n8n Explained: AI Workflow Automation for Agent Builders
What n8n is, how its 70+ AI nodes enable agent workflows, and when to choose it over Dify or code-first approaches for building AI automation in 2026.
SandBase Notes
SandBase Blog
Insights on AI agents, model routing, and building production-ready AI systems.
SGLang Explained: The Low-Latency Inference Engine for Agents
How SGLang works, why RadixAttention gives agents faster prefix reuse, and when to choose it over vLLM for production inference in 2026.
vLLM Explained: The Inference Engine Behind Agent Stacks
How vLLM works under the hood, why PagedAttention matters for agent workloads, and where it fits in a production agent infrastructure stack in 2026.
Warp Explained: The Agentic Development Environment
What Warp 2.0 is, how it evolved from AI terminal to agentic development environment, and why it matters for developers working with coding agents in 2026.
Claude Opus 4.7 for Agents: Why It's the Coding King in 2026
Claude Opus 4.7 for AI agents in 2026: SWE-bench numbers, where it wins on coding tasks, what it costs, and when to reach for a cheaper model.
DeepSeek V4: 1M Context Open-Source LLM for Agents (2026)
DeepSeek V4 ships a 1M-token context window under MIT at a fraction of frontier pricing. When the huge context earns its keep for agents, and when it's a trap.
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.
GLM-5.1: The Open-Weight Model That Tops SWE-bench Pro
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.
Kimi K2.6 for Agents: Trillion-Param Open Weights, Tested
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.