4708 related articles

Leaping AI builds voice AI agents for blue-collar services like home improvement and roofing, supporting 100+ concurrent calls, multi-day campaign auto-follow-ups, multilingual switching, and deep CRM integration.

HarnessRouter provides a unified API to access top AI agents worldwide, encapsulating sandbox isolation, task orchestration, fault-tolerant retries, and cost control for production-ready integration.

HarnessRouter provides a unified API to access top AI agents worldwide, encapsulating sandbox isolation, task orchestration, fault-tolerant retries, and cost control for production deployment.

Google Gemini Managed Agents API introduces environment hooks, model selection, free tier support, and default model upgrades—empowering AI Agent developers with stronger execution control and lower barriers to entry.

Explore how AI agents are redefining enterprise work—from applied AI partnerships and multi-agent collaboration to structural workflow redesign and organizational transformation.

API Mock is fast but misses bugs; Sandbox is realistic but costly. This article analyzes their core differences and provides a layered testing strategy for building reliable Agent test systems.

Google's official hands-on: how to go from idea to production fast with AI Studio and build AI Agents using the now-GA Interactions API. The core idea—Agents are just combinations of files.

Official Google hands-on: go from idea to production fast with AI Studio, and build AI Agents with the now-GA Interactions API. The core idea: an Agent is just a composition of files—Markdown plus a few scripts, no complex Python loops needed.

A deep dive into an AI paper writing system built with FastAPI + Vue3, covering multi-agent collaboration, RAG, streaming output, and full academic workflow automation.

A deep comparison of Pipecat Flows and Vapi Squad for voice AI agent architecture — covering latency, accuracy, multi-agent handoffs, and when to use each.
Text-to-CAD: How AI Agents Are Reshapi…
Explore how the open-source text-to-cad project wraps CAD modeling as AI agent skills, letting engineers generate 3D models from natural language descriptions.

Integrating email into LangChain agents: Gmail API's OAuth flow is too complex, while AgentMail offers a lightweight agent-native email API. A practical engineering comparison.

Full breakdown of a real AI testing pipeline: API collection, doc enrichment, AI test case generation, Agent-driven execution, and test reports — with Skills, RAG, and Harness engineering.

AI agents are revolutionizing JS reverse engineering. This deep dive covers built-in tool chains, automation modes, prompt engineering for e-commerce, and full pipeline automation from parameter extraction to database storage.
Designing APIs for AI Agents: A Paradi…
When AI Agents become the primary API callers, traditional interface design assumptions break down. This article explores agent-friendly API design principles and how MCP is driving this paradigm shift.

An orchestration Agent looped for hours, firing thousands of LLM calls and burning weeks of budget. Learn the root causes and practical defenses: circuit breakers, tiered budgets, and iteration limits.

A deep dive into AI-powered testing: Cursor Skills, Coze agents, and LangChain multi-agent systems for automated test case generation, BDD, and review workflows.
Reverse-Engineering Web Apps: A New Ap…
Explore a new approach to AI Agent tool integration: reverse-engineering web apps to turn API-less pages into callable Agent tools, with analysis of MCP synergy and challenges.

Based on Fireship's review, an in-depth look at GPT-5.6 Sol's Ultra Mode multi-agent parallelism, its 91.9% Terminal Bench score, and how it differs from Claude Fable in cost, speed, and precision.

Doubao and Qwen have retired their AI Agent features. The real reason isn't regulation—it's that companion-chat users don't pay, making compute costs unrecoverable. A deep dive into AI's cost dilemma.