ClawPaneBlog
Insights & Guides
Practical guides on model routing, cost optimization, and building better AI agent workflows with ClawPane and OpenClaw.
OpenClaw vs Perplexity Computer: Which AI Agent Setup Wins in March 2026?
Comparing OpenClaw vs Perplexity Computer for AI agent workflows. See why OpenClaw with smart model routing is the best Perplexity Computer alternative for self-hosted AI agents.
Read article →Best OpenClaw Skills to Install in 2026
A curated list of the best OpenClaw skills by category — developers, productivity, research, browser automation, and more. Includes direct links to each skill's SKILL.md on GitHub.
Read article →LLM Routing: What It Is and Why Your AI Stack Needs It
LLM routing automatically sends each AI request to the best model for the job. Learn how it works, why static model selection is costing you money, and how to implement it.
Read article →OpenClaw Workspace Files: AGENTS.md, SOUL.md, MEMORY.md and More
A complete guide to OpenClaw's workspace bootstrap files — AGENTS.md, SOUL.md, IDENTITY.md, USER.md, MEMORY.md, HEARTBEAT.md, and TOOLS.md. What each file does, what to put in it, and links to community examples on GitHub.
Read article →AI Cost Optimization: A Practical Guide for Engineering Teams
AI API costs can spiral fast. This guide covers the most effective strategies for reducing LLM spend — from model routing to prompt engineering to caching.
Read article →Model Routing: How to Automatically Pick the Best LLM for Every Request
Model routing dynamically selects the optimal LLM per request based on cost, speed, and quality. Learn how it works and how to implement it in your AI stack.
Read article →LLM Costs in 2026: What You're Actually Paying Per Request
A breakdown of LLM pricing across OpenAI, Anthropic, Google, Mistral, and others. See what each model costs per request and where your budget is going.
Read article →Getting Started with ClawPane: Smart Model Routing for OpenClaw
Learn how to set up ClawPane as a model provider in OpenClaw and start routing every agent request to the optimal model in under 5 minutes.
Read article →AI Gateway vs. Model Router: Which One Do You Need?
AI gateways and model routers solve different problems. Learn the difference, when you need each, and how they work together in production AI stacks.
Read article →Model Selection for AI Agents: Manual vs. Automated Approaches
Choosing the right LLM for each AI agent request is a growing challenge. Compare manual model selection with automated approaches and find the right strategy for your team.
Read article →LLM Proxy: How to Centralize and Optimize Your AI API Calls
An LLM proxy centralizes your AI API calls through a single endpoint. Learn how proxies work, what they optimize, and how to add intelligent routing on top.
Read article →AI Spending: Where Your Budget Actually Goes (and How to Fix It)
Most teams don't know where their AI budget goes. Break down your LLM spending by category, identify waste, and learn the fastest ways to cut costs without losing quality.
Read article →Why Smart Model Routing Matters for AI Agents
Static model assignments waste money and leave performance on the table. Learn why dynamic model routing is the next step for production AI agent workloads.
Read article →Model Fallback: How to Keep AI Agents Running When Providers Go Down
Provider outages are inevitable. Learn how to implement model fallback chains that keep your AI agents operational when individual LLM providers fail.
Read article →LLM Comparison 2026: Cost, Speed, and Quality Across Major Providers
Compare the leading LLMs of 2026 across cost, latency, and quality benchmarks. See which models win for different workloads and how to pick the right one.
Read article →How to Reduce LLM API Costs by 30–45% Without Sacrificing Quality
Concrete strategies to cut your LLM API bill by 30–45% while maintaining output quality. Includes model routing, prompt optimization, and caching techniques with real numbers.
Read article →Best LLM Router for Production: What to Look For in 2026
Evaluating LLM routers for production use? Here's what matters: multi-dimensional scoring, fallback chains, per-workload config, latency overhead, and provider coverage.
Read article →Per-Router Weight Tuning: Optimize Every Workload
Learn how to create multiple ClawPane routers with different optimization weights to match each agent workload — cost-first for support, quality-first for code, speed-first for triage.
Read article →How to Set Up a Custom Model Provider in OpenClaw
Step-by-step guide to adding a custom model provider in OpenClaw. Configure ClawPane as a provider to get smart model routing for all your agents in under 5 minutes.
Read article →Automatic Model Selection for AI Agents: A Step-by-Step Guide
Stop hardcoding model names in your AI agents. This guide shows you how to implement automatic model selection that picks the best LLM for each request based on your priorities.
Read article →The Cheapest Way to Run AI Agents at Scale
Running AI agents at scale doesn't have to break the bank. Learn the most cost-effective strategies for production agent workloads — from model routing to prompt engineering to batching.
Read article →LLM Cost Per Token Comparison: GPT-5 vs. Claude vs. Gemini vs. More
Side-by-side cost per token comparison for every major LLM in 2026. Includes input and output pricing, effective cost per request, and recommendations by use case.
Read article →How to Automatically Route AI Requests to the Cheapest Model
A practical guide to setting up automatic cost-optimized routing that sends each AI request to the cheapest model capable of handling it. Includes setup steps and expected savings.
Read article →How to Reduce OpenAI API Costs with Smart Model Routing
Spending too much on OpenAI? Smart model routing can cut your GPT-5 bill by 30–45% by automatically routing simple requests to cheaper models. Here's how.
Read article →Building Multi-Model Fallback Chains for Reliable AI Agents
Single-provider AI agents are fragile. Learn how to build multi-model fallback chains that keep agents running through outages, rate limits, and degraded performance.
Read article →AI Agent Cost Optimization: The Complete Guide for 2026
The definitive guide to reducing AI agent costs in production. Covers model routing, prompt engineering, caching, batching, architecture optimization, and monitoring with concrete ROI numbers.
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