Tired of babysitting your trading bots? 🍼 Let’s make them truly autonomous. What if OpenClaw could turn Hummingbot from a static script runner into a fully reasoning agent? 🧠 Imagine your bot autonomously: ✅ Monitoring portfolio health & exchange balances ✅ Dynamically starting/stopping executors based on real-time market context ✅ Reporting back to you via chat, so you can actually sleep 🤖✨ If your Hummingbot could reason and act on its own, what’s the VERY FIRST task you’d assign it? Drop your ideas below! 👇

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# Codex Features and Practical Usage 🤖 Stop babysitting the terminal — non-interactive mode lets you treat Codex as just another stage in your pipe, ready to drop into CI and scripts. 🏷️ Title: `codex exec` 🔗 URL: 📘 Overview `codex exec` runs Codex once, without launching the interactive UI. You pass the prompt as a single argument, the agent does the work, and only the final message is written to stdout. It is built for CI pipelines, pre-commit hooks, and ordinary shell pipelines. ⚙️ How It Works Progress logs stream to stderr while only the final agent answer goes to stdout, so it composes cleanly with pipes and redirects. Key flags: ・`--sandbox`: `read-only` (default) / `workspace-write` (allow edits) / `danger-full-access` (full access). ・`--ask-for-approval never`: suppresses approval prompts for fully unattended runs. ・`--json`: streams every event as JSON Lines (`thread.started`, `turn.started`, `item.completed`, `turn.completed`, etc.). ・`-o/--output-last-message `: writes the final message to a file. ・`--output-schema `: enforces structured output matching a JSON Schema. ・`-C/--cd `: changes the working directory before running. ・`--skip-git-repo-check`: bypasses the Git-repo requirement (normally required to prevent destructive changes). ・`--ephemeral`: keeps session files off disk. 🛠️ Practical Usage It pairs well with stdin. For example, pipe `npm test 2>&1` into `codex exec "summarize failing tests and propose minimal fix"` and tee the result to a summary file. Structured output gives you stable, machine-readable fields: pass `--output-schema ./schema.json` with `-o ./project-metadata.json`. You can chain sessions into multi-stage pipelines: run an initial `codex exec`, then continue with `codex exec resume --last` to fix what it found. 💡 Use Cases A common split is to trigger on CI failure, generate a patch read-only, then apply it and open a PR in a separate job that holds write permissions. It also works well for log triage — pipe the tail of a log and save root-cause analysis to `analysis.md`. ⚠️ Caveats Never expose API keys as job-level env vars in workflows that check out untrusted code; on GitHub, prefer the official Codex GitHub Action. The `--full-auto` flag is deprecated — use `--sandbox workspace-write` instead. If an MCP server marked `required = true` fails to start, `codex exec` exits with an error. Always pick the least-privilege sandbox for automation. #Codex# #CI#

bit bizzare how we went from babysitting models while they are implementing simplest of features to having agents securely build full fledged monoliths used by millions of users all in less than 8 months or so?

More building. Less babysitting infrastructure. @saranormous and @dok2001 just wrapped a live conversation about shipping and scaling the next generation of apps. Coming soon to @NoPriorsPod

🚀 AI agents can now handle even longer, harder coding and science work with less babysitting. Title: Introducing Claude Fable 5.1 and Claude Mythos 5.1 URL: 📊 Overview Anthropic released two new models built on the same underlying model with different safety configurations: Claude Fable 5.1 (general availability) and Claude Mythos 5.1 (restricted, vetted access). 🎯 Problem Solved The release targets three challenges: maintaining reasoning quality during long unattended runs, stronger self-verification in complex workflows, and reducing safety false positives that hurt legitimate users. 🔬 Methodology and Approach Mythos 5.1 is limited to vetted professionals through the Cyber Verification Program and Life Sciences Verification Program, while Fable 5.1 ships broadly as the standard model. New Enterprise Frontier Safeguards add zero data retention, and new anti-distillation protections block illicit capability extraction. 📈 Results Agentic scientific research benchmark scores jumped from 24.7% to 52.6%, and agentic coding scores from 42.0% to 55.8%. The model designed protein binders with 10x the affinity of competition winners and produced a new high-resolution Venus elevation map. Cache read pricing dropped 75%. #ClaudeFable# #AIAgents#