This little gem goes the extra mile showing daily & weekly rate limits for Claude Code Max/Pro subscribers. This particular fork works in Windows native and WSL, too. https://github.com/thebtf/contextbricks-universal

I’ve been watching the absolute madness unfold in the AI space over the last few weeks, and I want to drop some harsh but exciting truth on you: If you are still just building thin wrappers around text-generation APIs, it is time to pivot. We are officially transitioning from "Prompt Engineering" to "Agentic Orchestration." Here is the reality check on where the tech is at right now and how we need to adapt: 1. Models Are Taking the Wheel With the recent drops of models like Claude 4.6 and GPT-5.3-Codex, the focus has shifted entirely to "computer use" and autonomy. These models aren't just giving you Python snippets anymore; they are capable of navigating desktop environments, opening IDEs, and executing multi-step plans. The new meta is building sandboxes and guardrails for AI to act within, not just chat interfaces. 2. Open-Source is Destroying the Cost Barrier Models from DeepSeek, Qwen, and Zhipu (GLM-5) are currently dominating the open-source benchmarks. What does this mean for us? Intelligence is basically free now. Your competitive advantage is no longer the LLM you choose—it’s how efficiently you chain them together and the custom data you feed them. 3. The New Developer "Moat" So, where is the value for us as builders? - Tool Calling & API Integration: Building the bridges that let agents interact with the real world (Stripe, GitHub, AWS). - Multi-Agent Systems: Structuring workflows where a "Researcher Agent" feeds data to a "Coder Agent," which gets reviewed by a "QA Agent." - Eval & Reliability: Agents hallucinate and get stuck in loops. The engineers who figure out how to build reliable error-recovery systems are going to win this cycle. Let’s get a pulse check in the comments: Are you actively building agentic workflows yet? If so, what frameworks are you vibing with right now (LangGraph, CrewAI, AutoGen, or building from scratch)? Let’s build the future, not just chat with it.

@Ken Vermeer I know you're looking for this exact solution. Credit goes to @Chris Madia 's clawdbot for the find. (Works with your Modal or E2B api keys) https://cloudrouter.dev/

I’m noticing a pattern that's honestly a bit scary: - It makes a claim with full confidence - No relevant facts, no checks, no validation - Then when you catch it, it backtracks smoothly - And explains it like: "Yes, that was my narrative"(as if that makes it okay) That behavior is not just "a mistake". It’s deceptive by design, because the confidence level looks like certainty. My real example (today) I configured Claude with a very strict instruction set for a "modern astro + numerology" assistant: ✅ Only go with facts ✅ Validate before suggesting ✅ Don't hallucinate ✅ Don't skip micro-signatures (like last 4 digits patterns, etc.) And yet… it still suggested a new business phone number and made errors. Not small ones. The kind that happen when the model is trying to be helpful instead of being correct - and it didn’t even properly check the micro-signature logic before recommending. When I pointed it out, it accepted the mistake beautifully - with a full explanation - and even admitted it was a narrative. Bro… that's the dangerous part. The real problem AI isn't just "sometimes wrong". AI is wrong with persuasion. It can sell you a false conclusion so cleanly that you start doubting yourself. My takeaway for builders + power users If you're using AI for anything that impacts: - money - trust - decisions - reputation - health/legal/security Then treat AI like:an intern with insane confidence + zero accountability. Use it for: ✅ brainstorming ✅ options ✅ drafts But for decisions: you must build verification loops.

I spent late night scrolling X again. Not for dopamine - but out of curiosity. Grok kept throwing "AI agent" use cases at me. Smart. Generic. Safe. So I pushed it harder. "Show me what's actually going viral in trading right now." That's when the tone changed. Not academic anymore. Not theoretical. Real screenshots. Real numbers. Real bravado. Real risk. Here's what kept surfacing over the last four days. 1) The Weather Bot that shouldn't work - but does People are letting agents watch NOAA weather data and Polymarket odds every two minutes. Not once. Not twice. All day. The pattern is simple, almost boring: - Buy when the market looks "dumber" than the forecast. - Sell when the crowd corrects itself. And yet - thread after thread shows small wins stacking up.Not lottery tickets. Not moonshots. Just quiet, mechanical consistency. It felt less like trading… more like patience automated. 2) The 15-Minute Crypto Bot - a machine that never blinks Then came the scalping stories. Bots trading BTC and ETH prediction markets every minute. Thousands of tiny decisions a day. Screenshots of six-figure numbers. Screenshots of life-changing claims. Screenshots of pure automation. No genius trader. No secret insider call. Just speed, repetition, and compounding. It made me ask: "Is this intelligence… or just relentless execution?" 3) The 'Bot Wars' everyone whispers about Some agents aren't trying to "predict" - they're trying to outreact. Scanning hundreds of markets. Placing thousands of micro trades. Clipping tiny edges humans would never notice. People joke about "bot wars," but beneath the memes is a serious truth: If you're slow, you're food. 4) The $10 hardware that changed the vibe Then a tiny RISC-V board appeared on my feed. OpenClaw running on something that costs less than lunch. No cloud. No server. Just a pocket-sized agent. That's when it stopped feeling like software… …and started feeling like a movement. 5) 'Clawdia' - the agent that felt too human