7 Things I Wish Someone Told Me Before I Almost Gave Up on OpenClaw

OpenClaw is incredible in theory, but getting real value from it takes some know-how. This guide covers the practical lessons that turned it from a frustrating token-burner into something genuinely useful.

Last updated: February 17, 2026

1 Stop running everything through your best model

This is the single biggest mistake people make — and the single biggest reason costs spiral out of control.

By default, OpenClaw sends every single request to whatever model you set as your primary. That includes heartbeats (periodic "are you still alive?" pings that happen every 30 minutes), sub-agents that spin up when your main agent does parallel work, quick lookups like "what's on my calendar?", and complex coding tasks. If your primary model is Claude Opus or GPT-5.2, all of that hits the expensive model — even the simple stuff.

Think of it like this: using Opus for a heartbeat ping is like hiring a lawyer to check your letterbox. It works, but it makes no financial sense.

What to do instead

Set up a tiered model config. Use a cheap, fast model as your primary for everyday tasks, and keep the smart (expensive) model as a fallback for when your agent actually needs it.

Open your OpenClaw config file. This is where all your settings live:

If you prefer a different text editor, you can also use vim or code (VS Code) instead of nano. On Windows with WSL, you can also open it in File Explorer by typing explorer.exe . in your Ubuntu terminal and navigating to the .openclaw folder.

Here's an example config that uses a cheap model as the default, with smarter models as fallbacks:

The alias fields let you switch models quickly during a chat session by typing:

That switches your current session to Opus for a complex task. When you're done, switch back to Haiku with /model Haiku. Your wallet will thank you.

2 Your agent needs rules — a lot of them

Out of the box, OpenClaw is a blank slate. It doesn't know how you want it to behave, so it does unpredictable things: it loops on the same answer, repeats itself, forgets what it was doing, makes weird decisions, and chews through tokens doing nothing useful.

This is normal. The agents you see people showing off online — the ones that build apps overnight and manage email like a real assistant — all have heavily customised instruction sets behind them.

How to add rules

OpenClaw uses skills — these are folders containing a SKILL.md file (a plain text file with instructions) that your agent reads and follows. Think of a skill as a "rulebook" for a specific job.

Skills live in your workspace folder. Here's how to create one:

Inside that file, write clear rules in plain English. Here's an example of rules that solve common frustrations:

You can create as many skill folders as you want, each with its own SKILL.md. For example, you might have separate skills for email handling, coding standards, calendar management, etc.

3 "Work on this overnight" doesn't work the way you think

One of the most common complaints: "I told my agent to work on something while I sleep, and it just... didn't."

Here's why: when you chat with OpenClaw, that conversation lives in a session. When you close the chat or walk away, the session eventually ends. Your agent doesn't "keep working in the background" — it just stops.

If you want your agent to do things on a schedule or work independently, you need cron jobs.

What's a cron job?

A cron job is just a task that runs automatically on a timer. Like an alarm clock for your agent. You can set it to do something every hour, every morning at 6am, every weeknight at midnight — whatever you want.

The key is setting sessionTarget: "isolated" — this tells OpenClaw to spin up a completely fresh, independent agent session for the cron job. It runs on its own and messages you the results when it's done.

Setting up a cron job

The easiest way is to ask your agent to create one for you in a chat session. For example:

Your agent will create the cron configuration for you. You can also do this by directly editing your config file:

The "0 7 * * *" part is a cron schedule — it means "at minute 0 of hour 7, every day." Here are some common patterns:

For one-off deferred tasks

Cron jobs repeat on a schedule. If you want a one-off task (like "build this app tonight"), you need a different approach. The simplest method:

Option A: Ask your agent to create a cron job, let it run once, then delete the cron job.

Option B: Set up a task queue. Create a Notion page, a text file, or a simple database, and have a cron job check it every 30 minutes for new tasks. When the agent finds a task, it works on it. When it's done, it marks the task as complete. Several users have built full overnight pipelines this way — breaking a project into phases, adding them to a task list, and letting the agent work through them one at a time.

4 Start with one thing working end-to-end

It's tempting to set up email + calendar + Telegram + web scraping + cron jobs + file management all at once. Don't. Every integration is a separate failure mode, and when three of them break simultaneously, it's nearly impossible to figure out which one caused the problem.

The sanity path

Step 1: Pick one tiny workflow. Something like: "every morning at 8am, my agent checks the weather and sends me a message."

Step 2: Get it working perfectly. End to end. No shortcuts, no "I'll fix that later."

Step 3: Once it's reliable, add the next thing. Maybe email checking. Get that working.

Step 4: Keep layering, one integration at a time.

Keep explicit logs at every step. When something breaks, you can look at the inputs and outputs to see exactly where it went wrong, instead of guessing.

5 Save what works — you'll need it again

OpenClaw uses compaction to manage its memory. As conversations get long, it summarises older messages to stay within the model's context window. This is necessary — but it means things get lost. Configs that were working, decisions that were made, nuances that matter.

Here's how to fight context loss:

Use state files

State files are persistent files your agent can read and write to. Unlike chat history, they survive compaction. Tell your agent to save important information to state files.

Use workspace docs

Your OpenClaw workspace (at ~/.openclaw/workspace/) has special files your agent reads automatically:

Fill these in. The more context your agent has in these files, the less you have to repeat yourself.

Push context in, not just save it out

State files and workspace docs help your agent remember things from past conversations. But there's another angle most people miss: feeding your agent new context automatically, without having to copy-paste things into chat.

Think about how you actually work. You spend hours reading docs, researching tools, comparing options — and your agent knows none of it. You'd have to manually summarise what you learned and paste it into a message. Most people don't bother, which means the agent is always working with stale or incomplete context.

6 The model matters more than anything else

Most frustration with OpenClaw comes from using a model that can't handle tool calls reliably.

OpenClaw isn't a chatbot — it's an agent. Your model doesn't just need to write nice text. It needs to correctly call tools (browser, file system, shell commands, APIs) using structured function calls. A model can write beautiful prose and still produce malformed tool calls that crash your entire workflow.

OpenClaw also needs models with a large context window — at least 64,000 tokens is recommended. Smaller context windows lead to context overflow errors, which is a common cause of freezing and crashes.

What actually works

Switching models on the fly

You don't have to commit to one model for everything. During a chat session, you can switch models instantly:

Working on something complex? Switch to Opus. Quick lookup? Stay on Haiku. This alone can cut your costs dramatically.

You can also list all your available models from the terminal:

What about local models?

Running a model on your own computer (via Ollama or LM Studio) means zero API costs and full privacy. But there are trade-offs:

You need a decent GPU. For usable results, 16GB+ of VRAM is the minimum. Models like Qwen3 8B will run on less, but quality drops fast. Qwen3 Coder 30B (quantised) is a popular mid-range choice for people with 16–24GB VRAM.

The honest recommendation from most experienced users: use a local model as your primary for simple daily tasks, and keep a cloud model as a fallback for the hard stuff. You get privacy and zero cost for 80% of requests, and quality for the ones that matter.

OpenClaw makes this easy with models.mode: "merge" — it combines your local models and cloud models into one pool that your agent can use:

This uses your local Qwen3 model by default (free), and falls back to Claude Sonnet via the cloud only when the local model can't handle the task.

7 You're not bad at this — it's genuinely hard right now

If you've spent two weeks babysitting your agent and feel like you're getting nothing done — welcome to the club. You're not alone, and you're not doing it wrong.

OpenClaw is not a finished product. It's an incredibly powerful framework at a very early stage. The people posting "my agent built a full web app overnight" have spent weeks — sometimes months — tuning their setup, writing custom skills, building task pipelines, and working through exactly the same frustrations you're experiencing.

The gap between the demo and real daily use is real. It's closing fast, but it's still there.

What helps

Think of it as training a new employee, not installing software. It needs onboarding. It needs rules. It needs to be told your preferences. The upfront investment is real, but once you've built that foundation, things compound. Your agent gets more useful the more context and structure you give it.

Start with tasks that have clear success criteria. "Check my email and summarise it" is easier to get right than "manage my entire digital life." Build trust with small wins, then expand.

Save everything that works. When you find a config, a prompt, or a skill that produces good results, save it. Write it down. Put it in a state file. Future-you will be glad you did.

Use the community. The OpenClaw Discord is where most people get help fastest. The subreddit (r/openclaw) is also active. Don't suffer in silence — there's almost always someone who's already solved the exact problem you're hitting.