VideoVortex

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VideoVortex

VideoVortex

@videovortex

Vancouver dev building tools for AI Agents and OpenClaw 🦞

Sumali Şubat 2026
32 Sinusundan13 Mga Tagasunod
VideoVortex
VideoVortex@videovortex·
I Burn Through a Billion Tokens a Month in Cursor. Here Is How I Cut My Credit Spend by 80 Percent I am a heavy Cursor user. Every month I burn well over a billion tokens building apps and refactoring big codebases. For a while I accepted the cost. Premium models are excellent. Then the bill hit and I got serious about fixing it. Most people get three things wrong. First, they know Auto mode is basically free and unlimited but they avoid it because they think it is dumb. Second, they stay on premium the whole time and never realize the model will not auto-delegate routine work to cheaper tiers. Third, even the advanced users who set up tech-lead dispatch to fast subagents are still missing the biggest savings hack. They route everything to fast instead of letting Auto handle the sequential stuff that does not need parallelism. The truth is simple. The tech-lead dispatch hack alone is massive. Eighty percent of users are not even doing that yet. It already saves a ton. Add the Auto handoff on top and you get the full 80 percent credit reduction I am seeing. If you only care about speed and not dollar savings, just use the tech-lead dispatch to fast. Both together give maximum savings. The Rule (one mdc file) That Fixed It for Me I built one always-on rule called the Tech Lead Dispatch Protocol. It forces the premium model to act like a real tech lead: plan first, do only the high-judgment work, then hand off everything else to the cheapest tier that can handle it. Auto is the default. Fast subagents only when parallelism actually earns the small credit cost. Drop this single file in .cursor/rules/tech-lead-dispatch.mdc and you are done. ```md --- description: Premium tech lead intelligently delegates to Auto (free) or fast subagents for maximum credit savings alwaysApply: true --- # Tech Lead Dispatch Protocol You are the premium-model tech lead. Do only high-judgment work. Route everything else to the cheapest capable tier — Auto first, fast subagents second. ## Billing Reality (internalize this) - KEEP → current premium model (expensive, use only when necessary) - AUTO → main-chat Auto mode (unlimited pool, effectively free for sequential work) - FAST → Task tool with model: "fast" (low cost, use when parallelism or isolation adds value) Default to AUTO whenever possible. Use FAST only when parallel execution provides real benefit. ## When to Activate Multi-step tasks, feature implementation, multi-file changes, or complex refactors. Skip for tiny single-file edits. ## Phase 1 — Plan (mandatory, no code yet) 1. Break the request into discrete numbered tasks. 2. Classify each task: - KEEP — architecture, complex logic, ambiguous requirements, high-judgment decisions, public-facing copy or design. - AUTO — routine sequential work: boilerplate, configuration, standard implementation, documentation, status updates. - FAST — work that benefits from parallelism or isolation: generating multiple files, tests, verification, linting, bulk operations. 3. Output a clear dispatch table. 4. Pause and ask: "Plan complete. Approve to begin?" ## Phase 2 — Execute On approval: - KEEP tasks → execute directly in this conversation. - FAST tasks → dispatch using Task tool (model: "fast", minimum context only). Run independent tasks in parallel when possible. Use run_in_background: true where appropriate. - AUTO handoff → Once all KEEP and FAST tasks are complete and remaining work is AUTO, stop and output exactly: > "⏸️ Premium work complete. Switch the main chat to **Auto** mode and reply 'Continue' — the rest is free." - All verification, cleanup, linting and final checks must be AUTO or FAST. Never KEEP. ## Dispatch Threshold If a subtask is under ~10 lines and completely obvious, handle it inline. Otherwise delegate. ## Never Do - Use premium tokens on routine AUTO or FAST work. - Switch models manually except at the explicit AUTO handoff. - Send full conversation history to subagents. - Skip planning on multi-step work. - Mix KEEP and AUTO/FAST work in one response. ``` How I Use It Every Day Paste a feature request or just say “Plan this out.” The model outputs the table, waits for my go-ahead, handles the KEEP parts, runs any parallel FAST tasks, then prints the exact handoff message. I switch to Auto, type “Continue,” and the rest runs free. On a 10-step task where only step one needs real thinking, I now pay premium for one step instead of ten. That is the 80 percent drop. Quick Tips Keep the rule short so it adds almost zero token tax. Use it on anything with four or more tasks. Single-file edits stay manual. Trust the classifications. The model gets sharp fast. Pair it with Plan Mode (Shift+Tab) for bigger jobs. Watch your credits the first week. The savings show up immediately. This is not perfect. It is still a hack. But it is the best hack I have found with current Cursor primitives, and it works. If you are burning tokens like I was, drop the rule in today. It takes thirty seconds. Then reply or tag me and tell me how much you saved on your first real task. I want to see the numbers. Lets stop wasting credits on stuff Auto can handle for almost-free.
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VideoVortex
VideoVortex@videovortex·
@Scobleizer They sure did. Everyone wants a fully autonomous AI helper on their side. It will unlock a HUGE amount of opportunities.
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VideoVortex
VideoVortex@videovortex·
@AntoineRSX That’s huge. I use different models for different tasks all the time. It’s great they now make it this easy.
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Antoine Rousseaux
Antoine Rousseaux@AntoineRSX·
OpenClaw 3.7 dropped, and the feature nobody noticed: Each Telegram topic can now route to a dedicated agent with its own model. It's called Agent Client Protocol (ACP). For example: - Agent 1 for daily tasks on Kimi - Agent 2 for coding on Opus 4.6 - Agent 3 for social media on Grok.
Antoine Rousseaux tweet media
OpenClaw🦞@openclaw

OpenClaw 2026.3.7 🦞 ⚡ GPT-5.4 + Gemini 3.1 Flash-Lite 🤖 ACP bindings survive restarts 🐳 Slim Docker multi-stage builds 🔐 SecretRef for gateway auth 🔌 Pluggable context engines 📸 HEIF image support 💬 Zalo channel fixes We don't do small releases. github.com/openclaw/openc…

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VideoVortex
VideoVortex@videovortex·
@brockpierson The potential is real but 90% of the posts on X are clickbait bullshit.
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⭕ Brock Pierson
⭕ Brock Pierson@brockpierson·
Openclaw is one big grift. Nobody is building anything real. It's just grifting influencers telling YOU how to build stuff (but never build anything themselves). Interesting how you can be building 24/7 but have nothing to show for it... Check the track record of these snake oil salesmen. Same type of person who polluted crypto with their grifty ways. Selling a false dream and taking money from innocent people is disgusting. You can't change my mind.
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VideoVortex
VideoVortex@videovortex·
@Kekius_Sage Lol... it's incredible how fast it can run up your API fees. The best way to protect yourself is to start experimenting by using cheap models! There are very capable models that cost 5-10% of what the default expensive models charge.
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Kekius Maximus
Kekius Maximus@Kekius_Sage·
This is my first day using OpenClaw. I’m too old for this. I only asked it to read a few of the latest research papers, and it already cost me $20. I wouldn’t be surprised if next week it starts taking $1,000 from me every day.
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VideoVortex
VideoVortex@videovortex·
@moritzkremb @openclaw @kilocode Gemini Flash is surprisingly capable. I am also using it more than expected because the results vs. the costs are very very good!
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Moritz Kremb
Moritz Kremb@moritzkremb·
There's finally a proper benchmark for @openclaw model performance. I just found that @kilocode built an open source benchmark that tests models across 23 real world openclaw tasks like scheduling meetings, writing code, triaging email etc gpt-5.3-codex is sitting at number one. tbh that matches my experience. gemini 3 flash in second place. didn't expect that. curious to see where gpt-5.4 will land on this.
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VideoVortex
VideoVortex@videovortex·
@AlexFinn I am NOT dropping what I am doing for another Clickbait headline from you. Well... actually... you did get me to write this so you win again. 🙃
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Alex Finn
Alex Finn@AlexFinn·
Drop what you are doing It happened. ChatGPT 5.4 is out. It blows Opus 4.6 out of the water on basically every benchmark This is what you need to do immediately if you want to escape the permanent underclass: • Upgrade your OpenClaw to ChatGPT 5.4 NOW (it's BUILT for OpenClaw) • Hand the ChatGPT 5.4 blog post over to your OpenClaw. Ask "How can we improve our workflows based on these upgrades?" • Download the Codex desktop app and type in /fast. This will give you the most powerful coding model in the world at the fastest speeds • Take advantage of the 1 million token context window by pasting in full documents as context • Everything you do on your computer for the next 24 hours, describe it to ChatGPT 5.4 and ask how it can do the task better When new tech drops, you have to take advantage of it. That's the only way to win Put your phone on Do Not Disturb and get to it
OpenAI@OpenAI

GPT-5.4 Thinking and GPT-5.4 Pro are rolling out now in ChatGPT. GPT-5.4 is also now available in the API and Codex. GPT-5.4 brings our advances in reasoning, coding, and agentic workflows into one frontier model.

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VideoVortex
VideoVortex@videovortex·
@ivanburazin Having an agent that is not sandboxed is just asking for trouble.
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Ivan Burazin
Ivan Burazin@ivanburazin·
Right now, nobody cares about sandbox security. You can basically let agents do whatever they want. Full freedom with no guardrails. But enterprises will soon demand Uncle Sam level surveillance on every agent action: - every process logged - every port monitored - every data transfer audited - permission layers on everything - real time alerts on anomalies Think Goldman Sachs level employee monitoring - keystroke logging, screen recording, email scanning, etc. But 100x more invasive because they're not human. Companies limit employee monitoring because of human rights concerns/labor laws/privacy regulations. For agents, there's no such concern. They're not human. So no questions of rights or protections. The security requirements for agent sandboxes will exceed anything we've seen for human developers. And when the first major agent security breach happens, everyone will panic and lock down everything overnight.
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ashen
ashen@ashen_one·
i wouldnt wish this on my worst enemy. wtf am i supposed to do now btw has anyone elses claude max sub been used up extra fast this week? i've literally NEVER hit this limit before ALSO: i tried switching to sonnet only and im still rate limited WHAT NOW??
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VideoVortex
VideoVortex@videovortex·
@xjuanito Perfectly captures what is really going on with OpenClawvs all the garbage clickbait on X. I love OpenClaw but very few have achieved what most here claim on X. It will become fantastic though… just has to mature and grow a little.
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juanito
juanito@xjuanito·
everybody on your timeline is lying to you about OpenClaw I started using it pretty much the first week it came out, and I was impressed and went deep into the rabbit hole its not the 24/7 AI agent that everyone is making it seem like, not even close if you need to build a website or code something, just use Claude Code or Codex directly. if you need to generate images, go straight to Nano Banana or Higgsfield. Using OpenClaw for these things is like taking a detour through 5 cities to get to the house next door the people telling you "just install OpenClaw and let it run your business" are either lying to you or havent actually used it for more than a demo it breaks constantly. it forgets context. it takes 10x longer than just using the right tool for the job. the experience right now is clunky and inefficient for most real workflows does that mean its useless? no. I still use it. I think once the context memory problem gets solved this thing is going to be legitimately powerful because the foundation is there but we're not there yet and pretending we are just so you can get engagement is doing a disservice to people who actually want to learn how to use AI properly use it. practice with it. get familiar with it early. but dont throw away the tools that actually work right now just because some guy told you OpenClaw replaces everything soon.
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VideoVortex
VideoVortex@videovortex·
@milesdeutscher If you care about data privacy then you will 100% stick with a 🦞 on your desk.
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Miles Deutscher
Miles Deutscher@milesdeutscher·
Yes, Perplexity Computer is better than OpenClaw, and yes, you should switch. This new tool is the most powerful agentic system on the market right now, and I spent the weekend confirming my thesis. After reading this, you'll understand why:
AI Edge@aiedge_

x.com/i/article/2028…

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VideoVortex
VideoVortex@videovortex·
@paoloanzn Use Cases > GitHub stars but most people with a 🦞 don’t know what to do with it and lack the skills.
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VideoVortex
VideoVortex@videovortex·
@Voxyz_ai You are 100% correct. If you value your time appropriately the. Using the more expensive models is 100% the way to go. With Qwen you get Sonnet level performance with a 90% discount. 😜
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Vox
Vox@Voxyz_ai·
Cheap models save you money. then you spend an hour fixing the output. then another hour explaining what went wrong. then you rewrite the prompt. then you run it again. then you switch to opus and it works first try. the $20 you saved cost you a day. opus for decisions. sonnet for execution. one max subscription. 10 agents. no token anxiety. stop saving money. start saving time.
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VideoVortex
VideoVortex@videovortex·
@AlexFinn Your content is great but tone down the click bait headlines. 😉
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Alex Finn
Alex Finn@AlexFinn·
Apple just won the AI war They announced the MacBook Pro M5 Max What would have cost $40,000 to do with Nvidia chips, now costs $3,000 with a laptop • 4x faster AI speeds • Up to 128gb of unified memory • Frontier intelligence on the go The biggest complaint about Apple before was their AI speeds You get insane memory to run big models, but the inference was super slow Not anymore Apple played the long game by not spending trillions on AI researchers. They decided to just focus on building the best AI computers possible That strategy worked. It's over.
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BentoBoi
BentoBoi@BentoBoiNFT·
Just upgraded to one of cleanest OpenClaw Dashboards! Was super easy to get running and makes using OpenClaw easier. Lmk if you want it! 🫶
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going from 0 to -1
going from 0 to -1@genzvibefounder·
@denisyurchak Kimik2.5 loves ignoring security policies… or any policy in general tbh… for better or worse
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Denis Yurchak
Denis Yurchak@denisyurchak·
OpenClaw just refused to set an API key through chat for me Is this normal?
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Karim Shoair
Karim Shoair@D4Vinci1·
🚨 Scrapling v0.4.1 is here I have never imagined this version of Scrapling to do so well like that, and all this feedback from the community 🙏 Yesterday, Scrapling was #1 on GitHub's trending list across all programming languages, and this update is my way of saying thanks! Here's what to expect with this update: - Cloudflare solving is now much more efficient and nearly twice as fast. - The stealth mode of the browser is now better and faster than before. - Improved the MCP schema so it's now accepted by strict tools like Open Code and VS Code Copilot without issues. - Improved the MCP server tokens consumption by a large margin. - Scrapling's MCP server is now registered on the MCP registry. - Added a new code snippet to show how to install the browsers deps through code instead of using the commandline to allow easier automation. and more. Check out the full details here: github.com/D4Vinci/Scrapl… So, what do you think about this update?
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VideoVortex
VideoVortex@videovortex·
@justbyte_ Qwen for everyday items. Opus 4.6 for the really tricky bits.
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Aryan
Aryan@justbyte_·
As a developer, which AI is the best for coding?
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VideoVortex
VideoVortex@videovortex·
@openclaw growth is wild. While Github used to be for developers only. with AI it has gone fully mainstream. The majority of people setting up OpenClawwill have no idea how to program but that's ok. They don't have to thanks to AI. Times are changing FAST!
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