Agents & Manager Articles
Multi-agent development with Antigravity — Manager Surface leadership, orchestration patterns, loop prevention, and monitoring unattended runs.
Production Multi-Agent Systems with Antigravity AgentKit 2.0: Patterns, Failure Modes, and What the Demos Don't Show
AgentKit 2.0 makes multi-agent systems look effortless in demos, but running them in production is a different problem. This guide covers Planning vs. Fast mode, three real orchestration patterns, and the failure modes — infinite loops, cost blowouts, prompt injection — that bite on day one.
Designing Antigravity Browser Agents That Don't Go Flaky — Taming DOM Drift and Timing
A browser-agent task that passed yesterday trips today, then succeeds on retry, then fails again. Here's how I've been breaking down the causes of flaky Antigravity browser agents in production and addressing them at the design level.
Build a CSV Analysis Agent in Antigravity with pandas and Matplotlib
Walk through building an Antigravity agent that analyzes CSV files from natural-language instructions. Covers the pandas tool design, common pitfalls, and safety practices for production use.
Prompt Injection Defense in Antigravity — A Production Security Playbook for LLM Apps
Build a four-layer prompt injection defense inside Antigravity with working Python. Includes measured heuristic recall across eight obfuscations and the normalization bug that breaks detection for non-Latin scripts.
Diagnosing and Stopping Runaway Agent Loops in Antigravity
Build agents with Antigravity and you will eventually meet the 'same tool called twenty times in a row' problem. Here is how to classify the failure mode and stop it at the implementation level.
Antigravity Walkthrough Won't Load? A Field Guide to Fixing Empty or Frozen Panels
Your Walkthrough panel is blank, stuck on loading, or showing old data. Here's how to diagnose the real cause — cache, sync, or network — and get it working again.
Harness Engineering for Antigravity
How to get an agent past answering single questions and actually finish a project: a six-step harness, where to place it as a Skill, how to write role switches, and a script that checks the finish line mechanically, with real output.
Building a Business Automation Agent with Antigravity × Google Workspace API — Gmail, Drive, Sheets and Docs in Production
Learn how to build AI agents that automate Gmail responses, generate documents from Drive templates, and create intelligent Sheets reports using Antigravity, Google Workspace APIs, and Gemini.
Antigravity Background Agent in Production — Task Specs, git worktree Parallelism, and the Interactions API
From the sandbox VM to task specifications, AGENTS.md, git worktree parallelism, CI/CD wiring through the Interactions API, and realistic cost estimates — including the mistakes that shaped each one.
Antigravity AI Agent Design: Multimodal Production Implementation Patterns
A complete guide to building multimodal AI agents with Google Antigravity (Gemma 4). Covers image+text integration, Function Calling, async batch processing, state management, error handling, and cost estimation — with production-ready code.
AI Agent Memory Design: 4 Patterns for Context That Persists Beyond a Single Conversation
A practical breakdown of four memory architectures for AI agents — from in-session compression to episodic storage — with implementation code and the gotchas that only show up in production.
Antigravity × Python Structured Output Mastery: Building Type-Safe AI Data Pipelines with Pydantic and Google Gen AI SDK
A complete guide to designing and implementing type-safe AI data extraction pipelines using Google Gen AI SDK Structured Output and Pydantic in Antigravity. Covers schema design, error recovery, async processing, and cost optimization.
Multi-Agent Design Patterns in Antigravity — Building Workflows That Don't Break
Practical patterns for designing multi-agent workflows in Antigravity. Covers orchestrator architecture, state management, error recovery, and debugging techniques for building resilient systems.
Building an AI Test Pipeline with Antigravity Agents: Automating Quality Assurance in Production
Learn how to build a production-grade automated test pipeline using Antigravity's AI agents — from unit test generation to E2E testing with Playwright, complete with validation layers and CI/CD integration.
Build an AI Agent SaaS with Antigravity × AgentKit 2.0 × Stripe — A Complete Implementation Guide for Solo Developers
How to build a subscription AI agent SaaS with AgentKit 2.0, Stripe and Antigravity. Architecture, billing, Webhook idempotency, production deployment — plus the Redis concurrency-slot bug that quietly locks out your heaviest users.
How Claude Mythos Is Redefining AI Agent Limits—and What Project Glasswing Reveals
Explore Anthropic's Claude Mythos and Project Glasswing: AI agents that autonomously discover zero-day vulnerabilities with 93.9% accuracy on SWE-Bench. Why it's invite-only and what it means for developers.
Antigravity × AgentKit 2.0 × Gemma 4: Cut API Costs by 80% with a Local Multi-Agent System in Production
A complete implementation guide to combining AgentKit 2.0 with locally-run Gemma 4, cutting cloud API costs by 80% while maintaining production-grade quality. Covers hybrid LLM routing, fault tolerance, and cost monitoring.
Building a Coding Agent System with Gemma 4 × Antigravity — A Complete Implementation Guide for Code Review, Test Generation, and Refactoring
A hands-on guide to building a 3-agent collaborative system using Gemma 4 and Antigravity AgentKit 2.0, covering code review, automated test generation, and refactoring suggestions. Covers code, Cloudflare Workers deployment, one month of production numbers, and five pitfalls.
Unit Testing AgentKit 2.0 Agents with Vitest — A Practical Guide
Learn how to unit test and integration test MCP skill servers built with AgentKit 2.0 using Vitest. Covers mock strategies, InMemoryTransport integration tests, and CI/CD setup with real working code examples.
Resilient AI Agents in Antigravity — Retry, Circuit Breakers, and Fallback Strategies for Production
Build fault-tolerant AI agents in Antigravity with retry strategies, circuit breakers, model fallback chains, and checkpoint recovery — plus a measured look at why exponential backoff alone leaves retry storms completely intact at 200-agent scale.
AI Agent Error Recovery Design: Building Pipelines That Don't Stop
Covers the typical failure patterns AI agents encounter in production and practical implementations of retry, fallback, and circuit breaker patterns to keep pipelines running.
AI Agent Design Patterns in Practice: From Implementation to Production
Master the four major AI agent design patterns used in production environments. Learn the strengths, weaknesses, and implementation strategies for each pattern with real-world enterprise insights.
AI Agent Orchestration: Designing and Implementing Multi-Agent Systems
One failing agent can erase the work of the ones that succeeded. Four orchestration patterns, plus the boundaries that break in production, with runnable fixes.
Antigravity × Gemma 4 Multi-Agent Workflow: Building Local LLM-Powered AI Systems
Learn how to combine Antigravity IDE with Gemma 4 to build multi-agent systems that run entirely on your local machine. From setup to a practical CI/CD pipeline, this guide has you covered.
Accelerating AI Agent Development with Gemma 4
A practical guide to building AI agents with Google's Gemma 4. Covers model size selection, function calling, structured JSON output, multimodal agents, and parallel tool execution with working code.
Antigravity Multi-Agent Design: 7 Common Pitfalls and How to Fix Them
Deep dive into 7 critical multi-agent design pitfalls: context sharing failures, loop detection misconfiguration, timeout issues, race conditions, credit inefficiency, error propagation, and async debugging. Includes observability patterns and production-ready templates.
Antigravity Multi-Agent Orchestration Guide: From Communication Errors to Production
Complete guide to designing and implementing multi-agent systems with Antigravity. Covers architecture patterns, communication error troubleshooting, and production stability.
Building Multi-Agent Collaboration Systems in Antigravity: From Design to Production
A comprehensive guide to designing and implementing multi-agent collaboration systems in Antigravity. Covers architecture patterns, agent communication, error recovery, state management, and production monitoring.
AgentKit 2.0 Multi-Agent Collaboration Failures: Complete Recovery Guide
Diagnose and recover from AgentKit 2.0 multi-agent failures—deadlocks, orchestrator loops, silent sub-agent failures, and context contamination. Includes production-ready code for fault-tolerant agent system design.
Antigravity Agent Not Following Instructions: How to Fix Task Misunderstandings
When your Antigravity agent misunderstands instructions or drifts off-task, the fix is usually in how instructions are structured—not in the code. Learn agents.md design, task granularity, and context management to keep your agent on track.
Building a Multi-Agent System in Antigravity
One agent trying to do everything hits a ceiling. Designing and implementing multi-agent systems on Antigravity's Manager Surface: role delegation, three architectural patterns, and pairing with Gemma 4.
Antigravity × Gemma 4: Building Production AI Agents with Local LLMs
A complete guide to running Gemma 4 in Antigravity and building production-grade AI agents. Covers model selection, Ollama setup, AgentKit 2.0 integration, and multi-agent scaling.
Antigravity AgentKit 2.0 Runtime Errors: Complete Troubleshooting Guide — tool_call Failures, Infinite Loops, and Context Overflow
A comprehensive guide to diagnosing and fixing AgentKit 2.0 runtime errors in production: tool_call failures, infinite loop detection, context window overflow, parallel agent sync errors, and graceful degradation patterns — all with working code.
Antigravity Agent Output Validation Errors: A Practical Fix Guide
Fix Antigravity agent output validation errors systematically: format failures, quality issues, and consistency problems across multi-agent runs — with prompt design, auto-repair patterns, self-checking, and consensus aggregation.
Antigravity Multi-Agent Systems for Solo Founders: Automating 5 Business Functions
A practical blueprint for solo founders using Antigravity's multi-agent capabilities to automate content creation, customer support, analytics, social media, and development. Real system designs from operators who've doubled revenue while cutting work hours.
Production-Ready AI Agent Design: Orchestration Patterns and Reliability
A comprehensive guide to running AI agents reliably in production. Covers orchestration design, error handling, human-in-the-loop patterns, and state management — everything you need to build agents that hold up in real-world conditions.
Antigravity × LangGraph: Complete Masterguide for Stateful AI Agent Development
A comprehensive guide to building stateful AI agents by combining LangGraph with Antigravity. Covers graph-based workflow design, state management, checkpointing, and human-in-the-loop patterns for production-ready systems.
Orchestrating a Team of Specialist Agents Solo: Practical Multi-Agent Design in Antigravity
Master multi-agent development in Antigravity. Deep dive into Manager Surface architecture, specialist agent design, AGENTS.md configuration, common patterns, and production deployment strategies for enterprise-grade systems.
Claude Opus 4.6 + Gemini 3.1 Pro × Antigravity: Multi-AI Production Masterclass
Learn how to build production-grade AI applications in Antigravity using both Claude Opus 4.6 and Gemini 3.1 Pro. This masterclass covers task-based model routing, cost optimization, fallback chain design, and monitoring for real-world deployments.
Building Next-Generation AI Agents on Antigravity with AgentKit 2.0
A comprehensive guide to building AI agents with AgentKit 2.0 in Antigravity. Covers the 16 specialized agents, the Orchestrator, Planning vs Fast mode, and practical implementation patterns.