Articoli correlati a Rebuilding the SDLC for Probabilistic AI: A Practical...
Rebuilding the SDLC for Probabilistic AI: A Practical Guide to AI-Native Software Engineering, LLM Evaluation, and Production Guardrails - Brossura
Sinossi
For sixty years, software engineering ran on one assumption: same input, same output, every time. Large language models broke that promise, and most teams are still pretending they didn't.
Rebuilding the SDLC for Probabilistic AI is a practical guide for senior engineers, architects, and team leads who need to build reliable software on top of fundamentally unreliable components. Author Sujal Choudhari, who moved from ultra low latency C++ trading systems into AI engineering, walks through why manual vibe checks and eyeballing outputs do not scale, and what to build instead.
Inside, you will learn how to:
- Design architectural guardrails that enforce structure at the token level
- Build context aware data pipelines that ground model outputs in fact
- Replace exact match assertions with statistical evaluation pipelines using bootstrap resampling
- Scale QA using LLM as a judge techniques, and calibrate those judges properly
- Monitor for silent semantic drift in production before your users notice
- Structure engineering teams for AI native development
This is not management fluff or AI hype. It is a concrete, opinionated engineering framework for anyone tasked with shipping AI powered systems that actually hold up in production.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Rebuilding the SDLC for Probabilistic AI: A Practical...
Foto dell'editore
Rebuilding the SDLC for Probabilistic AI: A Practical Guide to AI-Native Software Engineering, LLM Evaluation, and Production Guardrails (Coding Mastery)
Print on DemandDa: California Books, Miami, FL, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. Print on Demand. Codice articolo I-9798185250440
Compra nuovo
EUR 13,39
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Rebuilding the SDLC for Probabilistic AI (Paperback)
Print on DemandDa: Grand Eagle Retail, Bensenville, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. For sixty years, software engineering ran on one assumption: same input, same output, every time. Large language models broke that promise, and most teams are still pretending they didn't.Rebuilding the SDLC for Probabilistic AI is a practical guide for senior engineers, architects, and team leads who need to build reliable software on top of fundamentally unreliable components. Author Sujal Choudhari, who moved from ultra low latency C++ trading systems into AI engineering, walks through why manual vibe checks and eyeballing outputs do not scale, and what to build instead.Inside, you will learn how to: Design architectural guardrails that enforce structure at the token levelBuild context aware data pipelines that ground model outputs in factReplace exact match assertions with statistical evaluation pipelines using bootstrap resamplingScale QA using LLM as a judge techniques, and calibrate those judges properlyMonitor for silent semantic drift in production before your users noticeStructure engineering teams for AI native developmentThis is not management fluff or AI hype. It is a concrete, opinionated engineering framework for anyone tasked with shipping AI powered systems that actually hold up in production. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798185250440
Compra nuovo
EUR 14,26
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: 1 disponibili
Foto dell'editore
Rebuilding the SDLC for Probabilistic AI
Da: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798185250440
Compra nuovo
EUR 14,49
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Rebuilding the SDLC for Probabilistic AI
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798185250440
Compra nuovo
EUR 13,00
Spedizione EUR 3,84
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Rebuilding the SDLC for Probabilistic AI (Paperback)
Print on DemandDa: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. For sixty years, software engineering ran on one assumption: same input, same output, every time. Large language models broke that promise, and most teams are still pretending they didn't.Rebuilding the SDLC for Probabilistic AI is a practical guide for senior engineers, architects, and team leads who need to build reliable software on top of fundamentally unreliable components. Author Sujal Choudhari, who moved from ultra low latency C++ trading systems into AI engineering, walks through why manual vibe checks and eyeballing outputs do not scale, and what to build instead.Inside, you will learn how to: Design architectural guardrails that enforce structure at the token levelBuild context aware data pipelines that ground model outputs in factReplace exact match assertions with statistical evaluation pipelines using bootstrap resamplingScale QA using LLM as a judge techniques, and calibrate those judges properlyMonitor for silent semantic drift in production before your users noticeStructure engineering teams for AI native developmentThis is not management fluff or AI hype. It is a concrete, opinionated engineering framework for anyone tasked with shipping AI powered systems that actually hold up in production. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798185250440
Compra nuovo
EUR 16,83
Spedizione EUR 43,20
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili