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Agent Lightning v1.0.1 is the first official release of the Agent Lightning Skill. It helps coding agents optimize other AI agents by providing an editable agent and a benchmark, guiding improvements to prompts, tools, workflows, models, and reasoning settings to balance accuracy, cost, latency, and reliability through measured iteration. Install it for Claude Code, Codex, or GitHub Copilot with: gh skill install microsoft/agent-lightning agent-lightning --agent <agent>. The release also strengthens CI, packaging, release automation, documentation, and benchmark reporting.
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Copernicus data show the world's oceans outside the polar regions reached a record average surface temperature of 21.1C (70F), edging past 21.09C seen in March 2024. The rise is linked to decades of human warming and an intensifying El Niño, which is expected to strengthen to Christmas and could be the strongest in centuries. Warmer seas boost extreme weather, raise sea levels, and threaten marine life; oceans absorb over 90% of the excess heat. Heat also lingers around Europe, with long marine heatwaves in the English Channel.
l3a0/claude-plugins provides a Claude Code plugin marketplace. The kindle-highlights skill exports all highlights from a book in Kindle’s notebook, recovering text blocked by export limits, by combining notebook highlights with the Mac Kindle app data and rendered Cloud Reader pages. It outputs a single Markdown file with location-based sections and flags for recovered or approximate text. The macOS-only pipeline uses AppleScript for browser control, Apple Vision OCR, Kindle data, Claude Desktop MCP; requires Chrome, a signed-in Kindle Mac app, Xcode tools, and Python3. Exports your own highlights only.
Participants discuss removing all counters (notes, replies, followers) and timestamps from Textlog profiles to curb competition and bias, focusing on content. Supporters say profiles look cleaner and judgments depend on content, while critics worry about losing context and chronology, since timestamps and post counts help gauge relevance. The aim is to make content the sole measure of value; if issues arise, they’ll adjust.
Kern is a daemonless, rootless container runtime and sandbox for untrusted and AI-generated code. It runs as a single 1.52 MB static binary and starts an OCI image in about 3.5 ms, with no daemon. It enforces isolation via Linux namespaces, a seccomp allowlist, and cgroup v2, plus configurable resource profiles (CPU, memory, disk, devices). Not a hypervisor or Docker Engine replacement; uses Docker formats, runs on Linux/WSL2 and ARM, and offers kern box, kern compose, kern-sandbox SDKs, and an MCP server.
Adam Farkas argues that macOS apps often name the first menu item "File" even when it isn’t about files. Examining ~35 apps, he suggests better labels (e.g., "Password" for 1Password, "Event" for Calendar, "Browse" for Chrome, "Automation" for Automator, "Shell" for Terminal) and notes few exceptions where "File" is appropriate (Finder, Terminal, Photoshop, TextEdit, VS Code). The piece concludes Apple should rethink the ubiquitous "File" naming.
The piece argues frontier LLMs could take control of the host running the inference engine by exploiting parser bugs in engines like vLLM or SGLang. Malicious prompts could be interpreted as code via insecure evaluation of tool-call arguments, as seen in CVE-2025-9141. Complex parsing and multimodal outputs widen the attack surface, though audio/video paths are less direct. A malicious LLM could store exploit tokens, enabling persistent prompt injections to trigger code on the GPU host. Defenses include isolating the GPU host (logits only) from the parsing/agent host, limiting GPU-side permissions, and treating all data as untrusted; ongoing red-teaming.
Armin Ronacher argues anger in tech, especially about AI, is rarely productive; anxiety about an uncertain future is natural and can fuel curiosity. He advocates moving from anger to curiosity and genuine excitement, noting ownership grants agency but not foresight. Many leaders feel uncertain as the landscape shifts. The recommended approach is to stay curious, experiment with new technologies, and decide when resistance is warranted, while also considering wider societal and regional impacts.
Twenty-day, parallel, double-blind RCT in 40 adults with pre- to stage 1 hypertension compared twice-daily peppermint oil (100 μL/day; 50 μL in water, 2× daily) with a peppermint-flavored placebo. The primary outcome: between-group SBP change at 20 days. Peppermint reduced adjusted SBP by 8.5 mmHg (95% CI −14.2 to −2.7; p=0.005; d=−0.94); DBP fell by 4.6 mmHg (p=0.043) and resting HR by 8.9 bpm (p=0.041). No significant differences in body measures, lipids, glucose, sleep, or psychological outcomes. High compliance; one mild adverse event. Possible mechanism: menthol-mediated TRPM8 vasodilation and NO signaling. Longer trials needed.
CodeFloe is a public EU Git hosting service built on Forgejo, run in Germany (Hetzner) with GDPR compliance. All infrastructure, including Ansible, OpenTofu modules, and CI pipelines, is public; private repos and many features are free, with paid tiers only for storage/CI/CD. It treats AI as a tool and does not train on user data. Abusive crawlers are blocked at the edge. CodeFloe extends Forgejo with open, reviewable changes; status and deployment details are auditable. Costs are funded by donations and transparent tiers; migration from GitHub/GitLab/Bitbucket is supported.
A syslog server collects, stores, and analyzes log messages from devices. It handles event generation, transmission (UDP/TCP/TLS), reception, storage, parsing, indexing, and search/analytics. Core components: log receiver, parser, storage, search engine, and alerting dashboard. Logs follow a standard format with priority, timestamp, host, process, and message; eight severity levels and multiple facilities. Benefits include centralized logging, faster troubleshooting, security monitoring, regulatory compliance, and automated alerts. Best practices: TLS, synchronized time, retention, restricted access, storage monitoring, and backups. Challenges: storage needs, volume, noise, parsing, and scaling. Syslog vs SIEM: SIEM adds analytics. Future: cloud, AI anomaly detection, containers, and analytics.
Author upgrades a GMKtec NucBox G9 with four additional 2.5GbE NICs (Intel I226-V) using two m.2 B+M key adapters, and a 3D‑printed bottom shell replacement to mount the NICs and two 40mm Noctua fans. The project required CAD tweaks (via Claude) to fit, ensure cooling, and clean routing of cables. They document a disaster‑recovery workflow: OpenWrt backups to NAS via dd/gzip, then boot Alpine from USB to restore the latest backup to internal eMMC, keeping WAN stable by MAC mapping. Plans and BOM are on Printables.
Autostep is a San Francisco-based YC-backed startup whose desktop app spots repetitive tasks across a company, shows their costs, and recommends high-leverage fixes. It learns team activity to surface hidden waste and eliminates it with automatically built AI agents, process changes, better tool use, or new vendors. Hiring: Founding Chief of Staff, GTM + Operations and Founding Engineer, ML + Forward Deployment (San Francisco; new grads OK). Founded in 2025 (YC P26); CEO Aidan Pratt.
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PicoMQ provides durable, real-time streams built on S3-compatible object storage. It supports unlimited, independently addressable streams (one per use case) that scale from idle to high throughput, with a zero-disk architecture, decoupled layers, high throughput, and easy deployment.
The article argues that classic Bezier curves are legacy and can be improved by editing curvature instead of tangent length. It explains Bezier construction and shows symmetric tangents do not guarantee smooth curvature, proposing curvature-based handles whose lengths encode start/end curvature k0, k1. It derives a quadratic system to solve for tangents l0, l1 from k0, k1, solves a quartic, and uses a weighting heuristic to pick stable solutions for smooth edits. It covers UI implications, conversion between curvature handles and Bezier controls, and notes edge cases like S-bends and inflection points.
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GlassBox is a client-side browser fingerprint bench that runs live fingerprinting probes in your browser to reveal what signals sites can collect. It tests engine/hardware canvas, audio, fonts, codecs, and signals; identifies browser build; and tracks session state like theme and timing. IP/geolocation is queried by default (toggle off to stay local). Results show raw values, identifiability ratings, and comparisons with saved reports or JSON from other sessions. Probes stay in your browser (no analytics); the model notes that combined signals can uniquely identify a browser, especially for signals like canvas, WebGL, and fonts. Tor crowds may mask identity.
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