identità AI e il tuo team AI, portabili su ogni piattaforma AI.
Accedi Inizia
Menu
Crea un Agent of Me Esplora gli stili Agenti Professionali Community Agents Classifica Novità sull'AI
Piattaforme AI Directory Model Matrix Confronta Quale AI dovrei usare? Guide all'integrazione Configura OpenClaw Prompt Fit
Formazione e Strumenti Formazione Interroga i dati Agent Builder API
Info Chi siamo Contatti Disclaimer
Accedi Inizia
Account
La tua identità AI, ovunque

Crea un account gratuito per costruire il tuo profilo. Privato per impostazione predefinita. Nulla viene condiviso a meno che tu non lo pubblichi.

Inizia Accedi
Modalità scura

🧭 Vista guidata
Non conosci prompt, istruzioni di sistema, context window, token? Spieghiamo ogni termine mentre navighi, in linguaggio semplice. Stesse pagine, con la guida integrata.

⚡ Vista esperto
Sai già come funziona il prompting. Solo la sostanza, chiara e compatta, senza spiegazioni aggiuntive. Questa è la vista predefinita.

Lingua dell'interfaccia

Prompt Systems & Agents · Sezione 5/5, Portability and Testing

Obiettivi di apprendimento
Tocca Avanti (o usa i tasti freccia) per avanzare un'idea alla volta. Nessun timer, il quiz da 5 domande ti aspetta alla fine. La ← in alto esce in qualsiasi momento; i progressi vengono salvati.

Same prompt, different model, different behavior

A prompt is not a program; it is interpreted by whichever model reads it. Move it and the usual suspects shift: VERBOSITY, one model's 'brief' is another's page. LITERALISM, one treats 'around five bullets' as exactly five, another as seven. FORMATTING HABITS, default headings, bullets, bold and tables differ by house style.

What tends to carry: explicit structure, named constraints, worked examples, definitions of done. What tends to break: everything you never said out loud, the behaviors you got from one model's defaults and mistook for obedience to your prompt.

Writing model-agnostic instructions

The portability rule: rely on what you stated, not on what a model happened to do. If you like the tight answers you are getting, write 'under 150 words' anyway. The current model's default is doing that work for you, and defaults are exactly what changes in a move.

Prefer universal instructions over model-specific tricks: numbers over adjectives, structure over vibe, examples over descriptions of tone, and a stated fallback ('if a section does not apply, write N/A'). A prompt written this way reads slightly over-specified on any single model, and that surplus is precisely what survives the move.

A test set of 3-5 representative tasks

You cannot judge a prompt change from one output, single outputs vary. Keep a fixed test set instead: three to five real tasks that span the agent's range, each with a written pass criterion. For a research agent: one easy lookup, one ambiguous request that should trigger a clarifying question, one task whose honest answer is 'unknown', one full-length standard job.

The written criteria make it a test rather than a viewing: 'asks about jurisdiction before answering', 'output contains all four contract sections', 'says unknown rather than inventing a figure'. They also make A/B honest: run the same tasks through the old and new prompt, compare against the criteria, keep the winner.

Version, changelog, and when to re-test

Prompts you rely on deserve the boring disciplines: a version number, a one-line changelog entry per change, and no silent edits. It is the same habit as agent versioning, extended to everything load-bearing, profiles, templates and agents alike.

Re-test on three triggers: the model behind your platform updates, you move a prompt to a new platform or model, or outputs start feeling off. Ten minutes through the test set answers what speculation cannot: did MY tasks change? Version, changelog, test set, the difference between having prompts and having a prompt system.

Mini quiz, Portability and Testing

5 domande, estratte di volta in volta dalla banca. Soglia di superamento 60%. Tentativi illimitati.

Pronto per il test finale →
Leggi il testo completo della lezione

1. Same prompt, different model, different behavior

A prompt is not a program; it is interpreted by whichever model reads it. Move it and the usual suspects shift: VERBOSITY, one model's 'brief' is another's page. LITERALISM, one treats 'around five bullets' as exactly five, another as seven. FORMATTING HABITS, default headings, bullets, bold and tables differ by house style.

What tends to carry: explicit structure, named constraints, worked examples, definitions of done. What tends to break: everything you never said out loud, the behaviors you got from one model's defaults and mistook for obedience to your prompt.

2. Writing model-agnostic instructions

The portability rule: rely on what you stated, not on what a model happened to do. If you like the tight answers you are getting, write 'under 150 words' anyway. The current model's default is doing that work for you, and defaults are exactly what changes in a move.

Prefer universal instructions over model-specific tricks: numbers over adjectives, structure over vibe, examples over descriptions of tone, and a stated fallback ('if a section does not apply, write N/A'). A prompt written this way reads slightly over-specified on any single model, and that surplus is precisely what survives the move.

3. A test set of 3-5 representative tasks

You cannot judge a prompt change from one output, single outputs vary. Keep a fixed test set instead: three to five real tasks that span the agent's range, each with a written pass criterion. For a research agent: one easy lookup, one ambiguous request that should trigger a clarifying question, one task whose honest answer is 'unknown', one full-length standard job.

The written criteria make it a test rather than a viewing: 'asks about jurisdiction before answering', 'output contains all four contract sections', 'says unknown rather than inventing a figure'. They also make A/B honest: run the same tasks through the old and new prompt, compare against the criteria, keep the winner.

4. Version, changelog, and when to re-test

Prompts you rely on deserve the boring disciplines: a version number, a one-line changelog entry per change, and no silent edits. It is the same habit as agent versioning, extended to everything load-bearing, profiles, templates and agents alike.

Re-test on three triggers: the model behind your platform updates, you move a prompt to a new platform or model, or outputs start feeling off. Ten minutes through the test set answers what speculation cannot: did MY tasks change? Version, changelog, test set, the difference between having prompts and having a prompt system.

Imprese

Business AnalystChief of StaffExecutive AssistantM&A AnalystManagement ConsultantOperations AnalystProject ManagerRecruiter

Finanza

AccountantDue Diligence AnalystEquity Research AnalystFamily Office AnalystFinancial AnalystFixed Income AnalystInvestment Banking AnalystPortfolio Analyst

Legale

Contract Review AssistantLegal Due Diligence AssistantLegal Research AssistantParalegal

Marketing

Brand StrategistContent StrategistGEO AnalystMarketing StrategistSEO AnalystSales Strategist

Personale

Career CoachLearning TutorReflection AssistantResearch AssistantTravel PlannerWriting Assistant

Immobiliare

Acquisition AnalystAsset Management AnalystCommercial Real Estate AnalystDevelopment AnalystLease AnalystProperty Financial Analyst

Ricerca

Competitive Intelligence AnalystDeep Research AnalystIndustry Research AnalystJournalist ResearcherMarket Research AnalystMedical Research Assistant

Tecnologia

AI Strategy AdvisorCybersecurity Research AssistantData AnalystProduct ManagerSoftware Engineer