Articles tagged “ai-agents”
19 articles
AI Agent Memory: From Session Context to Long-Term Knowledge
Build AI agent memory systems from scratch in TypeScript. Covers memory types (session, episodic, semantic, procedural), architectures (buffer, summary, vector retrieval), RAG intersection, and privacy-first design.
Build Your Own AI Agent Memory System (Then Learn What Breaks at Scale)
Build a complete memory system for customer-facing AI agents — session context, persistent recall, semantic search. Then learn what breaks when real customers start returning.
Build Your Own AI Agent Tool System (Then Learn What Breaks at Scale)
Build a complete tool system for customer-facing AI agents from scratch — registry, execution, auth, monitoring. Then learn what breaks when real customers start calling.
Multi-Agent AI Systems: Build an Agent Orchestrator Without a Framework
Build a multi-agent system from scratch — delegation, planning loops, and inter-agent communication — before reaching for LangGraph or CrewAI.
Voice AI Escaped the Call Center. Here's Where It Landed.
From $50K M&A due diligence to 9 million burger orders, voice AI agents are breaking into verticals nobody predicted. Here's what developers need to know.
Building an AI Agent That Remembers Everything (Without Creeping People Out)
Privacy-first memory design for AI agents: what to store, what to forget, how to give customers control, and how to stay compliant across GDPR, HIPAA, and multi-channel deployments.
Prompt Engineering Is Dead. Long Live Prompt Management.
Why production AI teams need version control, A/B testing, and rollback for prompts — not just clever writing. The craft has changed.
Scenario Testing: The QA Strategy That Catches What Unit Tests Miss
Discover how synthetic test conversations catch edge cases that unit tests miss. Personas, adversarial scenarios, and regression testing for AI agents.
Scorecards vs. Vibes: How to Actually Measure AI Agent Quality
Most teams 'feel' their AI agent is good. Here's how to build structured scoring with rubrics, automated grading, and regression detection that holds up.
Edge AI for Voice Agents: Fix Latency and Privacy at the Source
How edge AI eliminates 50-200ms of latency and entire classes of privacy risks for voice agents — with hybrid architecture patterns and TypeScript examples.
Voice AI Can Read Your Mood — Here's What That Changes
How emotion-aware voice AI detects customer sentiment in real time, adapts responses, and cuts escalations by 25-40% — plus the ethics you can't ignore.
Smarter Escalation: When Should Voice AI Refuse to Answer?
Industry research shows that 60-65% of enterprises struggle with AI escalation decisions, leading to customer frustration and compliance risks. Discover when voice AI should refuse to answer and how to build smarter escalation frameworks.
Agentic AI Liability: Who's Responsible for What When Things Go Wrong?
Industry research shows that 80-85% of enterprises lack clear liability frameworks for agentic AI failures. Discover how to establish responsibility structures that protect your organization while enabling AI innovation.
Prompt engineering vs. context engineering: What's the next step for voice AI?
While prompt engineering focuses on perfecting inputs, context engineering optimizes the entire conversation environment. Discover why context engineering is becoming the key differentiator in voice AI.
Digital Twins for AI Agents: Simulate Before You Ship
Build digital twins that test your AI agent against thousands of synthetic customers. Architecture, TypeScript code, and the patterns that catch failures.
Synthetic Empathy: Can AI Learn to Apologize (and Should It)?
Industry research shows that 55-60% of enterprises are exploring synthetic empathy in AI systems. Discover the ethical implications and practical applications of AI emotional intelligence.
The Voice AI Quality Crisis: Why Most Deployments Fail in Production
Most voice AI deployments fail in production despite passing lab tests. Real data on why the gap exists, what it costs, and how to close it.
Why 75% of AI Chatbots Fail Complex Customer Issues (And How to Fix It)
Industry research reveals 75% of customers believe chatbots struggle with complex issues. Learn why this happens and discover proven testing strategies to dramatically improve your AI agent performance.
The Human Touch: Why 90% of Customers Still Choose People Over AI Agents
Despite AI advances, 90% of customers prefer human agents for service. Discover what customers really want from AI interactions and how to bridge the trust gap through rigorous testing.
Learn Agentic AI
One lesson a week — practical techniques for building, testing, and shipping AI agents. From prompt engineering to production monitoring. Learn by doing.
