Are your AI agents struggling to operate reliably in complex, real-world environments? Do you want to build multi-agent web applications that are secure, scalable, and capable of orchestrating tools and automation seamlessly?
AI Agents in the Modern Web Era provides a complete, practical blueprint for designing, deploying, and maintaining powerful agentic systems. From integrating large language models with retrieval-augmented generation (RAG) to orchestrating multiple agents across workflows, this book equips you with the skills to build professional-grade applications that perform consistently and securely.
Inside, you will learn to:
Design secure tool-driven agents that interact safely with APIs, databases, and web services
Implement browser automation for tasks like web scraping, form filling, and multi-step workflows
Build scalable multi-agent systems using queues, workers, and orchestration frameworks
Monitor and optimize performance, latency, and cost for efficient deployments
Apply robust evaluation, regression, and red-team testing to maintain reliability and trust
Integrate CI/CD, feature flags, and canary releases for smooth production updates
Maintain agents with post-deployment upgrades, monitoring, and continuous improvement
Whether you are a developer, AI practitioner, or product team member, this book provides the practical guidance and actionable frameworks to confidently build and manage agentic web applications at scale.
Take the next step: Master the modern standards of AI agent development and deployment, and transform your ideas into secure, efficient, and scalable applications today.