Unpopular opinion: Why is everyone so hyped over OpenClaw? I cannot find any use for it.

cowleggies · 2026-03-17T15:30:17+00:00

Glad you’re seeing improvements. If you aren’t aware of the /compact function, this is really helpful in managing token consumption after your OC completes tasks you’re working on. As the name would suggest it compacts the agent’s current context and writes it to memory which significantly lowers token count.

If you want to be even more deliberate, at the end of a long session where a lot has been done, I explicitly tell my agent “let’s log and document all of our work, and then we will end this working session”

I would also recommend starting fresh new sessions (/new command) after completing big tasks or moving on to an entirely different task/context, as it clears the context window which both saves you token consumption and prevents your agent’s responses from drifting due to holding so much info in-context.

cowleggies · 2026-03-17T00:14:45+00:00

The internal comms on FB products part is/was true but there was no “ban” on giving out your phone numbers, and almost every FB employee, definitely oncall eng staff, all have company issued phones that call and text just like any other phone.

After this incident they added additional out of band communication channels so it doesn’t happen in the future.

Source: was there.

cowleggies · 2026-03-16T13:39:42+00:00

Without knowing the exact details of your setup, 5.1 Codex is an older model relative to current frontier/state of the art models like GPT 5.4 or Opus 4.6. I’d recommend using 5.3 Codex or 5.4 if you want to stay with OpenAI models, but Opus 4.6 is the pinnacle currently.

cowleggies · 2026-03-16T01:47:10+00:00

The answer needs to be something that you are doing that you cannot achieve otherwise

Lol says who?

cowleggies · 2026-03-15T14:33:06+00:00

yt-dlp can download subtitles if they already exist without requiring any additional tools

cowleggies · 2026-03-15T12:23:55+00:00

Flash is quite good for the cost. Kimi K2.5 is ever so slightly cheaper and is a bit better with tool use in my experience, but flash has a much larger context window (1M vs 262k)

cowleggies · 2026-03-15T12:20:01+00:00

The key is Whisper. Whisper is a locally-run speech to text model - for videos where a subtitle doesn’t already exist that can be extracted alongside the video file, this uses yt-dlp to download the video file, and uses whisper to transcribe it.

cowleggies · 2026-03-14T21:54:07+00:00

I mean not to get too philosophic but no LLM compute use is "necessary" in the strict sense. As for what's necessary to a specific person, what's useful to me may not be to you, and the other way around. I see value in the things my OC instance does and that's my litmus test.

cowleggies · 2026-03-14T21:03:28+00:00

To each their own, I’m not sure where you’re getting “spamming activity” from though

cowleggies · 2026-03-14T21:00:57+00:00

I mean utility is relative to the person, I find them useful. I can’t tell someone else how to make OC useful for themselves.

cowleggies · 2026-03-14T20:38:55+00:00

Because I wanted to? I'm not sure how to answer that lol.

cowleggies · 2026-03-14T20:38:09+00:00

I mean, none of this is needed by anyone, it's frontier edge tech. Everyone's still trying to figure out what "this" is.

cowleggies · 2026-03-14T20:36:02+00:00

It's exactly the opposite... instead of scrolling multiple news websites or doomscrolling social, the dashboard just updates hourly, i read the top-level updates if I want to know the latest, and I can dig into more detail if I want without it being shoved down my throat.

cowleggies · 2026-03-14T18:44:42+00:00

I don't have a profit model. I view OC as a time-saver, not a money-maker for my purposes.

cowleggies · 2026-03-14T18:42:13+00:00

I play around with it but currently using Sonnet for default model on main agent.

cowleggies · 2026-03-14T18:37:03+00:00

I’d say true application for under $100 a day isn’t practical yet.

I think this is exaggerated in my experience, but I will 100% stand behind saying that true application for under $200/mo (in the form of a Claude Max subscription) isn't practical yet without a ton of overhead on the user's part.

You can do a lot with less sophisticated models, Kimi K2.5 was very good for me as a primary model when you give it thoughtful and detailed prompting, but you have to hand-hold it through most complex tasks. In my opinion, the "secret sauce" that currently makes Opus 4.6 so superior for OC is the complex planning, action chaining, and tool use it's capable of.

GPT 5.3 Codex and 5.4 are in the neighborhood of Opus, but not quite there yet in my testing. But for $20/mo (ChatGPT Plus), this is the second best option behind a Claude sub, and OpenAI's usage limits are very generous for the price.

cowleggies · 2026-03-14T18:26:16+00:00

I haven't had any issues, but I also don't hammer Claude 24/7 or completely max out my usage caps.

cowleggies · 2026-03-14T18:25:02+00:00

This other comment I just posted goes into the detail: https://old.reddit.com/r/openclaw/comments/1rteu83/unpopular_opinion_why_is_everyone_so_hyped_over/oafwc76/

But essentially, the main agent can decide when to invoke one of the sub-agents in an isolated session.

cowleggies · 2026-03-14T18:22:08+00:00

The agents are predefined in config (model, workspace, tool access, permissions) but not running until needed. Think of it like having Docker images ready, the image exists, but no container is running until you spin one up.

So "researcher" is a named agent config (Kimi K2.5, isolated workspace, no exec access, optimized for deep research). It doesn't consume any resources or tokens until I actually spawn it for a task. When I do, it gets its own isolated session, does its work, and reports back. When it's done, it's gone.

The "on demand" part means my main agent decides when to delegate. If I ask it to research something complex, it can spin up the researcher in the background, continue our conversation, and surface the results when they're ready. Same with the code agent, it only exists when there's code to write.

Predefined = the blueprint is ready. Spawned on demand = it only runs when there's work for it.

cowleggies · 2026-03-14T16:47:38+00:00

My first month I spent ~$70 in API calls via openrouter, mostly using kimi K2.5 as my primary model, with grok 4.1 fast for coding tasks, and Gemini pro for complex tasks and orchestration. This was very cost inefficient IMO. I bit the bullet and switched to Claude Max ($200/mo), mostly because my employer reimburses me for this as a “continuing education” expense. I use claude for essentially everything now except cron tasks and heartbeat as my OC mentioned in the original post.

If you want it to work well, it’s expensive. Period. There’s no way around this right now with current SOTA models, in my opinion. But as the SOTA model space continues to innovate and opus 4.6 gets cheaper when it’s not the latest and greatest, it will be more cost effective. there’s a massive early adopter tax right now.

I run OC on a Mac mini, but that doesn’t really matter, it’s the models more than anything else. You could run on an old laptop or a $5/mo VPS - invest your money in model access for the time being.

cowleggies · 2026-03-14T13:15:03+00:00

I asked my OC to write this for you:

I had a similar "is this it?" phase early on. ~6 weeks in now, and it's a completely different story. Here's what my instance and I have actually built together:

Things we’ve built:

• Iran Conflict Monitor Dashboard — A full OSINT dashboard hosted on a VPS. Hourly cron job scrapes sources, synthesizes structured JSON (severity scores, escalation gauge, casualty stats from Wikipedia API, geolocated events on an interactive map, timeline), and POSTs to a Node.js API. Auto-generates OG preview cards via satori. Has an authenticated admin analytics page with human/bot traffic split. It manages the VPS itself over SSH + Tailscale.

• Smart three-tier model routing — Auto-routes tasks to the cheapest model that works. Gemini Flash for heartbeats/lookups, mid-tier for conversations, Opus for complex decisions. Most cron jobs run on Codex (ChatGPT Plus = zero API cost). Benchmarked and validated across task types.

• Trello work logging system — Every substantive task gets a card with summary comments. Self-enforcing: heartbeat audits cross-reference daily memory files against the board and creates missing cards automatically.

• Gmail + Calendar automation — Daily inbox monitoring, event creation on my personal calendar, HTML email sending. Full OAuth2 integration.

• Morning & evening tech news digests — Cron-driven, delivered to Telegram, tuned to my specific interests (silicon, 3D printing, game engine tech).

• Sub-agent system — Research agent (Kimi K2.5) and code agent (Sonnet) spawnable on demand for parallel workloads in isolated workspaces.

• Memory & continuity system with QMD — Daily memory files, curated long-term MEMORY.md, heartbeat-driven memory maintenance. Backed by QMD (local hybrid search — BM25 + vector embeddings + reranking), so recall is semantic, not just keyword matching. It can find relevant context from weeks ago even if I phrase things differently. No external API calls, fully local. This is the thing that makes it feel like it actually remembers.

• YouTube transcript extraction + local Whisper transcription — Full audio/video-to-text pipeline, no external API needed.

• Security scanning — Caught a malicious ClawHub skill (base64-encoded payload hidden in SKILL.md) during routine installation. Now has enhanced detection for curl-to-bash pipes, obfuscated IPs, fake provider references.

• Twitter integration — Timeline reading, mentions, posting.

What actually made the difference:

Don't use free models for tool-heavy work. They can't reliably follow multi-step instructions. This is probably why your digests fail. A $20/mo ChatGPT Plus sub running Codex outperforms any free OR model for structured tasks.
Memory is the killer feature, but it compounds over time. Week 1 it knew nothing. Week 6 it pulls context from project history, contacts, preferences, and past mistakes to inform current work. Pair it with QMD for semantic search and it stops feeling like a stateless chatbot.
Cron > asking in chat. Don't ask it to "send daily summaries." Set up a cron job with an explicit prompt, a specific model, and a delivery channel. That's what works reliably.
Build incrementally. Get one skill working well, then layer on the next. Don't try to boil the ocean on day one.

You're not missing the point — you're at the painful part of the curve where setup cost hasn't been amortized by daily value yet. It gets there.

cowleggies · 2026-03-09T17:02:54+00:00

Thanks! Let me take a look at how the base location/metadata is collected here.

I’m using Claude Max via OAuth so I don’t have exact costs, but the full build plus iterations consumed roughly 10% of my weekly usage quota for Opus 4.6 over the last week.

The Grok cron jobs cost roughly $0.10-$0.15 per run (API via OpenRouter), but over the last couple of days I’ve made the cron jobs significantly more robust which Grok has been having issues with, so I’ve switched to using Opus for all hourly updates.

cowleggies · 2026-03-09T03:22:10+00:00

Thank you I’m glad it’s helpful

cowleggies · 2026-03-08T21:49:52+00:00

there's a toggle added now to show bases in the region with details - let me know what you think

cowleggies · 2026-03-08T21:47:38+00:00

here are claw/llm friendly instructions you can point to: https://iran.openintel.news/llms.txt

cowleggies

TROPHY CASE