This week's newsletter is sponsored by Anyshift.

Context is what separates a 30-second root cause from a 2-hour investigation

Anyshift maps every service, deploy, config change, and dependency into a versioned graph.

When an incident fires, it traces the root cause to the exact commit that caused it. No jumping between consoles. No guessing. Up to 85% MTTR reduction.

• Zero agents, read-only access, connects your stack in 30 minutes

• One graph that stays in sync across AWS, GCP, Kubernetes, GitHub, Datadog

• Start with one service, scale when you're ready

Used by engineering teams at Citrix, Yelp, MotherDuck and more.

Check the ROI

Thanks to Anyshift for sponsoring this newsletter. Let’s get back to this week’s thought!

Intro

Over the past few years, tools like ChatGPT, Claude, Copilot, and Gemini have made a big impact on the way we work. Especially in our industry, the focus has moved from pure writing code toward solving problems more effectively.

Now, we’re moving into a phase where AI doesn’t just respond to prompts, but actually takes action and gets work done for you.

That’s where OpenClaw comes in.

OpenClaw isn’t just another chatbot. It’s more like having an assistant that can break down tasks, spin up sub-agents, connect with the tools, and deliver real outcomes instead of just ideas.

There are still common downsides, though, where your overall judgment becomes more important than ever, and we’ll get to that later in the article!

In today’s article, we’ll go through what OpenClaw is, why it’s getting so much attention, and, most importantly, how you, as an engineering leader, can use it to save time, help your team, and build things.

Let’s start!

What is OpenClaw?

If you haven’t heard of OpenClaw before, it’s an open-source personal AI assistant that you can install on your own device, and chat with it through your preferred choice of messaging software. That can be WhatsApp, Slack, Discord, Telegram, and others.

If we make a comparison with ChatGPT, it’s less of a chatbot, but more of an autonomous assistant who executes tasks on your behalf. It can also connect to the tools that you use, and it understands the context of your work.

It can also spin up sub-agents and assign tasks to them to finish a specific (bigger) project. Think of it as: assigning a big project and implementing it as well.

It can dissect a project into multiple smaller tasks and assign them to other agents who would implement them in parallel.

The project was first published in November 2025 as ClawdBot and renamed to Moltbot on January 27, due to trademark complaints by Anthropic.

That’s the time it also gained a lot of momentum, and now (as OpenClaw) has already close to 350k stars on GitHub.

In February, OpenClaw was also bought by OpenAI.

Why Has It Gained So Much Popularity So Fast?

I’ve set it up myself in order to understand where the appeal is coming from, and I can clearly see why. There are many possibilities with it, and there are endless use cases that you can use it for.

It’s up to you for what particular things you want to use it for, and if it makes sense in terms of making you more productive. There are also more than 46k skills published in Clawhub, which you can use for your case.

And if you do something that’s not done yet, you can also publish the skill yourself, which is great!

We’re also going to go through the use cases that I believe are the most useful for engineering leaders later in the article.

A thing that I really like is that if you want to do a certain optimization, let’s say use fewer tokens per request, you can just ask openclaw, and it’ll share the available options that you can do, which you can just easily pick and choose the one that makes sense.

Even though setting it up can be a bit of a pain, especially for a less technical person, with enough perseverance, I believe anyone could set it up and start using it.

We’ll go through a step-by-step process on setting it up, and I’ll share my reasoning for what makes the most sense, what I found out works, and what doesn’t.

Choosing Where to Install It

You can install it on your own computer, a separate computer, a virtual machine, or on a dedicated server.

I don’t recommend installing it on your own computer, where you have all the important files that you work with daily. The reason is that you are giving OpenClaw access to your full computer to do things.

Unless you are really diligent with permissions, and you really know what you’re doing, I wouldn’t recommend it.

The quickest starting point and also a relatively cheap one would be to buy a virtual machine, a.k.a droplet, on a hosted service like DigitalOcean or similar. Here is also the guide if you want to do that.

They already have an OpenClaw image prepared that you can just install on the droplet.

The downside is that the OpenClaw version is most probably not going to be the latest, but I think you can update it manually yourself later on. So, if you just want to quickly try it and see how it goes, you can go that route.

But in our case, we are going to use our own hardware and install OpenClaw on a separate Mac mini. That also gives us complete control of all the data and resources as well.

If you want to follow along and install it on your own, feel free to do so; if not, you can read through the steps, and you’ll get insights on how to install OpenClaw and also ideas on how to use it.

Let’s start.

Let’s Prepare Our Mac Mini

Starting from scratch is the best way to go, so completely wiping out our Mac mini is the first step. You can do that by going to System Settings > General > Transfer or Reset > Erase All Content and Settings.

The second thing we want to do is to prepare all the necessary accounts and API keys. I highly recommend setting up a separate Gmail account for OpenClaw, which we are also going to use for creating a new Apple ID.

Also, having a password manager like LastPass or 1Password is really great. I personally use LastPass and then share only the necessary passwords to the Gmail account I use for the Mac mini, so I can just copy&paste them when I need them.

Regarding API keys, I first started by adding Anthropic’s API key to OpenClaw. But after trying out a harder task, where there was much more work, I quickly stumbled upon rate limits. So, my recommendation here is to set up at least another one, such as OpenAI’s API key or Gemini API key.

In the best case scenario, you would have all 3 (or even additional, like Grok, MiniMax, Deepseek, etc. and then OpenClaw can route different requests to different APIs if the rate limit has been hit. But for starters, you can start with creating 1 API key, and then if you hit rate limits, you can set up additional ones.

So, now that we have everything ready, let’s install MacOS on the Mac mini and create the Apple ID with the Gmail we created for this purpose. We’ll want to use Apple’s App Store to install the Amphetamine app, so we can keep our Mac mini on at all times.

If you want to go through a very detailed guide on the installation, check out this guide.

Installing OpenClaw

Once we have the MacOS installed, it’s time to start installing everything that we need for OpenClaw. We first need Xcode Command Line Tools. We can get it by simply copying this into the terminal:

xcode-select --install

Of course, having Homebrew is great, and you can get it by copying this into the terminal:

/bin/bash -c “$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)”

Next, you’ll want to have Node.js.

brew install node@24

After that, it’s time to start installing OpenClaw. Paste this into the terminal:

curl -fsSL https://openclaw.ai/install.sh | bash

And once you have it installed, you can start with onboarding:

openclaw onboard --install-daemon

We won’t go through this step in detail, but I highly recommend checking out the details on different options when onboarding here.

A cool thing after we go through onboarding is that we can check out the gateway dashboard on http://127.0.0.1:18789 or http://localhost:18789.

That’s where we can check logs, and a lot of other interesting info on what’s happening regarding openclaw.

Connecting Your Messaging Software

Once we have OpenClaw installed and onboarded on our system, that’s when it’s important to connect your messaging software of choice.

I personally use Telegram, as that’s what has been recommended as easiest, as you can quickly set up a bot there and connect it to OpenClaw.

There are a lot more options, like Slack, WhatsApp, Discord, etc. Check the options here.

In order to connect to Telegram, all we need to do is open Telegram, search for @BotFather, and start creating our own bot.

I won’t go into detail on how to do that, as this guide gives you a good walkthrough. Once we have our bot configured in Telegram, it’s important to connect it to OpenClaw.

On the chat with our bot, type /start, and it will return the pairing code. Then all we need to do is add the pairing code to OpenClaw. We can do it like this:

openclaw pairing list telegram
openclaw pairing approve telegram <code>

Now, once we have that all running, congrats, we have a working OpenClaw bot, which we can talk with!

If you want to go through the setup in detail and configure a lot more other things, this guide will help you with that.

Fun fact: I’ve named my bot GOclaw, but you can name it anything you wish!

First Thing I’ve Built

Now, once I had that, I started testing what’s possible and what’s not. The first thing that came to my mind was to ask GOclaw to call me and wish me a great day.

So, I asked, what is needed to achieve that. GOclaw responded with the plan to get a number on the Twilio dashboard (which I did) and then proposed to write a script that calls Twilio’s API and makes the call.

We basically did this in a couple of minutes, and it worked well! We then also played around with it to make a few tweaks and so on. It felt like working together on a problem, similar to how I would work with another engineer.

Another thing that’s important to keep in mind is that I was using Claude Sonnet 4.6 at the beginning as the main model of choice, but it became really expensive pretty fast, so I switched to using Haiku, and it was much cheaper and produced similar results.

The Second Thing: Technical Specification of a Project

After that, the next goal was to create a technical specification of a certain project. I specified the functionalities needed, provided examples (links to working functionalities) of what needs to be done, and included some of the links to where more information about what’s needed can be found.

So, in this case, if you have been using Cursor or Claude Code, instead of adding the context in the prompt or as a .md file in the project, you can just add context as a message, and OpenClaw will automatically use that to do what’s needed.

The first version was already pretty good, the second a lot better, and the third one, even better, which I was pretty happy with.

The Third Thing: Build the Project

Now that we have a technical specification, with a good plan of implementation, we can implement the project.

That’s when I saw issues with rate limits, as there’s a need for many different things to be implemented in order to finish the project, which took a lot of tokens, and Anthropic’s API just couldn’t support using so much in the short amount of time.

So, that’s when it’s really important to connect additional API keys, so that if the rate limit happens, OpenClaw can then call other APIs.

In the end, I was pretty happy with the result, as it implemented the project based on the technical specification. I also created a separate GitHub account (that is connected with GOclaw’s email) and created the repo there. The newly generated code was then also pushed to that GitHub repo.

My Thoughts After the Test Projects

So, these were my test projects in order to see what’s possible and how we can use OpenClaw. And I am impressed by the flexibility and the overall experience.

There are, of course, some things that are not so great, as the onboarding process can be quite tedious, as there are many things to think about, especially regarding security and ensuring that you really take care of permissions and restrict access.

And of course, as with all LLMs, hallucinations are the problem, and you need to have good judgment and overall technical experience to know if a certain approach is actually the right approach to take or not. You can’t get away with bad fundamentals and a poor understanding of engineering.

So, think of using OpenClaw as Claude Code or OpenAI Codex, just with a different interface (as you are talking via messages) and a bit more flexibility and options, as you have the whole Mac mini available to store things and create context.

I really like the overall user experience with that, as I find it much easier to do things, then just prompting via terminal or using a separate UI. And the reason is that we are already using messaging software a lot daily, so it feels a lot more natural.

Now, let me share some of the concrete examples that I believe you can use OpenClaw as an engineering leader.

How to Use OpenClaw as an Engineering Leader

After the test projects, here are my thoughts on projects that could be great to use OpenClaw as an engineering leader:

1. Use OpenClaw for side projects/internal tools

I think this is a great use case, especially if you are building projects where you are fine with just “throwing away code”.

• You can build a website that would help organize learning sessions for your teams, send reminders, and automatically generate transcripts + create documentation pages based on the session.

• You can build throwaway proof of concepts of certain new features and see the complexity behind them before handing them over to the teams.

• Build something that just helps you in your day-to-day life, maybe a quick daily reminder to go for a walk, or do exercise. Openclaw is really great at creating cron jobs and executing a certain task at a certain time.

2. Working on an already existing project

Now, here it’s really important to be a lot more careful. You can use OpenClaw the same way as you are giving access to human engineers. You can create a GitHub account and give access to specific repositories, and then ask to finish a certain task and open a PR.

You then review the PR, add comments, and then tell OpenClaw to make adjustments based on the comments and commit them.

Important: You should never give direct write permissions here, as that may cause a lot of issues. As I mentioned, hallucinations are a problem, and you can’t rely on the results being on point.

This is a trial-and-error approach, where you need to work on giving the best possible context and requirements, and good feedback. OpenClaw will store your feedback as context and ensure that the next time it will be considered.

3. Meeting checker and reminder

Ask OpenClaw to check your calendar and give you insights for every meeting 5 minutes before it starts. Who’s attending, some additional info about them, what’s the purpose of the meeting, and what are the key expected takeaways.

You can then also grab the transcription and summary of the meeting from the note taker and share that with OpenClaw, which can analyze if the meeting was needed or if it could be just an email.

4. Get the info about existing projects

As mentioned, OpenClaw is really great with cron jobs, and you can connect Jira/Linear with it and then ask to give you the latest summary on projects and tasks.

Are we still on track, or are there some potential issues that a certain timeline may not be reached? You can go into as much detail as you need.

5. Check for stale PRs

As we all know, some of the biggest blockers in engineering team productivity are slow code reviews. In my experience, slow code reviews have always been a sign of a poorly performing team.

What you can do is ask OpenClaw to create a cron job every morning and give you the list of all the PRs that have been open for more than 2 days.

Then you can make a habit in the morning and go through them and see if there’s a certain repeating pattern happening.

6. Turn Slack discussions into documentation/reports

This can be an interesting project, especially if you are doing incident management communication via Slack. Let’s say that there was an incident, and you were in charge of comms with other departments to ensure everyone was on the same page.

You’ve created a new Slack thread where you reported the findings and what’s happening at the moment.

After the incident is finished and the problem is gone, you can ask OpenClaw to analyze the thread and create an incident retrospective document based on the thread.

Then you can make a few adjustments needed, and you’re good to host an incident retrospective and ensure everyone is aware of the root cause and action items that need to be taken.

Last Words

These are just a few examples of how you can use OpenClaw to help you be more productive and get things done.

Over to you, what are you building with OpenClaw? I would love to know! Make sure to share your experience in the comments.

Liked this article? Make sure to 💙 click the like button.

Feedback or addition? Make sure to 💬 comment.

Know someone that would find this helpful? Make sure to 🔁 share this post.

Whenever you are ready, here is how I can help you further

• Join the Cohort course Senior Engineer to Lead: Grow and thrive in the role here.

• Interested in sponsoring this newsletter? Check the sponsorship options here.

• Take a look at the cool swag in the Engineering Leadership Store here.

• Want to work with me? You can see all the options here.

Get in touch

You can find me on LinkedIn, X, YouTube, Bluesky, Instagram or Threads.

If you wish to make a request on particular topic you would like to read, you can send me an email to info@gregorojstersek.com.

This newsletter is funded by paid subscriptions from readers like yourself.

If you aren’t already, consider becoming a paid subscriber to receive the full experience!

Check the benefits of the paid plan

You are more than welcome to find whatever interests you here and try it out in your particular case. Let me know how it went! Topics are normally about all things engineering related, leadership, management, developing scalable products, building teams etc.