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cost optimization

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AI Tools/2026-06-14Intermediate

Routing thinking_level by Task in Gemini 3.5 Flash — Re-measuring My Token Spend

After Gemini 3.5 Flash became Antigravity's default, my thinking tokens crept up quietly. Here's how I measured thinking_level per task type and landed on a setup that cuts spend without losing accuracy.

Agents/2026-05-20Advanced

Prompt Caching and Context Strategy for Antigravity Agents — Cutting 60-80% Off Monthly API Costs in Long-Running Production

The longer you keep agents running, the more the monthly invoice quietly piles up. Running Antigravity agents alongside an AdMob-monetized indie app business (50M cumulative downloads), I managed to cut API costs by 60-80% by rebuilding prompt caching and context strategy. This article shares the three-layer cache, context compression, and TTL design I now run in production — with the code and numbers behind them.

AI Tools/2026-05-06Intermediate

3 Weeks with Gemini 2.5 Flash as My Default in Antigravity — Speed, Accuracy, and Cost in Practice

What actually changes when you switch from Gemini 2.5 Pro to Flash as your default model in Antigravity? Three weeks of real usage data, including where Flash falls short and when Pro still earns its place.

Agents/2026-04-27Advanced

Designing a Context Compression Sub-Agent in AgentKit 2.0 — A Production Pipeline That Stops Long-Running Tasks From Drowning in Their Own History

When you run an AgentKit 2.0 agent for hours inside Antigravity, response time and accuracy degrade together as the conversation history balloons. This premium guide walks through a production-grade dynamic compression sub-agent — schema, prompt, integration hooks, and an A/B evaluation harness — so you can decide rollout based on numbers, not gut feel.

Antigravity/2026-04-22Advanced

Cutting Antigravity Agent Costs in Half Without Sacrificing Quality — A Practical Optimization Playbook

Running Antigravity agents full-time can drive your API bill up fast in the first month. Across four sub-agents in my own production setup, I cut monthly token consumption almost in half while keeping quality identical. Here is the before/after breakdown, the model-routing break-even, and the mistakes I made along the way.