Is OpenClaw actually worth the effort or is it just outdated

I’ve been trying to automate as much of my daily life as possible lately, mostly using a repurposed 2017 Intel MacBook that I turned into an always-on server. For the most part, the workflows I’ve built are strictly deterministic—once the script or the logic is set, it just runs without needing any heavy lifting from an LLM. However, I've hit a wall with traditional automation, and I'm debating whether moving toward an OpenClaw-based workflow is the right move or if I'm chasing a trend that has already peaked.

My biggest headache so far has been trying to integrate Home Assistant into this setup. I made the mistake of running Home Assistant inside a virtual machine on that old MacBook, and it was a disaster. The resource overhead was so high that the laptop started overheating constantly, which eventually caused iCloud syncing to fail. Because my automation logic relies on writing data directly to Obsidian, that sync failure broke my entire productivity chain. It turns out that a dedicated Raspberry Pi is actually a much better deployment choice for Home Assistant than trying to force a high-level VM onto aging laptop hardware.

This brings me to the question of agentic workflows and OpenClaw. When the headlines were screaming about these types of frameworks, I didn't jump in. Now that the dust has settled, I'm looking at my current "dumb" automations and wondering if adding a layer of reasoning via an LLM agent would actually solve the rigidity problems I'm facing.

If I were to implement a more advanced AI workflow, I'd want to move away from "if this, then that" logic and toward something that can handle ambiguity. For example, instead of a script that just writes a timestamped note to Obsidian, an agentic approach could potentially interpret the context of my day and decide how that information should be categorized.

But there is a massive catch: the hardware and stability aspect. If running a simple VM for Home Assistant crashed my entire ecosystem, I have to be incredibly careful about how I manage the deployment of an LLM-driven agent. Running local models for an agentic workflow requires significant VRAM or a very stable connection to an API, and I don't want to end up in another situation where a runaway process overheats my server and breaks my Obsidian sync again.

I'm trying to figure out if OpenClaw offers enough of a leap in capability to justify the complexity of managing it alongside my existing tools. Is it a practical tutorial-level project for a hobbyist, or is it something that requires a much more robust, dedicated server environment to be truly useful in a real-world setting? I'm leaning toward wanting more intelligence in my automations, but I don't want to break my hardware doing it.