When Antigravity Ignores Your Pasted Screenshots: A Six-Point Diagnostic Guide
Pasted a screenshot into Antigravity and got a text-only reply that ignored the image? Walk through six concrete checks — multimodal model selection, format pitfalls, paste-path differences, and OS-specific quirks — plus a fast sanity-check prompt to confirm whether the AI actually sees your image.
Implementing Antigravity's A2A Protocol — Practical Patterns for Agent-to-Agent Conversation
A hands-on guide to Antigravity's A2A (Agent-to-Agent) protocol. Walks through the minimal two-agent setup and three real-world patterns — fire-and-forget, bidirectional confirmation, and scatter-gather — with runnable samples.
LM Studio Not Visible to Antigravity — Diagnosing Port, CORS, and Model-Load Layers
When Antigravity can't see LM Studio's models, the fix is rarely one setting. Walk through the three layers — server port, CORS, and model visibility — and recover cleanly, with the exact commands to verify each step.
Antigravity × Gemini File API: A Production Guide to Feeding Long-Form Media (Video, Audio, PDF) into Your Agents
Feed hour-long videos, podcasts, and book-length PDFs into your Antigravity agents with the Gemini File API. A practical, production-oriented pipeline with timestamped highlight extraction, idempotent uploads, cost accounting, and failure recovery.
Fixing Mid-Stream Cutoffs and Long-Run Freezes When Antigravity Talks to Ollama
When Antigravity connects to Ollama just fine but responses keep dying mid-stream or long refactors hang forever, the fix usually isn't at the connection layer. A focused triage guide for cutoff-class symptoms, with measured numbers, a durable hardening recipe, and a verification loop.
Fixing IME Input Issues in Antigravity: Dropped Composition, Premature Commits, and Keybinding Clashes
If you type Japanese, Chinese, or Korean inside Antigravity, AI inline completion and keybindings sometimes eat your IME composition before you can commit it. Here is a pattern-by-pattern fix covering macOS, Windows, and Linux.
Antigravity × Local LLM (Ollama / LM Studio / LM Link): A Production Connection Playbook
Getting Antigravity to connect to Ollama, LM Studio, or LM Link is the easy part. Running on that setup for eight hours a day, week after week, surfaces disconnects, model-swap hangs, stale sessions after lunch, and VRAM pressure from other processes. This playbook covers hardening the connection layer, picking the right backend for the task, and designing the fallback path for when local goes silent.
Antigravity Retry Stuck in a Loop? A Triage Guide That Actually Breaks It
Pressing retry in Antigravity feels like it should eventually work, but sometimes the same failure keeps coming back with only tiny variations. This guide names the three modes the retry loop falls into, walks through a triage flow, and gives you a rule of thumb for when to stop retrying and start intervening.
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.
Semantic Caching for LLM Responses in Antigravity — Estimating Your Own Savings Before You Build It
Building a semantic LLM response cache with Antigravity, pgvector, and Gemini. Covers migrating off the retired text-embedding-004, normalizing truncated vectors, and a formula that turns hit rate and unit-cost ratio into an actual savings estimate.
Using Antigravity's Retry Feature Wisely — A Smarter Way to Resume Failed Agent Runs
Antigravity's Retry button is not a reroll. This guide explains when retry actually helps, how to prepare context before retrying, and when you should stop retrying and start a fresh session.
Observing Antigravity AI Agents with Langfuse — A Practical Setup Before You Ship
Before you push an Antigravity AI agent to production, wire up Langfuse so you can actually see traces, token spend, and cost. A hands-on guide with real Python code and lessons from the field.