Gemini 3.5 Flash for Agents: Fast, Cheap, and When It Wins
Google's Gemini 3.5 Flash trades a little reasoning depth for big wins in speed and cost. Where a fast model is right for agents, and where it hurts.
SandBase Notes
Insights on AI agents, model routing, and building production-ready AI systems.
Google's Gemini 3.5 Flash trades a little reasoning depth for big wins in speed and cost. Where a fast model is right for agents, and where it hurts.
Zhipu's GLM-5.1 took the top SWE-bench Pro spot among open-weight models in 2026. What the benchmark measures, where it fits, and how to use it.
Moonshot's Kimi K2.6 is a 1T-parameter open-weight MoE model for agents. What it's good at, where the params help, and how to wire it into a loop.
A head-to-head guide to open-weight LLMs for agents in 2026: Kimi K2.6, DeepSeek V4, GLM-5.1, Qwen 3.6. Which to pick for tool-use, context, or cost.
Real guardrails for AI agents in production: input validation, action allow-lists, sandboxing, cost ceilings, and human-in-the-loop. Patterns you can ship.
Qwen 3.6 is Alibaba's open-source LLM that punches above its size on SWE-bench. Why a smaller, efficient model is often the smarter agent default.
A comparison of AI sandboxes for agent development in 2026: E2B, Modal, Daytona, and self-hosted options. Cold-start latency, isolation, and pricing.
A head-to-head comparison of AutoGen and CrewAI for multi-agent systems in 2026: architecture, developer experience, cost, and when to pick each.
How to build a self-correcting AI agent using the reflection pattern and persistent memory. A runnable Python loop that critiques and fixes its own output.