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{ "item_title" : "TypeScript for AI-Era Full-Stack Development", "item_author" : [" Freddie B. Carson "], "item_description" : "Picture this: It's 2:00 AM on a Tuesday. Your newly launched AI agent just went viral. But suddenly, your error-tracking dashboard explodes.The provider's latest unannounced model update changed its output format, breaking your database parsers. Un-sanitized user prompts are triggering costly infinite tool-calling loops, and your cloud bill is spiking through the roof. Worst of all? You have no automated tests to tell you what went wrong.Sound like a nightmare? It happens every day to engineering teams relying on fragile wrapper libraries and demo-grade tutorials.Building for production isn't just about sending an API request-it's about controlling chaos. I spent years architecting high-scale TypeScript systems, and I wrote this book to give you the exact operational frameworks, mathematical metrics, and production-tested code you need to sleep soundly while your AI infrastructure handles live traffic.What's insideCustom LLM Client Architecture: Build resilient streaming gateways, SSE chunk decoders, and token rate-limiters from scratch.Type-Safe Prompt Versioning: Decouple prompts from application logic with Zod validation, SHA-256 lockfiles, and dynamic registries.Enterprise RAG & Vector Search: Master embedding similarity math, multi-tenant vector isolation, and hybrid retrieval.Multi-Agent Orchestration: Design stateful, autonomous agent loops with deterministic tool-calling and sandboxed execution environments.Automated Vitest Evaluations: Implement LLM-as-a-Judge rubrics, cosine distance assertions, and continuous quality gates in CI/CD.Maintenance & Context Drift: Monitor Population Stability Index ($PSI$) vector shift, catch provider deprecations, and prevent schema drift.Production Boilerplates & Security: Plug-and-play pnpm/Turborepo layouts, OWASP LLM security hardening, and KMS key rotation pipelines.Who it's meant forTypeScript & Node.js Developers who want to master AI engineering without relying on heavy Python frameworks.Software Architects & Engineering Leads responsible for building reliable, enterprise-ready AI backends.Full-Stack Engineers looking to elevate hackathon prototypes into resilient products with strict SLAs and cost controls.Stop building fragile demos that break in production. It's time to start engineering enterprise-grade AI systems that scale. Scroll up, click Buy Now, and master the TypeScript AI stack today!", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/817/656/9798176562880_b.jpg", "price_data" : { "retail_price" : "29.99", "online_price" : "29.99", "our_price" : "29.99", "club_price" : "29.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
TypeScript for AI-Era Full-Stack Development|Freddie B. Carson

TypeScript for AI-Era Full-Stack Development : Building Intelligent, Scalable, and Production-Ready Web Applications

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Overview

Picture this: It's 2:00 AM on a Tuesday. Your newly launched AI agent just went viral. But suddenly, your error-tracking dashboard explodes.

The provider's latest unannounced model update changed its output format, breaking your database parsers. Un-sanitized user prompts are triggering costly infinite tool-calling loops, and your cloud bill is spiking through the roof. Worst of all? You have no automated tests to tell you what went wrong.

Sound like a nightmare? It happens every day to engineering teams relying on fragile wrapper libraries and demo-grade tutorials.

Building for production isn't just about sending an API request-it's about controlling chaos. I spent years architecting high-scale TypeScript systems, and I wrote this book to give you the exact operational frameworks, mathematical metrics, and production-tested code you need to sleep soundly while your AI infrastructure handles live traffic.

What's inside

  • Custom LLM Client Architecture: Build resilient streaming gateways, SSE chunk decoders, and token rate-limiters from scratch.
  • Type-Safe Prompt Versioning: Decouple prompts from application logic with Zod validation, SHA-256 lockfiles, and dynamic registries.
  • Enterprise RAG & Vector Search: Master embedding similarity math, multi-tenant vector isolation, and hybrid retrieval.
  • Multi-Agent Orchestration: Design stateful, autonomous agent loops with deterministic tool-calling and sandboxed execution environments.
  • Automated Vitest Evaluations: Implement LLM-as-a-Judge rubrics, cosine distance assertions, and continuous quality gates in CI/CD.
  • Maintenance & Context Drift: Monitor Population Stability Index ($PSI$) vector shift, catch provider deprecations, and prevent schema drift.
  • Production Boilerplates & Security: Plug-and-play pnpm/Turborepo layouts, OWASP LLM security hardening, and KMS key rotation pipelines.

Who it's meant for

  • TypeScript & Node.js Developers who want to master AI engineering without relying on heavy Python frameworks.
  • Software Architects & Engineering Leads responsible for building reliable, enterprise-ready AI backends.
  • Full-Stack Engineers looking to elevate hackathon prototypes into resilient products with strict SLAs and cost controls.

Stop building fragile demos that break in production. It's time to start engineering enterprise-grade AI systems that scale. Scroll up, click "Buy Now," and master the TypeScript AI stack today!

This item is Non-Returnable

Details

  • ISBN-13: 9798176562880
  • ISBN-10: 9798176562880
  • Publisher: Independently Published
  • Publish Date: October 2026
  • Dimensions: 9.61 x 6.69 x 0.74 inches
  • Shipping Weight: 1.26 pounds
  • Page Count: 358

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