Michael already answered these pretty well, I'll just add my take from what I'm doing with my agency 1. Keeping agents organized and cost-effective Ask it do delegate to subagents as much as possible, they're very token-efficient Rotate between models for different tasks. For non-reasoning-heavy stuff like summaries or cleaning up reports , I use GPT or Sonnet instead of Opus Opus has a huge reasoning window and will burn through tokens fast.

2. Building tools that give replicable outcomes Two things I do here: First, after it builds something I make it put as much info in markdown as possible so it has its own knowledge base Second, I ask it to build an internal tool in Python or whatever where the AI doesn't have to reason through the task every time. It just runs the script Once I'm confident the quality is good enough for day-to-day use, I just let it run For example we use ClickUp for project management. We built an internal tool that scans ClickUp, GitHub, Figma, and generates daily and weekly reports automatically every day. You can also build a dashboard with an API so you can access it visually and see the AI's internal process 3. Giving these tools to your team What we did is install OpenClaw for each team member, replacing all their ChatGPT and Gemini subscriptions We set up a shared Discord channel where everyone shares their OpenClaw knowledge and their agents share knowledge between each other you can use Slack as-well here. For example one of our team members built a meeting summary skill that puts post-call summaries into our project management tool They made it a shareable one-click install. Now all agents on our team have that skill instantly Our agents are learning from each other way faster than if everyone was using it solo If you have the visual dashboard you can just ask it to add team functionality so your whole team can use it together

VPS with the right security setup is far better Most VPS you can get for around $20/month and it'll run OpenClaw at scale The good part is if you wanted to scale your AI workforce by adding more specialist agents like a marketing guy and a head of ops, your only cost is spinning up another instance With the setup we do you also get 24/7 backups in case something goes wrong, and the ability to clone an agent's brain to another one instantly On the other end, a lower end Mac Mini is $599 You'd have to do some work to not expose your IP and home network when putting it on the internet It'll run some mid-tier open source models, which honestly until now aren't good enough to do serious work that you can do with Opus The only real advantage you get is access to Apple Notes and iMessage