Agentic Workflow: Definition and How It Works
An agentic workflow turns a goal into a controlled loop of planning, tool use, observation, and decisions. Learn how it works, which pattern to choose, and how to build one safely.
How to Run Browser Automation Actors as Real-Time APIs
Turn browser automation into an authenticated API with Playwright workers, Actor runs, or a warm Standby service. Choose a run model, define the contract, and handle security and failures.
MCP Server Tools and API Specification: Define, List, and Call Tools
Learn how MCP servers define tools, expose them through tools/list, and handle tools/call results, errors, pagination, and updates.
Why Browser Agents Fail in Production and How to Fix Them
Browser agents fail in production because of timing, locators, state, browser drift, and human verification. Learn a repair process that makes flows reliable.
Generating Video, PDFs, and Images with the Antigravity MCP Server
Learn what Antigravity MCP and SDK actually support for image generation, PDF analysis, video input, configuration, permissions, and screenshot workflows.
Session Isolation for AI Agents and Web Scrapers
Learn how to isolate browser state, agent memory and credentials across AI tasks and web scrapers without assuming a browser context is a full sandbox.
How AI Agents Browse the Web
AI agents browse through an iterative loop of planning, search, page inspection, and verification. Learn when to use APIs, browsers, or both.
How to Integrate Google Search into Your AI Apps
Choose the right Google Search integration for your AI app: legacy JSON, embedded PSE, Agent Search, or Gemini grounding.
How to Reduce False Positives in Production AI Agents
Reduce false positives in production AI agents with labeled traces, calibrated thresholds, deterministic controls, human approvals, and drift monitoring.
How to Build AI Agents with a Browser Automation SDK
Build a browser agent by pairing an LLM’s reasoning loop with a scoped browser tool. Compare Playwright, Stagehand, Browserbase, and computer-use execution.
How AI Design Agents Turn Descriptions into Templates
Learn how AI design agents turn written briefs into editable templates, what differs across Figma, Canva, and Framer, and how to refine the result.
Designing Error Messages That AI Agents Can Use
Design error contracts that help AI agents diagnose failures, choose safe recovery steps, and give people a truthful explanation.
Build AI Agent Workflows with WebMCP: Live Web Access for Agents
Learn how WebMCP exposes typed website tools to AI agents, with implementation patterns, security controls, managed browsers, and practical code.
Logging Browser Automation Actions for AI Agents
Use Playwright traces, screenshots, DOM snapshots, and OpenTelemetry to reconstruct every browser-agent action and diagnose failures safely.
Why You Should Never Rely on Just One AI Model
Use multiple AI models to expose disagreement, then verify important claims against primary sources. Here is a practical workflow for reliable answers.
How to Contain Prompt Injection in AI Browsers
Learn how hostile web content can steer browser agents—and how to limit risk with least privilege, action gates, independent checks, and human oversight.
Summarizing and Analyzing Reddit Posts with AI Agents
Build a traceable Reddit summarizer with authorized access, claim-level citations, deletion handling, and quality checks.
Using Browser Plugins with AI Agents
Learn how browser extensions connect AI agents to pages and logged-in sessions, how permissions and prompt injection work, and how to test safely.