Model Comparison
Best Open-Weight LLMs for AI Agents in 2026 (Compared)
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.
ReadSandBase Blog — Page 28
Insights on AI agents, model routing, and building production-ready AI systems.
Page 28
Model Introduction
Qwen 3.6 for Agents: Alibaba's Efficient Open Model
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.
Read
Agent Use Cases
Guardrails for Production AI Agents: A Practical Guide
Real guardrails for AI agents in production: input validation, action allow-lists, sandboxing, cost ceilings, and human-in-the-loop. Patterns you can ship.
Read
Agent Daily News
5 Agent Design Patterns for Robust, Cheap AI Systems
Five agent design patterns for reliable, low-cost AI systems: ReAct, Plan-and-Execute, Reflection, Router, and Tool-First, with trade-offs for each.
Read
Agent Daily News
AI Agent Observability: Logging, Tracing & Debugging Guide
AI agent observability guide: instrument structured logs, distributed traces, tool spans, token cost, and replay data to debug production agents.
Read
Model Comparison
AutoGen vs CrewAI: Multi-Agent Showdown (2026)
AutoGen vs CrewAI tested on real multi-agent tasks. AutoGen wins on flexibility; CrewAI wins on speed-to-ship. Full architecture and cost comparison inside.
Read
Agent Daily News
Why Autonomous AI Agents Need Secure Sandboxes
Autonomous AI agents that run code and shell commands need isolation. Why sandboxes are non-negotiable in production, the isolation levels, and how to choose.
Read
Best Of
Best AI Sandboxes for Agent Development in 2026
A comparison of AI sandboxes for agent development in 2026: E2B, Modal, Daytona, and self-hosted options. Cold-start latency, isolation, and pricing.
Read
Agent Use Cases
Building a Self-Correcting AI Agent with Reflection
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.
Read