There's a common thread between the French protests and unrest elsewhere in the Europe: the economic cost of always protecting pensioners, writes @LionelRALaurent (via @opinion)

Where capital moves on #JustLendDAO#? Supply Market 📥 🥇 #ETH# 🥈 #sTRX# 🥉 #TRX# Borrow Market 📤 🥇 #USDT# 🥈 #TRX# 🥉 #U# Supply reveals where users earn. Borrow reveals where liquidity is needed. Liquidity always leaves clues. 🔗Supply & earn:

A weekend fire at an Alberta military base killed several and seriously injured dozens in what Prime Minister Mark Carney called one of the worst peacetime tragedies ever for Canada's armed forces on home soil

Data engineers > AI engineers there's a big difference between a "RAG guy" and a "Data Intensive Applications" person like in this screenshot and there's never been a starker difference in demand in my entire career in tech (aka post search engine wars) if your blog / github is full of stuff like this, I have a fantastic mission/job for you (SF preferred, can relocate u, visas ok) (if you can name who's blog this is without even checking, you definitely are in the community. bonus points if you know where he ended up also without looking) jobs@latent.space and the team will reach out if you fit

A useful but little-known Claude API feature 🔌 Want to use Agent Skills not just in Claude Code or Console, but directly from your API? Now you can. Skills in the API shows how to invoke Agent Skills via the Messages API. Bring the power of skills into your own applications and supercharge API-based agents. 📌 Title: Skills in the API 🔗 URL: 🧩 Overview Agent Skills were originally a Claude Code and Console feature, but Skills in the API lets you call them directly from the Messages API. Apply the workflows, tools, and knowledge defined in skills to your API-based agents, deploying skills prototyped in the Console straight to production. 🛠 How to use it Specify skills in `container.skills` on your Messages API request (each entry takes `type` of `anthropic` or `custom`, a `skill_id`, and an optional `version`; up to 20 skills per request). You also need the code execution tool (`code_execution_20250825`) in `tools`, and then the API response reflects agent behavior guided by that skill. The key benefit: skills prototyped in the Console work in the production API without code changes. 🏗 Building it into production ・Production agents: deploy skills developed and tested in the Console directly to your API. Smooth transition from prototype to production. ・Microservice integration: have each microservice call the skills it needs via API. Easy skill sharing and reuse across services. ・Dynamic skill selection: build a router that calls different skills dynamically based on user request content. ・A/B testing: switch between skill versions via API to automate quality comparison evaluations. 💡 Use cases 🚀 Console-to-API skill deployment 🔗 Skill reuse across microservices 🔀 Dynamic skill selection routing 🧪 Skill A/B testing ⚠️ Watch out Skill quality determines result quality whether you're in the Console or the API. Test thoroughly in the Console before deploying to API. Also, skill updates may immediately affect API behavior, so pay attention to version management. ✨ Skills built in the Console work directly in the API. Use this shortest path from prototype to production. #Claude# #LLM#

# Codex Features and Practical Usage ⚙️ Review the moment a PR opens, ship a scheduled report every morning — run Codex as a single workflow step and the automation lives entirely in CI. 🏷️ Title: Actions Execution (Codex GitHub Action) 🔗 URL: 📘 Overview The Codex GitHub Action (`openai/codex-action@v1`) is the official action for running Codex from GitHub Actions workflows. It installs the Codex CLI, configures API access, and runs `codex exec` for you, keeping code review, quality gates, and scheduled reports entirely inside CI. ⚙️ How It Works Store your OpenAI key as a GitHub secret (e.g. `OPENAI_API_KEY`) and check out the code before invoking the action. Key inputs: ・`prompt` / `prompt-file`: inline instructions or a prompt file in the repo (pick one). ・`model` / `effort`: choose the model and the work intensity. ・`sandbox`: `read-only` / `workspace-write` / `danger-full-access` control filesystem and network access. ・`codex-args`: extra CLI flags as a JSON array or shell string. ・`output-file`: save the final message to upload as an artifact. The `safety-strategy` input defaults to `drop-sudo` (irreversibly removes sudo); other options are `unprivileged-user` and `unsafe`, which Windows runners require. Results are exposed via the `final-message` output. 🛠️ Practical Usage A minimal review workflow triggers on `pull_request` (types `opened`, `synchronize`), checks out the code with `actions/checkout@v5`, then runs `openai/codex-action@v1` with `openai-api-key` from secrets, a `prompt-file`, and an `output-file`. To post the result as a PR comment, pass the `final-message` output to `actions/github-script` in a downstream job (which needs `pull-requests: write`). 💡 Use Cases Use `pull_request` triggers for review and quality gates, `schedule` (cron) for periodic reports, `workflow_dispatch` for manual runs, and `issue_comment` for comment-driven automation. ⚠️ Caveats You cannot supply both `prompt` and `prompt-file`. If you ingest PR titles or comments, guard against prompt injection and restrict to trusted events or explicit approvals. Keep `safety-strategy` on `drop-sudo` or an unprivileged user, and place the action at the end of the job to avoid inheriting state. After `drop-sudo` you may need to grant write access (e.g. `chmod -R g+rwX`). #Codex# #GitHubActions#

100,000 USDC up for grabs! 🦋 The @flapdotsh × @bstocksfinance × @BinanceWallet Booster Campaign is going LIVE soon! Complete social, Flap trading tasks, and bStocks purchase for a share of the rewards. 💰 Reward Pool: 100,000 USDC 📅 Oct 19, 07:00 UTC – Nov 2, 23:59 UTC On Flap, trade $10+ worth of meme tokens paired with bStocks using BNB to complete the trading task. More details coming soon at