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  1. August 17, 2026
    1. đź”— crosspoint-reader/crosspoint-reader v1.6.0rc release

      Summary

      This release is mostly bug fixes reported after 1.5.0. A handful of new features rode along too.

      New hardware support

      1.5.0 officially brought in support for our first ESP32S3-based reader — the Seeed reTerminal Sticky. With this release we now officially add support for the X4pro and M5Stack PaperMono devices. Both devices get full frontlight controls, swipe gestures in the reader, and the X4 Pro adds a capacitive Home key with configurable long-press settings.

      Want one? You can order them at crosspointreader.com/devices — that has our affiliate links, and buying from here helps support CrossPoint.

      Transparent sleep screens

      The sleep screen now supports transparent images. Add transparent PNGS and BMPs to your .sleep folder to see nice sleep screen overlays on top of your book pages!

      Reading Night Mode

      You can now toggle on Night Mode in the Reader settings to invert your display. This setting only effects your reader and will therefore flash white at the page refresh interval and revert to white outside of the reader and on your sleep cover.

      For dictionary users

      StarDict .syn synonym lookups are in, and HTML dictionary definitions now render through the EPUB engine instead of raw text — styled entries in dictionary lookups should display correctly now.

      The rest

      An Extra Wide line spacing option. You can now see the password while typing it into Wi-Fi, KOReader, and OPDS fields. Lists and tabs moved onto the new FUI framework.

      What's Changed

      New Contributors

      Full Changelog : v1.5.0...1.6.0rc

    2. đź”— PrimeIntellect-ai/prime-agent Beta (v0.7.2-beta.505.1.114a1d6) release

      Automated beta build from main (114a1d6af4f84c317d1b9080c9c487d20185e57a).

    3. đź”— anthropics/claude-code v2.1.234 release

      What's changed

      • Added the optional CLAUDE_CODE_PROJECT_DIR_NAME environment variable: hosts that give each session its own config directory can choose a short name for the per-project transcript directory
      • Added the selection:clear keybinding action, so a key can be bound to clear an in-app text selection; also works in the agents view
      • Added a GitLab merge request badge to the footer and statusline: repos with a GitLab remote and an authenticated glab CLI show MR !N with draft/pending/green states
      • Claude Code now continues your session automatically when a claude.ai usage limit resets; turn it off in /config ("Continue automatically at usage limit")
      • Claude is now told to use your account email only to identify you, and not to send it to unrelated services unless you ask
      • Security: remote file reads, session restore, CLAUDE.md includes, workflow scripts and file uploads now reject Windows NT-namespace (\??\) paths, hardening the remaining pre-approval file accesses against the NTLM credential-leak vector
      • Fixed auto mode in very long sessions repeatedly re-checking and denying sandboxed commands' network access after the conversation had been compacted
      • Fixed session-scoped permission answers (including denies) being dropped when answering background subagent tool permission prompts
      • Fixed a crash when an API response on the non-streaming fallback path (typically via third-party gateways) contained a thinking block missing its thinking field or a text block missing its text field
      • Fixed markdown rendering becoming extremely slow for some messages containing unusual Unicode sequences
      • Fixed SendMessage rejecting a recipient copied from ListAgents when the session name is at the 200-character cap or emoji-heavy
      • Fixed repository detection mis-reading the host of git remotes with unusual userinfo, producing links and repo-specific behavior for the wrong host
      • Fixed MCP diagnostics printing resolved secrets: scope-conflict warnings now show the configured ${VAR} form, and connection-failure details show only the server origin
      • Fixed strictKnownMarketplaces allowlists accepting SCP-style git marketplace sources whose host differs from the one git would actually connect to
      • Fixed modal text such as the /login OAuth URL losing characters when copied in fullscreen
      • Fixed a --- horizontal rule in rendered markdown running into the line after it
      • Fixed consecutive shell commands splitting into multiple "Ran 1 shell command" rows when todo/task updates were interleaved between them
      • Fixed dialogs like /permissions opened while a ! shell command was running being dismissed when the command finished
      • Fixed a queued ! shell command being sent to the model as plain text after pressing up-arrow to edit the queued input
      • Fixed queued messages reappearing in the prompt history while still queued, Esc while selecting a queued message no longer interrupts the turn, and ! mode no longer sticks after a mid-turn submit
      • Fixed accepting the "Try the new fullscreen renderer?" prompt restarting the session without its permission mode (e.g. --dangerously-skip-permissions), tool allow/deny rules, model or effort flags
      • Fixed /tui dropping launch --allowed-tools/--disallowed-tools rules when it restarts; it now declines to switch, with the reason, when the session has restrictions a restart can't carry over
      • Fixed trust prompts omitting the repository-wide scope warning when the directory was first seen before the repository existed there
      • Fixed a case where an IDE diff tab closing during a permission re-prompt could answer the new prompt with the previous input
      • Fixed: files sent to the user during Remote Control sessions hosted by Claude Code Desktop or VS Code now upload, so they open on phone and web instead of showing an empty card
      • Fixed: after /login while CLAUDE_CODE_OAUTH_TOKEN is set, the stale-token reminder no longer leaks into Claude's automatically resumed turn — it now appears only to you
      • Fixed: permission previews now relay only to channel servers admitted by the inbound trust gate, and a server's explicit permission-capability opt-out is honored
      • Fixed: credential masking on relayed permission previews can no longer hide commands, paths, or destinations from the approver; oversized private-key blocks now redact under full-strength redaction
      • Fixed: provider API tokens that mask on permission previews now mask even when directly followed by shell delimiters
      • Fixed Claude Desktop inter-session messages being silently dropped by the recipient session when cross-session messaging read as disabled, which left the sender's query "thinking" for many minutes
      • Remote Control: signing this computer in to a different claude.ai account or organization now stops the running session within seconds and says why, instead of a misleading HTTP 404 hours later
      • Remote Control sessions started from Claude Code Desktop or VS Code now keep phones and claude.ai/code updated on the session's permission mode (and claude.ai/code on the model) as they change
      • Remote Control: effort picks made on a phone or on claude.ai/code now apply to terminal- and Desktop/VS Code-hosted sessions, and the session publishes its effort level to connected clients
      • SendMessage and ListAgents now say when your account's session list was too long to check completely, instead of treating unseen sessions as absent
      • Expired Anthropic profile credential now points you at /login when a claude.ai login would take precedence
      • Improved the transcript: your own prompts now render markdown (highlighted code blocks, inline code, lists) the same way replies do
      • Improved the "API returned an empty or malformed response" error to say what came back (content type, body kind, size, request ID) and why the original streaming request failed
      • Improved auto-generated session titles to read as short, specific names (e.g. "Login button bug") rather than sentences restating your request (e.g. "Fix the login button on mobile")
      • Reduced the context cost of loading the built-in claude-api skill from ~200k+ tokens to ~25k by loading reference docs on demand
      • /permissions can now be opened while Claude is working — rule changes apply to the rest of the current turn
      • /add-dir <path> can now be used while Claude is working; /add-dir, /autocompact, /theme, /help, /config and /advisor dialogs open mid-turn in the fullscreen TUI
      • /goal now clears itself with a notice when a turn dies on an unrecoverable error (e.g. revoked auth, an exhausted credit balance, or a context overflow) instead of staying armed
      • /goal: when background tasks keep a goal waiting for 30+ minutes, Claude now checks in on them instead of waiting indefinitely (set CLAUDE_CODE_GOAL_CHECKIN_MINUTES=0 to opt out)
      • claude setup-token now rejects unexpected extra arguments instead of silently ignoring them
      • Changed Esc in fullscreen mode to no longer clear a mouse text selection: it interrupts or dismisses as usual and the selection stays highlighted
      • Removed the redundant "Allowed by auto mode classifier" line that auto mode showed under every Agent tool call
      • Removed the "Default teammate model" setting from /config; agent-team teammates now use the leader's model unless the spawn names one
      • Dimmed the elapsed-time counter on the running tool header so it no longer competes with the bold counts
      • Background task notifications delivered between turns are now sent to the model inside <system-reminder> tags, matching mid-turn delivery
      • Mantle: skip the admin-pin availability probe at startup when a main-loop model is already picked
      • Windows: startup no longer stalls on repeated rename retries when ~/.claude.json is read-only
    4. đź”— backnotprop/plannotator v0.27.4 release

      Follow @plannotator on X for updates

      Missed recent releases? Release | Highlights
      ---|---
      v0.27.3 | Folder watcher freeze fix on large repos, first SBOM-attested release pipeline
      v0.27.2 | Mobile plan and code review, Codex CLI 0.147 fix, folder annotate cold-start, configurable markdown extensions
      v0.27.1 | Open-in-editor launch fix, file headers respect Viewed/Git-add visibility toggles
      v0.27.0 | Call Flow analysis, --tailscale remote reviews, review panel remembers your view, Pi rebuild (breaking command rename), focus-mode shortcut
      v0.26.8 | Placed comment markers on HTML pages, shift-click multi-select, live app annotation
      v0.26.7 | Pinpoint targets any element on HTML pages, smarter hover labels, zero-scan hit testing
      v0.26.6 | Fixed empty environment variables in sandboxed sessions (Bun 1.3.14 builds)
      v0.26.5 | HTML pinpoint element annotations, durable annotate submissions, installer fallback for old git, vim HUD cursor fix
      v0.26.4 | Skill-menu hover jitter fix (same-day patch on v0.26.3)
      v0.26.3 | Skill references in comments with / or $, reachable remote session URLs, worktree switcher tooltips
      v0.26.2 | Single-file diff tabs render fully, no more silently dropped review files, light/dark theme pairs, palette-matched code blocks
      v0.26.1 | GitButler 0.22.0 compatibility via capability-probed JSON flags

      What's New in v0.27.4

      A Guided Review can now leave Plannotator. This release ships portable guide exports, share links on guides.show, and a guide CLI any agent can drive, alongside a favicon style switcher, jj support for Call Flow, GitLab artifact fixes in PR review, and a smoother call-flow Lens. Eighteen PRs, four from community contributors, two of them first-timers.

      Portable Guided Reviews and guides.show

      Guided Reviews used to live and die inside your review session. Now a guide has three ways out:

      Download it. Every guide gets a "Download portable guide" button that produces one HTML file containing the full guide and the diff it describes. It opens anywhere, renders exactly like the in-app guide with side-by-side diffs and per-section reviewed checkboxes, and needs no Plannotator install. The file stays small because it carries your content, not the renderer: the viewer loads from guides.show, pinned by filename and cryptographic checksum, so a tampered or wrong viewer never executes. Offline, the file degrades to a readable plain-text version of the guide.

      Share it. "Create share link" uploads the guide to guides.show and hands you a link anyone can open in a browser. Shares are end-to-end encrypted by default: the key lives in the URL fragment after the #, which browsers never send to the server, so guides.show stores bytes it cannot read. You also get a one-time delete token, and "Remove link" works from the same dialog for as long as that Plannotator remembers the share. An optional "Allow link previews" checkbox stores the guide unencrypted so chat apps can show its title; that is a choice, never the default. Setting PLANNOTATOR_SHARE=disabled turns all of this off.

      Author it from anywhere. The new plannotator guide subcommands (list, export, share, unshare) let any agent or script produce and publish a guide from a guide JSON and a patch, without a browser in the loop.

      Saved guides from v0.27.x load unchanged. The share service runs on Cloudflare with add-only, content-hashed viewer publishing and per-IP rate limiting on creation.

      Choose your favicon: Totman or the classic P

      The browser-tab icon is now a setting. Appearance settings offer two styles with visual previews: Totman, the current mascot, and Classic P, the original Plannotator mark restored byte-for-byte from the pre-mascot era. The server remembers your choice and serves it directly, so tabs show the right icon from the first paint without flashing the default. Hosts that embed the published UI packages are unaffected unless they opt in.

      Call Flow analysis on jj repositories

      Call Flow previously required a plain Git checkout. Reviews running on jj (Jujutsu) colocated repos now get the same changed-call-path analysis: the jj snapshot is resolved to the underlying Git objects and fed to the same CallDiff engine, with the same per-file Lens and dock views. Diff collection is untouched; this only extends where the analysis can run.

      GitLab PR artifacts fetch reliably and more safely

      Reviewing GitLab merge requests with uploaded artifacts (screenshots, logs, design files) got a hardening pass. Uploads now fetch through the authenticated API with a strict rewrite that only touches real upload URLs, falls back to the original web route when a self-hosted GitLab predates the API route, maps 401/403 responses to a clear "run glab auth login" hint, and no longer serves HTML or JavaScript content types through the artifact proxy. A regression test pins the invariant that credentials never follow a cross- origin redirect.

      The call-flow Lens stops fighting your scroll

      Community feedback within hours of trying Call Flow in Safari: the per-file Lens popover closed randomly mid-scroll and popped open for every badge that passed under the cursor. Three causes, three fixes: the Lens's internal scroll no longer chains to the page when momentum hits its edge (the chain moved the popup out from under a stationary pointer, which read as a random close and was worst under Safari rubber-banding); hover now has a 100ms intent delay so drive-by badges stay closed; and an in-flight page scroll holds any pending close until the scroll settles.

      Reported by Rustan (@acewhocares on X).

      Additional Changes

      • Touch selection survives the comment composer. On phones and tablets, dragging a multi-line range in a single-file diff no longer collapses the selection when the composer opens; the range you dragged is the range you comment on. #1333
      • Skill picker works with screen readers. The / and $ skill reference menu now exposes real listbox semantics with option roles and active-descendant tracking, so assistive tech announces what Enter will insert, closing #1233. #1316 by @ashish921998
      • Blog: an interactive UI for the grill-me skill. A new post on using /plannotator-last as the review surface for Matt Pocock's grill-me workflow, at plannotator.ai. #1321, #1322, #1323, #1332
      • Security page linked from the site footer. #1305

      Install / Update

      macOS / Linux:

      curl -fsSL https://plannotator.ai/install.sh | bash

      Windows:

      irm https://plannotator.ai/install.ps1 | iex

      Claude Code Plugin: Run /plugin in Claude Code, find plannotator , and click "Update now".

      OpenCode: Clear cache and restart:

      rm -rf ~/.bun/install/cache/@plannotator

      What's Changed

      • fix(comments): expose skill picker semantics to assistive tech by @ashish921998 in #1316
      • feat(review): jj support for Call Flow analysis by @graemefolk in #1312
      • blog: an interactive UI for the grill-me skill by @backnotprop in #1321
      • blog: grill-me post additions by @backnotprop in #1322
      • blog: repo link, image alt text, and larger blog type by @backnotprop in #1323
      • feat: Portable Guided Reviews, export, share links, agent-authored guides, guides.show by @backnotprop in #1324
      • guides-show: GitHub link in the landing page header by @backnotprop in #1327
      • guide-viewer: label agent harnesses in the generated-by line by @backnotprop in #1328
      • guide-viewer: readable on phones and tablets, desktop untouched by @backnotprop in #1329
      • seo: index live root blog pages by @backnotprop in #1332
      • guide: voice rules in the organizer prompt by @backnotprop in #1330
      • docs(marketing): link security page from footer by @backnotprop in #1305
      • fix(review): preserve dragged diff ranges on compact touch before commenting by @backnotprop in #1333
      • feat(ui): Totman/Classic P favicon style switcher by @FNDEVVE in #1325
      • fix(review): GitLab upload artifact fetching via authenticated API with hardened rewrite by @yuensunn in #1228
      • guides-show: example guide screenshot at the bottom of the landing page by @backnotprop in #1336
      • guides-show: example guide screenshot replaces the abstract figure, opens in a lightbox by @backnotprop in #1337
      • fix(review): stop the call-flow Lens closing mid-scroll and opening on drive-by hovers by @backnotprop in #1338

      New Contributors

      Contributors

      Four community authors shipped code in this release, two for the first time:

      • @FNDEVVE built the favicon style switcher in #1325, including restoring the classic P icon exactly as it shipped before the mascot era, and worked through a review round that added server-side icon serving so the choice applies without a flash. Their second contribution.
      • @graemefolk extended Call Flow analysis to jj repositories in #1312, their third contribution to Plannotator's jj support, which they have carried since the original provider landed.
      • @yuensunn fixed GitLab merge request artifacts in #1228, their first contribution, and stuck with it through a security-focused review round on the URL rewrite.
      • @ashish921998 made the skill reference menu real for screen reader users in #1316, their first contribution.
      • Rustan (@acewhocares on X) test-drove Call Flow in Safari and reported the Lens scroll behavior that #1338 fixes, hours after trying the feature.

      Full Changelog : v0.27.3...v0.27.4

    5. đź”— r/LocalLLaMA Artificial Analysis' Qwen3.8-27B benchmarks put it neck and neck with DeepSeek V4 and GPT-5.6 Luna Max rss

      submitted by /u/anderspitman
      [link] [comments]

    6. đź”— @binaryninja@infosec.exchange Seven sidebars was a bit much. Sidekick 26.1 brings Indexes, Notebooks, Code mastodon

      Seven sidebars was a bit much. Sidekick 26.1 brings Indexes, Notebooks, Code Maps, and Repositories together in one Sidekick Resources sidebar! Search across all four from the same place, then open or pin whatever you need right in Binary Ninja. See what else is new in 26.1: https://sidekick.binary.ninja/blog/sidekick-26-1-a-proper-home-for- sidekick/#seven-sidebars-were-too- many

    7. đź”— @malcat@infosec.exchange Did you know that [#Kesakode](https://infosec.exchange/tags/Kesakode) can use mastodon

      Did you know that #Kesakode can use fuzzy-matching for functions? While a bit slower, this kind of lookup helps against obfuscation (here: #vidar)

    8. đź”— r/LocalLLaMA After pushing 1M+ tokens through Qwen 3.8 27B, here is my optimal llama.cpp config for 16GB VRAM (73k Context, Agentic Coding) rss

      After pushing 1M+ tokens through Qwen 3.8 27B, here is my optimal llama.cpp config for 16GB VRAM (73k Context, Agentic Coding) | Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance. Like many of you, I was refreshing the page waiting to download Qwen 3.8 27B the second it dropped. After spending the entire weekend stress-testing it with agentic coding workflows, I managed to run a complete, large-scale project almost entirely autonomously (over 1M total tokens processed , only 3 prompts total). Here is a quick breakdown of the core setup before we dive into the config and workflow details.

      Quick Specs & Params

      • Model: Qwen3.8-27B-UD-Q3_K_XL.gguf
      • Hardware: RTX 5060 Ti (16GB VRAM) + Intel N100 (4C/4T, 16GB RAM)
      • Context Window: 73,728 (73k context) running comfortably in 16GB VRAM!
      • KV Cache Quant: q4_1 for main context, q5_1 for MTP draft context
      • Speculative Decoding: Native MTP enabled (spec-type = draft-mtp, n-max = 2)
      • Sampling: temp = 0.4, top_p = 0.90, top_k = 15, min_p = 0.02

      The Experiment: Building a full API in 3 Prompts

      Instead of running synthetic benchmarks, I put this setup through a real-world software engineering pipeline: building an unofficial REST API and MCP Server for a legacy vBulletin forum.

      1. Prompt 1 (Site Architecture & Analysis): Asked the model to map out the target site. It generated a flawless ~1,500-lines Markdown spec covering structural analysis, scrapable HTML nodes, expected JSON payloads, stack selection, pagination logic, session auth, and search endpoints—far more thorough than I would have written manually.
      2. Prompt 2 (Development Architecture): Using the spec as the single source of truth, it designed a modular NestJS API implementation plan broken into 9 execution phases:
      3. Phase 1: Project Scaffolding
      4. Phase 2: Domain Models
      5. Phase 3: Scraping Core (HTTP + Rate Limiting + Retries)
      6. Phase 4: HTML Parsers (cheerio)
      7. Phase 5: Cache Layer
      8. Phase 6: Application Services + REST API
      9. Phase 7: Authentication (Cookie Sessions)
      10. Phase 8: MCP Server (Primary Deliverable)
      11. Phase 9: Hardening, Docs, & Delivery
      12. Prompt 3 (Autonomous Agentic Execution): The real test. I instructed OpenCode (using Qwen 3.8 27B) to act strictly as an orchestrator, spawning sub-agents for each task phase. It ran autonomously for ~2 hours. When context limits were approached, OpenCode summarized its state and kept building. It wrote unit tests, enforced linting, and delivered fully functional code—only needing one minor automated fix when fed a edge-case raw HTML payload.

      The llama.cpp Configuration File

      Here is my exact --models-preset router configuration file. Note how fit = off is used on the 27B profile alongside ctx-size = 73728 (73k) and q4_1 KV cache quantization to maximize VRAM allocation while preserving native MTP performance. ```ini

      ==============================================================================

      LLAMA.CPP — INFERENCE CONFIGURATION (router mode / --models-preset)

      ==============================================================================

      Hardware Target:

      GPU: 16 GB VRAM (RTX 5060 Ti)

      CPU: Intel N100, 4C/4T (Debian Headless)

      ------------------------------------------------------------------------------

      GLOBAL / BASELINE

      ------------------------------------------------------------------------------

      [*]

      --- CPU THREADING

      Reserve 1 core for OS/services during decode.

      Use all 4 threads during prompt prefill bursts.

      threads = 3 threads-batch = 4

      --- SERVER / CONCURRENCY

      Single slot, disabled continuous batching for maximum single-user

      throughput.

      parallel = 1 cont-batching = 0

      --- GPU / VRAM FIT

      flash-attn = on fit = on

      Safety headroom for VRAM physical limit (MiB).

      Set low (128) because system is headless (100% VRAM available for

      inference).

      NOTE: If using MTP draft KV caches, watch out for double VRAM allocation.

      Bump to 128-256 if you encounter OOMs.

      fit-target = 128

      --- CONTEXT & CACHING

      ctx-size = 65536 context-shift = 1

      Disable context checkpoints (avoids reprocessing issues in hybrid

      architectures)

      ctx-checkpoints = 0

      RAM Prompt Cache (2 GiB)

      cache-ram = 2048

      --- GLOBAL KV CACHE

      cache-type-k = q5_1 cache-type-v = q5_1

      --- PREFILL / BATCHING

      batch-size = 2048 ubatch-size = 1024

      --- DEFAULT SAMPLING (Coding / Precision)

      temp = 0.2 top-p = 0.95 top-k = 20 min-p = 0.0 repeat-penalty = 1.0 presence- penalty = 0.1 frequency-penalty = 0.0

      ------------------------------------------------------------------------------

      QWEN 3.8 27B — REASONING & HEAVY CODING PROFILE

      ------------------------------------------------------------------------------

      [qwen3.8-27b] model = /opt/llama- infrastructure/models/Qwen3.8-27B-UD-Q3_K_XL.gguf

      Disable "fit" to prevent layers from being loaded into the CPU due to an

      automatic calculation error

      fit = off ctx-size = 73728 context-shift = 1

      Native Model MTP (Speculative Decoding)

      spec-type = ngram-mod,draft-mtp spec-draft-n-max = 2

      KV Quantization (q4_1 allows us to fit 73k context in 16GB VRAM)

      cache-type-k = q4_1 cache-type-v = q4_1

      Thinking / Reasoning Budget Params

      chat-template-kwargs = {"preserve_thinking": true, "reasoning_effort":"medium"} reasoning-budget = 5000

      Reduced batch sizes to prevent VRAM spikes during massive prefills

      batch-size = 1024 ubatch-size = 512

      Official / Recommended Quant Sampler Tuning

      temp = 0.4 top-p = 0.90 top-k = 15 min-p = 0.02 ``` submitted by /u/chiribe
      [link] [comments]
      ---|---

    9. đź”— seanmonstar Tending my little plot of the Internet rss

      As many parts of the Internet continue to get worse, I figured it was time to improve my own little plot.

      I mean, I’m always tinkering, making small tweaks regularly. Did you know I keep /now up-to-date? But anyways, a couple changes here felt big enough to write about.

      My microblog is mine

      I’ve been outputting random microposts since… checks archive 2009, apparently. They were “status updates” back then. With Twitter dying, I started doing that sort of thing on Mastodon, and then on BlueSky. Wherever the people want to be, I suppose.

      At first they were just silly jokes. But eventually, besides announcements, they became ways to express raw (bad) ideas and get feedback. But something about that always bugged me: they were on someone else’s property, and linking to them (let alone finding them again) felt bad.

      So, I own my microblog now. They have their own place on this domain. They get a dedicated RSS feed. And they are included in the main feed (currently prefixed as “Micro” so you know). They get syndicated to those other networks automatically as threads.

      What makes them micro? I don’t constrain myself to just 250 characters or anything. They’re so far about 3 paragraphs. That’s about the size, I aim for, I guess. It let’s me publish thoughts without blocker energy telling me I need to polish it into an essay. It also allows me to output 1 or 2 a week. Or none.

      And I can link to them and build on them. Mine!

      Subscribe via email

      I have improved the subscribe via email option of this site.

      For a long time, “subscribe via email” was easy and nice, provided by Feedburner. When that service was shutdown, I looked for an alternative. Something that was both free and automatically just worked from an RSS feed.

      I’m sorry about that. I picked something horrible, a service I don’t want to provide any further attention. They inject gross click-baity ads inside the emails. I subscribe to myself, and after being repulsed at the last email, I had to fix it.

      I couldn’t find any other service that automatically works from RSS for free. I could pay for a service, but I don’t need to send that much email. And I’m doing this as a convenience, to let users read how they want, not as a business. It’s not a newsletter.1

      So I imported that list to Buttondown. I can copy-paste the markdown of blog posts manually. That’s fine, I don’t write so often to need it to be automated.

      But since it is manual, I can do more. I can also include a list of “recent microblog posts”, now that I own them.

      Anyways, back to continual tinkerage.2

      1. And there’s no way I could subject my readers to Substack or Medium or something. Those sites do not treat readers well. I automatically refuse to read any article on such a site. I assume that if you don’t care about my reading experience, I don’t care enough about your idea. Not sorry. ↩

      2. Other things I want to improve: a combined blog and micro archive. A tags page. A better chronological story for About. A set of “values” pages. ↩

    10. đź”— r/LocalLLaMA Stripe will reportedly acquire AI gateway startup OpenRouter for $7B+ rss

      another one ..

      submitted by /u/ab2377
      [link] [comments]

    11. 🔗 r/LocalLLaMA …and I’m not afraid of losing my social credits. rss

      …and I’m not afraid of losing my social credits. | submitted by /u/JLeonsarmiento
      [link] [comments]
      ---|---

    12. đź”— WerWolv/ImHex Nightly Builds release

      Nightly

      242416b Changelog

      • fix: Broken AES Modes in data processor (#2831)
      • fix: Documentation links
      • build: Try to get MSVC vcpkg cache working
      • fix: MSVC build
      • fix: Preserve custom encoding row cache boundaries (#2846)
      • impr: Replace all mentions of provider IDs with their names
      • feat: Add option to reopen an unavailable data source with a different source
      • fix: Wrong project icon in recent files menu
      • impr: Remember which providers were open in project
      • fix: Set cursor position explicitly before jumping to the selection in paste from source feature (#2833)
      • fix: Remove duplicated scroll bar from sidebar
      • fix: Move a bunch of project strings into localization
      • fix: Remove pattern source sync option as it serves no purpose anymore
      • impr: Auto create project folder during import
  2. August 16, 2026
    1. đź”— smol-machines/smolvm smolvm v1.8.3 release

      What's Changed

      • Give every pack-export read the same ceiling instead of two that disagree by @Bnjoroge1 in #959
      • Provide a default /etc/hosts when the image ships none by @BinSquare in #962
      • Resolve host.smolvm.internal to the gateway address by @BinSquare in #963
      • Roll back checkpoints after clone identity failures by @depombo in #967
      • Fix(network): forward guest TCP FIN to remote peer in virtio-net relay by @Vishv07 in #961
      • Named inter-VM networks with routed addressing between machines by @BinSquare in #964
      • Bump the workspace to 1.8.3 by @BinSquare in #968

      New Contributors

      Full Changelog : v1.8.2...v1.8.3

    2. đź”— Simon Willison Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things rss

      Friday's big release was Qwen 3.8 27B, an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba's Qwen research lab. I've been looking forward to this one: 27B is an excellent size for running a model on a reasonably specced laptop, and its predecessor Qwen 3.6 27B was impressive.

      Qwen's self-reported benchmarks for this model are eye-opening. They show a boost from both Qwen 3.6 27B and the closed-weight Qwen 3.7-Plus, which was one of Qwen's strongest models of any size as recently as May this year. It will be interesting to hear what independent benchmarks have to say about the model.

      I've been running the model on two different machines: my 128GB M5 Max MacBook Pro, and an NVIDIA DGX Spark. On both machines I'm running LM Studio and their 17GB Q4_K_M quantized build. I also tried using llama-server directly on the Spark.

      The default of extra high results in spectacular over-thinking

      Qwen's documentation describes the model as defaulting to xhigh for the reasoning effort, and the LM Studio GGUF I've been trying preserves that default:

      Qwen3.8 comes with official support for reasoning_effort, which can be used to adjust reasoning depth and control cost:

      • xhigh (default): for complex tasks demanding thorough analysis
      • medium: balancing accuracy and speed
      • low: efficient reasoning optimizing for speed and cost

      This is a hilarious default. It's absolutely not a good way to run the model, especially on consumer hardware. I've been finding the results extremely entertaining.

      I quickly ran into problems with LM Studio's default context limit of 8,192 tokens - Qwen was using them all up thinking about even the most mundane of problems. I loaded the model with the full 262,144 maximum context length and that problem went away.

      Here's the pelican riding a bicycle SVG I got from my first attempt with that increased context length. It took 21 minutes to generate, using 22,276 reasoning tokens to produce 3,223 tokens of output. You can read the reasoning trace here.

      A very pleasing image of a pelican riding a bicycle. The bicycle is red and has the correct frame shape. The pelican looks like a pelican and has its wing extended to the handlebars.

      This is by far the best pelican SVG I've been able to generate with a model that runs on a local machine - and this Qwen is pretty small, just a 17GB file on disk. There's a lot to like about this:

      1. The bicycle frame is the right shape
      2. It has legs on each side of the bike - that's very rare
      3. Good, clear pelican pouch
      4. The wings extend to touch the handlebars!
      5. The motion lines are behind, not in front
      6. It has a tasteful background - nice sun, clouds, hill, flowers and grass.

      Was that worth waiting 21 minutes for? Absolutely not.

      Here's that same prompt run with reasoning turned off - transcript here. This one produced 3,715 tokens and took 137s - just over two minutes.

      The bicycle frame is a bad shape now. The pelican remains recognizable but has a less obvious pouch. The feet miss the pedal, there is no attempt to hold the handlebars. And just for completeness, I used OpenRouter to run the same prompt through the much larger Qwen 3.8 2.4T-A95B (released last week) and got this snazzy animated SVG:

      I said Qwen at xhigh has a tendency to over-think things, but how bad really is it?

      I tried a much simpler prompt, again with that default extra high setting:

      draw an svg of a circle

      Qwen's reasoning trace started like this:

      The user is asking for an SVG drawing of a circle. Simple request — but I want it to be a carefully crafted piece. Let me make something that goes beyond just <circle>: a single self-contained SVG file with character — maybe a geometric "circle study," with subtle animation, layered rings, and a distinctive palette.

      Keep the scope right: they asked for an SVG of a circle. So the core is a circle. But I can add craft: concentric guide circles (like a compass/geometry drawing), tick marks, a soft gradient fill on the main circle, restrained ambient motion (a slowly rotating dashed ring, pulsing glow). Respect prefers-reduced-motion? That's more for CSS; SVG SMIL or CSS inside SVG will do.

      Palette options: deep teal ink on warm paper? Or bold vermilion circle on off-white with navy construction lines — Bauhaus/compass-drawing vibe. Let me go with a "geometric study" look: cool slate background, or bright paper white? Paper white is fine if it's not the cream-and-terracotta combo. [...]

      Several minutes later it produced this absolutely beautiful animated circle, which was entirely not what I had asked for!

      My strong recommendation: ignore that default. Run Qwen 3.8 27B on low or even no reasoning levels at first. It's a great model, but wow that default setting is a bad place to start.

      It's very good at bounding boxes

      A fun way to test a vision model is to see how well it can return bounding boxes around items in a photograph. I've seen previous Qwen models deal well with this, so I decided to put it to the test drawing bounding boxes around some pelicans.

      I've seen asking for 0-1000 scale produce good results in the past. I tried this:

      llm -a https://static.inaturalist.org/photos/714731804/large.jpg \
  -m lmstudio/qwen/qwen3.8-27b \
  'Return JSON bounding boxes for the pelicans in this photo, 0-1000 scale for each dimension'

      Here's the reasoning trace, which produced this:

      [
  {"bbox_2d": [195, 290, 370, 780], "label": "pelicans"},
  {"bbox_2d": [445, 320, 675, 850], "label": "pelicans"}
]

      This is such a good match. Here are those boxes rendered on top of the photo:

      A photograph of two pelicans on a rocky outcrop, with three other smaller birds. The pelicans both have bounding boxes exactly surrounding them, each with a label that says pelican.

      Building a tool to label bounding boxes

      That visualization of the bounding boxes was taken using a new custom tool that I had Qwen 3.8 27B build for me, running offline on my laptop.

      I forgot to dial down the thinking effort so it was massively over-engineered, but it did manage to produce this full interface from this single prompt:

      [
   {"bbox_2d": [195, 290, 370, 780], "label": "pelicans"},
   {"bbox_2d": [445, 320, 675, 850], "label": "pelicans"}
]

      Build an HTML page which has an input box for accepting the URL to an image and a textarea for accepting the above style of JSON.

      It appends the image to the page, measures its width and height, then treats the coords in the bbox_2d as scaled from 0-1000 and scales them against the actual width and height, then it renders labelled boxes over the image.

      This screenshot shows one of the features I did not ask for - a demo scene, for if you don't have a photograph to test the tool with:

      Screenshot of bbox·lab, a dark-themed web tool that overlays object-detection bounding boxes on an image, with an input panel on the left and a stage on the right showing two labeled boxes around stylized pelicans in a sunset illustration. Header: bbox·lab — normalized 0–1000 coords → pixel overlay; status indicator: RENDERED · 2 BOXES. Panel 01 INPUT (URL + detections) contains an IMAGE URL field reading data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA+, a DETECTIONS — JSON textarea reading {"bbox_2d": 195, 290, 370, 780, "label": "pelicans"}, {"bbox_2d": 445, 320, 675, 850, "label": "pelicans"} , an orange RENDER BOXES button, and dashed boxes labeled DEMO SCENE and CLEAR. Panel 03 STAGE header: display 661 × 661 px · 1 unit = 0.661px x 0.661px · nat 1000×1000. The stage shows a flat-style illustration of two dark pelican silhouettes with orange beaks standing in calm water against an orange-to-purple sunset sky with a pale yellow sun and distant birds; an orange bounding box labeled 1 · pelicans surrounds the left pelican and a cyan bounding box labeled 2 · pelicans surrounds the right pelican. Footer: move the cursor over the image to read grid coords; boxes map 0–1000 → displayed px.

      Here's the relevant segment of the thinking trace, where it decided to draw its own pelicans purely because I had used the label "pelicans" in the example JSON I gave it in the prompt:

      Also a "load sample" that uses a known image? Can't depend on external images, but… the image URL input is user-provided; I could add a "try with sample" button [...] Hmm, I can draw a simple scene on canvas, export it as a data URL, and load it into the image — that's self-contained and demo-able! [...] But the user's coords are for an actual pelican image; a generated placeholder can still demo the scaling. Generate a 1000x1000 placeholder: gradient water + two blob-like "pelican" silhouettes placed at the given bboxes (using the same scale — cute: silhouettes at the exact 0-1000 positions, showing the boxes align). This makes for a fun, self-contained demo. Keep it simple: sky gradient, sun, water, two pelican-ish shapes (ellipse body, circle head, beak). Place at bbox centers.

      (I'm slightly nervous that models around the world might have a bias towards drawing pelicans at any chance they can get, brought on by nearly two years of exposure to my own stupid benchmark.)

      Is all that over-thinking necessary? Maybe it is, at least a bit. I tried with reasoning turned off and got this version, (transcript here), which nearly works but shows the boxes in the wrong place:

      BBox Studio screenshot - a solid UI but the yellow and green boxes do not cover the pelicans.

      So without reasoning it didn't quite one-shot a working tool. I'm sure it could get there with some follow-up prompts, but this is a good example of how reasoning can make a difference.

      Yes, it can drive coding agents

      One of the biggest questions around local models is whether or not they have enough horsepower to successfully run a coding agent loop. Coding agents require long context, strong code generation support and reliable tool-calling. On paper Qwen 3.8 27B has all three of these, so is it up to the task?

      My initial experiments with Pi have been very promising. I chose Pi because it has a shorter system prompt than most other options, making it a better fit for trying out smaller models.

      I configured Pi to use Qwen 3.8 27B running in LM Studio on the Spark (shared via tailscale serve) by adding this to ~/.pi/agent/models.json:

      {
  "providers": {
    "spark": {
      "baseUrl": "https://spark-18b3.tail68a31.ts.net/v1",
      "api": "openai-responses",
      "apiKey": "dummy",
      "models": [
        {
          "id": "qwen3.8-27b",
          "reasoning": true
        }
      ]
    }
  }
}

      Then ran pi --provider spark --model qwen3.8-27b in my ~/dev/datasette folder and prompted:

      how does auth work?

      After a sequence of reasoning and tool calls that accessed a bunch of different files it produced this reply, which is very solid.

      Just one problem: I wanted to share that transcript. So I pointed Pi and Qwen 3.8 27B at the JSONL transcript file in ~/.pi/agent/sessions/--Users-simon-Dropbox-dev-datasette-- and prompted:

      Write Python code to convert this jsonl to markdown

      And it built and tested this pi_jsonl_to_md.py, which did exactly what I needed. Here's that session transcript, published using the tool that it created.

      The quest for speed

      So far this is all looking very promising. We have a 17GB model that runs on high-end consumer hardware and can write code, drive tools, annotate images and generally do everything that I need from an LLM for getting real work done.

      There's one very significant catch: it feels slow - especially when it starts over-thinking, but even without that it's not particularly sprightly.

      I've been getting around 15-30 tokens a second from LM Studio. That's not terrible, but it's slow enough that it's going to be hard to win me away from hosted API models, which can return results a whole lot faster. Artificial Analysis track token speed and show OpenAI 5.6 Sol at 74 tokens/second and 5.6 Luna at an impressive 184/second.

      The good news is that the community have been exploring ways to speed things up since the model was first released two days ago.

      One of the most promising optimizations is baked into the model itself. Qwen supports Multi-Token Prediction, an architecture trick where a cheaper mechanism guesses several tokens ahead and the main model can then quickly verify if the guesses were correct. This can have quite a dramatic effect on inference performance.

      Based on this tweet from llama.cpp creator Georgi Gerganov I tried running the model with MTP like this on the Spark:

      llama serve \
 -hf  ggml-org/Qwen3.8-27B-GGUF:Q4_K_M \
 -hfd ggml-org/Qwen3.8-27B-GGUF:Q4_0 \
 --spec-default \
 --spec-type draft-mtp \
 --reasoning-preserve

      And sure enough, this gave me a significant boost. I had GPT-5.6 in Codex run a comparative benchmark on the Spark and the --spec-type draft-mtp server outperformed the LM Studio default GGUF by around 72%.

      I expect we'll see a whole lot more innovation around serving this model faster over the next few weeks. The MLX community likely have some tricks brewing as well.

      Some observations

      The fact that a 17GB file can do all of this stuff on my home machines is a miracle. Once again, I'm delighted and amazed at how much progress local models have made this year. A year ago this would have been competitive with the best and most expensive of the proprietary models - today it can run on a capable laptop.

      The only thing holding this back from being a daily driver is performance. It feels pretty slow on both the M5 Mac and the DGX Spark. That's the catch with these dense (non-Mixture-of-Experts) models - they require a whole lot of memory bandwidth to perform well, and neither of the machines I have access to are top performers in that regard.

      The most important thing about Qwen 3.8 27B is what it demonstrates. We can have an open weights general purpose model with a long context, effective tool calling, strong vision ability, and competent code generation, and we can fit the whole thing in just a 17GB file.

      The models at this size continue to get better at an impressive rate. We don't need to spend half a million dollars on datacenter-class hardware just to run a competent model.

      You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options.

    3. đź”— modem-dev/hunk v0.19.0 release

      What's Changed

      hunk-v0.19.0-launch.mp4

      Highlights

      • Install shared extensions from Git, build docked panes and session keyboard modes, and use Hunk's bundled extension-authoring skill by @benvinegar and @mikeclarke in #697, #708, #710, #712, and #717.
      • Guide reviewers to exact code with line navigation and contrast-safe character-range highlights for extensions and live agent sessions by @elucid in #726, #727, and #728.
      • Keep large reviews responsive with in-process untracked-file diffs, active-review syntax caches, and experimental worker highlighting by @benvinegar in #738, #754, and #759.
      • Control the workspace more precisely with configurable files-pane visibility and independent extension panes by @skaragianis and @tridha643 in #648 and #757.
      • Verify release archives with GitHub build-provenance attestations and install Hunk through mise across macOS, Linux, and Windows by @elucid in #714 and #777.

      Full Changelog : v0.18.2...v0.19.0

    4. đź”— HexRaysSA/plugin-repository commits sync repo: +1 plugin, +1 release rss 
      sync repo: +1 plugin, +1 release

## New plugins
- [climacros](https://github.com/allthingsida/climacros) (1.0.5)
    5. 🔗 r/LocalLLaMA Let’s all thank Georgi Gerganov who gave use llama.cpp rss

      Let’s all thank Georgi Gerganov who gave use llama.cpp | I was looking into the story a bit further earlier. Very interesting. Couldn’t have done it without him submitted by /u/on_line187
      [link] [comments]
      ---|---

    6. đź”— Register Spill Joy & Curiosity #95 rss

      In the last two weeks I've shipped: a new experimental provider backend for our orbs, an in-product bug reporting feature (not released yet) including an admin area where we can triage bugs, disk and memory warnings for orbs, visible setup logs when orbs are starting, a full Comet Busters-like game that's hidden as an easter egg on our website, a microphone selector for our dictation features, a new work-in-progress page that explains what orbs are that has a bunch of handwritten text and videos and other stuff I put in there by hand, user preferences for themes, and a few smaller things.

      I also fixed around twenty bugs and removed 5k lines of code that we no longer need.

      "We get it, man, you shippe--"

      Nah, nah, nah! Not the point. The point is this:

      I have not used my local development environment for any of this. I've done all of this remotely, using Amp, in orbs. Everything! Backend for remote machines; messages sent across three services to warn about system resources; landingpage. The freaking game is probably the least surprising thing here, isn't it? And it's a game with custom assets!

      Isn't this wild? No, I know, it is, that's what I'm saying.

      "Surely some things you want to check or test locally, no?" Nah, not really. I mean, yes, that's probably what I would've said half a year ago if you'd told me I won't need my local dev setup anymore.

      Turns out that, no, you don't. You can just ask the agent to give you "irrefutable proof" that something works and if you have an orb and it can do whatever it wants and install whatever it needs it will find a way to give you that proof. Orbs are malleable, the agent can shape them to fit the task by installing and running whatever it needs and and then you get a bespoke made-for-exactly- this-task machine in which an agent can go crazy and if you ask it it will give you a presentation or a narrated video in which it shows by -- frame-by- frame, man! -- that the race condition has been fixed.

      And then, what else do you need your local dev env for? Editing code by hand? Come on, man. Reviewing code deeply? Amp has a diff viewer, so you don't need to do that locally either. And for all of the things I shipped here, I didn't review each line anyway. I do spot checks and make sure the architecture is right, yes, but do I need local tools for that? No. You can ask the agent to help you with reviewing by quizzing you, by giving you diagrams, by showing you a presentation.

      What about the fiddly things? The things you do want to feel your way towards, with your hands? Little bit of padding here, some margin there; now let me flip these two paragraphs and-- ah yes, better. That kind of stuff? That's actually where I'm now experimenting the most because I do have this need to flip words and paragraphs and move stuff around. I want to look at it, change something, look again; undo, redo, change, undo, and back around again.

      But here too the game has changed in a way I find marvelous. Because you can just dictation-dump all your ideas to the agent and hand it screenshots and assets and raw notes and snippets and then ask it to provide you with example pages and 15 different variations of the widget you're interested in, and then you can tweak those and say "this one's good, let's use this one" and you feel like you're the head chef strolling through the kitchen, spoon in hand, tasting the soup over here, tasting the dessert over there, saying "nah" or "mmmmh, good" or "into the trash", and your headless and faceless and bodyless sous-chefs don't mind at all and just do what you say and try again.

      Then weeks go by and you notice you haven't git pulled in a long time and every time you do end up doing that again (due to nostalgia?) maybe use more than one checkout, you notice that it starts to feel… yucky? dirty? unclean?

      Wild times. Exciting times. The models are there now. And if you doubt that, just wait a couple months.

      • New episode of Raising An Agent is out! We recorded this one in-person, in Munich, and talked about everything that was on our mind last week (and this week): orbs, jellyware, why AI by itself doesn't lead to slop, how you need to rethink software now, and, maybe most importantly, the mind-blowing realization of that week in Munich, that no one cares about their local dev env anymore. We all had to wipe our laptops four weeks ago and people said they still haven't ported their dotfiles over and at this point don't care anymore.

      • Speaking of which: I recorded a short video on why orbs aren't "just VMs" and why saying "orbs are just VMs" is missing the mark, just like saying "the cloud is just another person's computer". Also: woo boy, some people are really bothered by product names? Well, too late. It's orbin' time. I get emails from customers telling me they want to get their team "into orbit", others signing off with "happy orbin'!", and customers greeting us in Slack channels with "I love me some orbin' in the mornin'."

      • My teammate Will wrote about how we can push straight to main and still have SOC2. One of the most asked questions we got in the last few months: "Wait, you don't use pull requests? How do you have SOC2 then?" Turns out that SOC2 doesn't require PRs.

      • Very short video in which I show off how I iterate with agents in orbs, working on landingpages and making visual changes, something.

      • Stolen Thoughts - Stealing Reasoning Traces from Proprietary LLM APIs. First of all: wow, what a name, what a website. And then, of course, this is fascinating, isn't it? But I'm not sure whether it's much more than that.

      • Wired also has a write-up on it: A New Trick Reveals AI Models' Inner Thoughts.

      • Read Austin Kleon's Don't Call It Art. Lovely, as expected. If you're in any way interesting in making things or building or writing or just … doing stuff on the Internet: get all of his books. They're very short but very good and very inspiring.

      • It's been a while since I've wanted to access to something this badly: "Cerebras powers GPT-5.6 Sol on Ultrafast mode, delivering up to 750 output tokens per second." Hey, tell the kids to cup their ears real quick. Motherfucking seven hundred and fifty tokens per second. Fucking hell! If there's a sweet angel at OpenAI reading this and can give me access: I will fly to San Francisco and hold your hands and kiss your forehand before I kneel down to thank you and to bless your family and the house they live in and the ground they walk on.

      • Zuckerberg weighs in: "I do not understand why anyone who believes that AI will eliminate most jobs and much of humanity's relevance would rush to build that future." (No, I have not read the whole thing.)

      • The hardest working font in Manhattan. This was long, but soooo good. So good. On a spectrum from "doesn't care about to fonts" on the left to "writes a long and deeply researched article about the history of an unknown font" I'm slightly to the right of center, but I read the whole thing and think you should too if you ever thought "that's a neat font." (Except if that font was Papyrus, of course.)

      • Nail it to the walls: There are no lossless transformations of natural-language text. Very, very, very good. (Sidenote: can you imagine working at a 1000 people org and people use AI to generate Slack messages, emails, PRDs, and slide shows? Yup. Horror stories between two parens.)

      • Craig Mod: A Swarm of Blood Robots. Insert the usual adjectives that I use when talking about Craig Mod's writing: excellent, fantastic, lovely, beautiful. They all apply here too. There are so many things I want to quote here: the section about writing with LLMs, the part about the Weirdness, some of his example projects, the end about the usefulness of these tools. But instead let me just share this one observation: maybe my views on the future of software are so aligned with Craig's (if you go back and read the last twenty issues of this newsletter you'll find that my thoughts on liquid software, jellyware, the future of software, etc. match what he's describing here) because Craig is not part of the software industry and he's not huffing and puffing about how things aren't done properly and he's not stomping his feet about these models being bad at X and Y and he's not stuck in a ten-year old world view of how software's supposed to be built and instead he just has a ton of ideas for things to build and leans into seeing what these models can do and then goes and does it.

      • Sudo Aquarelle, a watercolor simulator. So nice.

      • Finally an end to this stupid argument: "Code was never the hard part" is an insult to all programmers.

      • There is No "Done": Reflections on a Completed AT Thru-Hike. This was great, saying that as someone who's dreamt of walking the AT since he read A Walk in the Woods many, many years ago.

      • I didn't know that the Apple TV has color calibration via iPhone.

      • One of the most beautiful things I've come across this week: Ordinary Abundance. "All the items in this room were once out of reach; some not yet invented, others too rare or costly for the vast majority of people. Today, most of us lucky enough to live with them walk past without a second thought." We'd all probably do well by scrolling through it once a week.

      • Are you a hardcore Rust engineer and want to work remotely with a small and equally hardcore team and do systems- and infrastructure programming? Look no further. I highly recommend working with Nathan and Nick.

      • The Antithesis Principle. This was fascinating. I failed to apply it to every example and got different answers, which makes me think that either (a) the principle is not that clearly defined (possible) or (more likely) that (b) my brain's not wired in this way and I could probably benefit from rewiring it a bit.

      • OpenAI has a friction@ email address employees can use if they feel like they're being blocked.

      • My wife and I were talking about Dolly Parton this week and I said, "Have you ever seen her when she was younger? Or heard her talk?" She said, "No, I haven't." I immediately pulled out my phone and showed her this video.

      • Reminds me: I fell off the wagon again and have watched this video five times in the last 24hrs and I'm about to watch it again, so here, you watch it too. It's only one of the greatest things ever recorded. Danny Carey performing Pneuma.

      • "My dad used to tell me that you could yell at a bear and it would go away. Camping when I was 10, a bear came into the site. Dad got out of the tent and yelled at it, and it just snorted back at him. Dad got back into the tent. 'That's all I got.' A lot of life is like this."

      You should subscribe and tell your friends about this newsletter too, because I know you love it and you keep telling me, but I need the numbers to go up, for the shareholders (and the board):

    7. đź”— smol-machines/smolvm smolvm v1.8.2 release

      What's Changed

      • Spawn VM boot subprocesses via /proc/self/exe on Linux so a binary replaced under a running serve cannot make every subsequent boot fail by @BinSquare in #945
      • chore(nix): bump flake to 1.8.1 by @BinSquare in #940
      • Bump the workspace to 1.8.2 by @BinSquare in #946

      Full Changelog : v1.8.1...v1.8.2

    8. đź”— r/LocalLLaMA Qwen3.8-27B vs Qwen3.6-27B writing ray-tracers in BASIC rss

      Qwen3.8-27B vs Qwen3.6-27B writing ray-tracers in BASIC | one of my llm hobbies is re-creating graphics demos i used to write in BASIC in the late 1980s. i slopped together an agentic harness and a basic-to-js transpiler in a web page i've been playing with for a few months. the agent can write basic programs, run them, examine the resulting images, and iterate. qwen3.6 could do a ray-tracer with some user input -- often it got something wrong that it couldn't see/didn't notice, and hence wouldn't fix without further prompting. qwen3.8 typically knocks it out of the park on its own, iterating to a good result. both models are running the unsloth UD-Q8_K_XL quants. i'm pretty happy with 3.8 so far. the user prompt was "write a recursive ray-tracing demo to render three metallic spheres (copper, silver, gold) over a glossy checkerboard plane and under a deep blue sky. use the cook-torrance model to render the spheres." submitted by /u/Ok-Breakfast1878
      [link] [comments]
      ---|---

  3. August 15, 2026
    1. đź”— IDA Plugin Updates IDA Plugin Updates on 2026-08-15 rss

      IDA Plugin Updates on 2026-08-15

      New Releases:

      Activity:

    2. đź”— HexRaysSA/plugin-repository commits sync repo: +1 release rss 
      sync repo: +1 release

## New releases
- [IDA-MCP](https://github.com/captain-ai-hub/ida-mcp): 0.8.1
    3. đź”— r/LocalLLaMA If you would have told me half a year ago that a local model running in my office would be able to one-shot a Super Mario clone, I would have called you nuts. Qwen3.8-27B is a different beast. rss

      If you would have told me half a year ago that a local model running in my office would be able to one-shot a Super Mario clone, I would have called you nuts. Qwen3.8-27B is a different beast. | Running the Q8 GGUF on my Framework Desktop is not fast, but it's extremely smart for overnight batches and background jobs. Can't wait to play around with MTP and other quants. Have any of you found ways to improve speed while keeping accuracy? https://mikeveerman.github.io/qwen38-27b-mario Edit: to avoid copyright issues and to see how creative it would get, I asked Qwen3.8 to make it circus-themed instead of Mario-themed. It's technically no longer a one-shot. submitted by /u/MikeNonect
      [link] [comments]
      ---|---

    4. đź”— r/LocalLLaMA Aged like fine wine rss

      Aged like fine wine | submitted by /u/TigleLive
      [link] [comments]
      ---|---

    5. đź”— r/LocalLLaMA Qwen 3.8 35BA3B spotted rss

      Qwen 3.8 35BA3B spotted | https://preview.redd.it/xwbkbbj55ijh1.png?width=1554&format=png&auto=webp&s=abd354c8a6bef033d5fb8383c49e4a682ab22105 Just wait and see https://github.com/modelscope/ms-swift/commit/ab726e9d445a6520a70df2c831177d46adb1f589 submitted by /u/BazzyIm
      [link] [comments]
      ---|---

    6. đź”— r/LocalLLaMA Qwen 3.8 - 27B is a game changer rss

      So a bit of context, I am a cybersecurity senior analyst
      I am interested in LLMs for that field especially with MCPs to connect them to the tools or for writing scripts

      I started this field by doing assembly language reading for hacking games when I was a teenager then that became malware analysis then I started to analyze traffic and logs at work for a living
      Before work I competed in cybersecurity competitions known as capture the flag to solve only one category of the challenges and that is malware analysis

      Now here is the scene in LLM x Cybersecurity

      Entry-level CTF challenges (I used to solve around 2017-2018, got first job in 2019) were solved and saturated by LLMs a long time ago (See intercode CTF benchmark)

      Then High level CTFs (NYU CTF Bench, CSAW challenges, and CyBench) these were solved a while ago

      Today we have
      CyberGym (vulnerability description (CVE report not real details) plus code base find vulnerability
      That was solved

      Then ExploitGym (the one recent OpenAI model escaped and hacked hugging face to find solution, the 2 vulnerabilities themselves are trivial (JWT spoofing with no server side checks for Jfrog sandbox and JS + Python template in open source data viewer of Hugging face)
      Still impressive for a fully autonomous model

      ExploitGym gives vulnerability details + exploit technique/details and codebase (I wonder how/why OpenAI model escaped it in the first place those details should manage it this is why I feel it is staged but whatever right)

      ExploitBench
      More realistic threat vector
      1-day not 0-day (0-day is a novel vulnerability no one else knows about it hence the name, 1-day is a known vulnerability patched, if in an open source project you can compare patches before and after and know it but not as valuable as 0-day since people will/should update their software, 0-days can and are used against high profile targets like in some 3rd world countries used for surveillance (and possibly non-3rd world countries ?!) but you usually can’t use a 1-day for that but still)

      So ExploitBench is 1-days in V8 engine (used in chrome, electron vs code almost everything!!)

      Gives the model a patch diff and codebase base that is it

      Models are going wild on ExploitBench and ExploitGym but haven’t gotten there yet at the moment and only recent frontier models improved massively instead of near zero across the board

      This is a massive risk indicator
      Imagine models capable of exploiting any and every piece of software written by less capable people or other weaker LLMs (complex vulnerabilities!)

      Not only that but global elite CTFs like DEF CON

      You have an OpenSage harness (and ADK like Google adk or Anthropic adk, however this OpenSage ADK asks the model to design its own agent/s!, with whatever tools or sandbox environments it finds fitting for the Subagent to do the assigned subtask effectively, it can even design its own MCPs!, models don’t fully utilize that yet but some do and improved form like 39% to ~60% just by using that harness (same model!) )

      1. Now my own benchmarks are simple

      Some malware samples that I learned during my career and consider personal milestones

      And one SIEM analysis challenge (logs that contains an attack plus normal behavior)

      I tests on lots of models (Qwen3.6, heavily trimmed down Minimax 2.5 …etc, on my Strix halo and compared with opus at the time (the best opus at the time was 4.5!, it was better solved major stuff but didn’t implement the code required to decompose the malware and analyze its second stage)

      Now enter Qwen 3.8 27b
      3.
      What was SOTA like 6 months ago or around beginning of this year
      Now we have better local models at the same task

      Qwen 3.8 devoured the malware that Opus couldn’t

      I had some time analyzing and remembering its custom implementation (it has custom RC4 decryption routine, that is tricky with string manipulation!
      And Strix halo isn’t the fastest LLM machine

      By the time I remembered that malware and how it works

      Qwen had already extracted and disassembled the decrypted payload!

      I am stunned

      This is super dangerous

      I imagine how a single person / threat actor can now do what a state-sponsored intelligence service shacking team was required to do 1 year ago

      These teams usually have

      1. Usual network scanning or mapping especially of their targets
        This can be easily done by even weaker models or no models at all

      2. Initial access operations (phishing campaigns until some clicks or attempting to profile people like receptionist or sales people or HR, essentially any first line of communication at an organization or a company, to later make a targeted phishing against them)

      This could be also better done with the aid of deep fakes and other stuff

      1. Advanced and resourced teams would have zero-day or 1-day research teams
        Especially against software used on the targets site from team 1

      This third step can be fully automated with models now
      This is the hardest step

      Defenders can use LLMs but it is much harder to integrate new tools than offensive teams

      At this level the world will change
      Tbh I always thought cybersecurity was harder to automate with LLMs than software engineering or IT
      But with this, this is super unbelievable

      And not only a cloud model or an expensive to run locally model
      A local model! Can you believe it
      No traces no API calls no nothing

      Empowered with the right environment setup and tools and it can do what teams of attackers or malware analysts were needed to do

      Btw for malware analysis I give it Ghidra and a sandbox with python (it can use pefile or capstone or whatever it needs and it does use them!)

      And also recently I added a Vbox with Vbox MCP and a debugger inside that box with another MCP for the LLM to control both (snapshot restore functionality and debugger functionality)

      These tasks were hard and not every security analyst was a malware analyst
      Even malware analysis positions are very rare and technical and don’t pay well because not much needed (I used to starts at assembly in assembly debuggers for nights at times!)

      This is going above and beyond

      Anyone had similar moments in cybersecurity or anything else ?

      submitted by /u/Potential_Block4598
      [link] [comments]

  4. August 14, 2026
    1. đź”— IDA Plugin Updates IDA Plugin Updates on 2026-08-14 rss

      IDA Plugin Updates on 2026-08-14

      New Releases:

      Activity:

      • augur
        • 5a538755: ci: bump the actions-dependencies group with 3 updates
      • capa
      • efiXplorer
        • fe106ca6: feat: use uncached ctree for analysis, combine efixplorer windows and…
        • 65f3af5e: fix: use decompile uncached (#146)
        • 6b2707c2: feat(ui): combine efixplorer windows and preserve deterministic order
        • 9c24e3c0: build: update idasdk and disable warnings for third-party headers (#144)
        • e66f693d: feat: add support for linux aarch64 builds (#143)
      • eject_idb
        • 4fb7b2fb: Maintenance release (v0.0.3)
      • haruspex
        • 072bd725: ci: bump the actions-dependencies group with 3 updates
      • ida-sdk
        • 2a9143f2: idapython: Make the standalone build self-sufficient
        • e7239805: sdk: Rebuild the Windows int128/network libs CRT-neutral
        • dca60670: build: Default to Release for every standalone entry point
        • 225c3064: build: Ship the Windows Qt import libs
      • qscripts
        • 6d361f34: hcli: package qscripts as flat per-IDA-version plugin zips (hcli-inst…
      • rhabdomancer
        • 10c1433e: Merge pull request #7 from 0xdea/dependabot/github_actions/actions-de…
        • 5ea066d0: ci: bump the actions-dependencies group with 3 updates
      • Security-Tools
        • 5fbe3378: Add Proxychains for Windows with documentation and configuration
      • twdll
        • 389b8551: feat!: properly return POLITICAL PARTY LIST
    2. đź”— anthropics/claude-code v2.1.233 release

      What's changed

      • Added GitLab merge request URL support to the --worktree flag and the claude agents view (where MRs display as !N)
      • Added an opt-in forward_user_identity apps gateway setting on Anthropic upstreams that sends the signed-in user's identity as headers, so a proxy behind the gateway can attribute spend per user
      • Added opt-in memory cgroup support for Bash tool commands on Linux (CLAUDE_CODE_TOOL_MEMORY_LIMIT) so a runaway build can't stall the session
      • Added CLAUDE_CODE_WEBFETCH_CACHE_TTL_MS environment variable to configure the WebFetch session URL cache TTL (default unchanged: 15 minutes)
      • Fixed cloud sessions occasionally being marked as lost when the environment shut down while Claude was waiting on a permission prompt
      • Fixed MCP v2 connections endlessly reopening the subscriptions/listen stream against servers that terminate long-held streams on a fixed timeout (e.g. serverless hosts)
      • Fixed Notification hooks not firing for permission prompts when running under Claude Desktop or VS Code
      • Fixed idle sessions on Linux sometimes keeping one CPU core at 100% when sandboxing is enabled
      • Fixed bundled skill aliases like /checkup and /review reporting "Unknown command" in -p mode or with plugins/MCP loaded when a user or project skill shadows the bundled skill
      • Fixed skill/command argument substitution to prevent argument values from being re-expanded as template markers
      • Fixed Windows paths spelled with the NT \??\ device prefix bypassing UNC path validation, closing an NTLM credential-leak vector
      • Improved claude self-hosted-runner session start time: the session branch is now created without rewriting the working tree, and two server round trips no longer block the agent's launch
      • Improved apps gateway error forwarding: 400/413 errors from Vertex, Foundry, and Claude Platform on AWS upstreams now carry the upstream's own message; fixes a bug with auto-compact on apps gateway
      • Improved claude plugin validate to check a bare .claude/skills directory, reporting SKILL.md files whose frontmatter fails to parse
      • Improved screen reader mode: the /effort selector renders as a numbered list with a typed-number prompt, and hint and dialog text is no longer clipped
      • Improved print mode diagnostics: a [claude-code:unrecognized_model] line is written to stderr when a request goes out for a model ID Claude Code doesn't recognize; map it with modelOverrides to silence
      • Changed the GitHub app setup tip to no longer appear in repositories whose origin remote is on gitlab.com or bitbucket.org; the enterprise marketplace tip now covers non-GitHub internal git hosts
      • Todo/task-tracking tools (TaskCreate/Get/Update/List, TodoWrite) are no longer available on Opus 4.8, Sonnet 5, Fable 5, Mythos 5, and newer models; set CLAUDE_CODE_ENABLE_TODO_TOOLS=1 to bring them back
      • Windows: fixed auto mode repeatedly stopping for manual approval on ordinary cd <dir> && <command> > file Bash commands (a 2.1.232 regression)
      • Reverted the 2.1.232 Bash permission changes for Cygwin-style symlinks on Windows and for input redirections (< file); a narrower version will return in a later release
    3. đź”— exe.dev No Plan Survives Contact With the Enemy (Reality) rss

      If you’ve ever presented the design of a product after the fact, you know the most interesting bit is the surprises. What broke at scale? Where did you change course? What did the customers do that you didn’t expect? What were the interesting metrics? These are impossible to predict in advance. They’re also the most important parts—the punch lines.

      When we talk to folks about how they use coding agents they usually fall near one end of a spectrum: planners , who work on a spec or design with an agent, and iterators , who write a short prompt, and iterate on (or throw out) the results. Of course, this is all new, and none of us knows what we’re doing yet. (This is the time to let a thousand flowers bloom. Build your own software factory.)

      But the debate on planning vs iteration is not new. (And neither side is right, though you should consider about what works for your team, and why). We’ve read clear PRDs or slides that have set the direction for a product or project. We’ve been in meetings where the prototype carried the day after weeks of failed paper designs. And everything in between.

      If your most precious commodity is your attention, ask your agents for the design after they’ve built the thing. Ask it for the surprising things. The sticky bits. The workarounds. The contentious topics in review. The traditional funny quote here is from Frank Westheimer, who said “Why spend a day in the library when you can learn the same thing by working in the laboratory for a month?” If it’s the coding agent—and not you—in the lab, however, this is turned upside down: let the agent spend some extra cycles in the lab, and get one layer deeper on the design.

      The planners and iterators are closer than they think: a plan that’s been prototyped is a better plan.

    4. đź”— modem-dev/hunk v0.18.2 release

      What's Changed

      • Speed up hunk diff in repositories with many untracked files by @benvinegar in #742

      Full Changelog : v0.18.1...v0.18.2

    5. đź”— r/LocalLLaMA Local uncensored Opus 4.6 at home - Qwen3.8 27B heretic rss

      Local uncensored Opus 4.6 at home - Qwen3.8 27B heretic | Someone made a heretic version of Qwen 3.8 27B, giving us a local Opus 4.6 tier model but without any refusals or safeguards! Fuck Dario submitted by /u/Temporary_Idea8880
      [link] [comments]
      ---|---

    6. đź”— r/LocalLLaMA Qwen3.8-27B is identical to Qwen3.6-27B! rss

      Qwen3.8-27B is identical to Qwen3.6-27B! | Interestingly, the 3.8 version has exactly the same architecture - meaning all the capability gains come from training improvements! See the diff (0 changes) here! https://hfviewer.com/compare/qwen3.6-27b-vs-qwen3.8-27b submitted by /u/Course_Latter
      [link] [comments]
      ---|---

    7. đź”— r/LocalLLaMA Qwen 3.8 27B Released! Please Share Your Experience rss

      With your experiments, Qwen 3.8 27B most close which frontier model? And please specify which quantization you run. I will post to comments my tests and experience too.

      submitted by /u/BarberIcy366
      [link] [comments]

    8. 🔗 r/LocalLLaMA Qwen/Qwen3.8-27B · released rss

      Qwen/Qwen3.8-27B · released | submitted by /u/de4dee
      [link] [comments]
      ---|---

    9. đź”— r/LocalLLaMA IT'S OUT rss

      IT'S OUT | submitted by /u/Certain-Cod-1404
      [link] [comments]
      ---|---

    10. đź”— HexRaysSA/plugin-repository commits sync repo: +1 plugin, +9 releases rss 
      sync repo: +1 plugin, +9 releases

## New plugins
- [eject_idb](https://github.com/allthingsida/eject_idb) (0.0.3)

## New releases
- [IDA-MCP](https://github.com/captain-ai-hub/ida-mcp): 0.8.0, 0.7.1, 0.7.0
- [QScripts](https://github.com/allthingsida/qscripts): 1.2.8
- [SigMaker](https://github.com/mahmoudimus/ida-sigmaker): 1.14.3
- [ida-codemode](https://github.com/hexrayssa/ida-codemode): 0.6.1, 0.6.0, 0.5.3
    11. đź”— earendil-works/pi v0.84.2 release

      New Features

      • Fullscreen transcript search — Search and navigate matches in fullscreen mode. See TUI Fullscreen Viewport.
      • Configurable default tools — Choose startup built-in tools globally or per project. See Tools.
      • Configurable fullscreen exit output — Print the transcript or only a resume hint on exit. See Interactive Mode.

      Added

      • Added fullscreen transcript search with Ctrl+Shift+F, incremental match highlighting, configurable search match theme colors, and next/previous navigation with Enter/Ctrl+G and Shift+Enter/Ctrl+Shift+G.
      • Added experimental strict JSON-schema constrained sampling for the default read, bash, edit, and write tools under PI_EXPERIMENTAL=1.
      • Added a fullscreen exit output setting to choose between printing the final transcript and only a session resume hint.
      • Added the defaultTools setting for configuring the initial built-in tool selection globally or per project.
      • Added --use-theme <name[/name]> to choose an initial per-run interactive theme without changing saved settings (#7722 by @rwachtler).
      • Added expandPromptTemplates to extension pi.sendUserMessage() options for explicitly dispatching commands and expanding skills and prompt templates. See pi.sendUserMessage() (#7857 by @mrexodia).
      • Added inherited createGatewayBindingFetch() for routing Cloudflare AI Gateway requests through a Workers AI binding without an API token (#7901 by @Maximo-Guk).
      • Added inherited AssistantMessage.endTurn to preserve OpenAI Codex's terminal end_turn signal for diagnostics (#7766).
      • Added inherited unbound single-line transcript scrolling actions for fullscreen mode. See TUI Fullscreen Viewport (#7903 by @midastruth).

      Changed

      • Changed inherited Kimi Coding requests to use pi's runtime User-Agent header.
      • Replaced the inherited Mistral SDK transport with a native Chat Completions HTTP stream, eliminating its generated client and schema runtime overhead.
      • Documented the generic AI_AGENT=pi process marker and how it differs from PI_CODING_AGENT=true (#7747).
      • Changed inherited OpenAI Responses deferred tool loading to prefer message-anchored additional_tools where supported while retaining tool-search and top-level fallbacks (#7709).
      • Reduced inherited fullscreen rendering allocation churn by painting full-width layout rows directly instead of recompositing them on every frame.

      Fixed

      • Fixed managed-tool downloads delaying TUI startup and hiding diagnostics in fullscreen mode by mounting the TUI first and showing download progress and warnings inside it.
      • Fixed opening a model selector immediately after startup cancelling and restarting the in-progress model catalog refresh.
      • Fixed inherited GitHub Copilot login triggering API rate limits while enabling model policies by limiting concurrent policy updates (#6187).
      • Fixed fullscreen transcript search snapping back to the current match during manual scrolling and fragmented mouse input leaking into the search query.
      • Fixed inherited required LaTeX arguments starting on a new line being parsed as empty (#7760).
      • Updated the transitive nanoid development dependency to address a denial-of-service vulnerability.
      • Fixed fallback rendering for extension tool results to collapse long output and honor tool expansion (#7979).
      • Fixed JSON and RPC message_update events dropping cumulative usage during streaming. See JSON Event Mode and RPC message_update (#7982 by @christianklotz).
      • Fixed pi.sendMessage(..., { triggerTurn: false }) steering an active run instead of only recording the custom message (#8022 by @cristinaponcela).
      • Fixed the defaultTools setting dropping extension and SDK custom tools when selecting built-in defaults.
      • Fixed the subagent example rejecting YAML array syntax for the tools frontmatter field (#7598 by @alexsavio).
      • Fixed the subagent example dropping parent session model, thinking, and tool configuration (#7897 by @virtuald).
      • Fixed custom system prompts concatenating the current working directory with later appended prompt content (#7887 by @distributedlock).
      • Fixed inherited OpenAI Responses function and custom tool calls losing namespaces during streaming, proxying, and replay (#7709).
      • Fixed inherited upstream request buffer failures not triggering automatic assistant retries.
      • Fixed inherited built-in and custom DeepSeek API models sending output limits through an unsupported field.
      • Fixed inherited Amazon Bedrock replay rejecting tool arguments that contain empty object keys while preserving all valid nested values (#7882 by @muyiyr).
      • Fixed inherited DeepSeek compatibility detection for base URLs whose hostname contains uppercase letters (#7933 by @yearth).
      • Fixed inherited Google Generative AI and Vertex AI responses with tool calls incorrectly treating output-limit or provider-error stops as normal tool use (#8059).
      • Fixed inherited fullscreen mouse drag selection and OSC 8 link activation in terminals that report generic SGR mouse release button codes (#7963).
      • Fixed inherited focused fullscreen overlays not receiving mouse wheel or viewport scroll keys such as PageUp and PageDown (#7894).
      • Fixed inherited LaTeX control spaces split across line endings causing complete expressions to fall back to raw source.
      • Fixed split Alt+Enter input over SSH being misread as Escape, added PI_TUI_ESC_TIMEOUT for high-latency terminals, and limited that timeout to lone Escape input (#7899 by @powerfooI).
      • Fixed inherited idle fullscreen sessions repainting and clearing text selection when the terminal loses focus (#7892 by @terrorobe).
      • Fixed fullscreen selection copy to use the host clipboard and report failure instead of claiming success when OSC 52 is unsupported (#8110 by @Panoplos).
    12. đź”— smol-machines/smolvm smolvm v1.8.1 release

      What's Changed

      • Add labels to the embedded MachineSpec so SDK callers reach CLI parity by @BinSquare in #929
      • Move the label parser into the library so every front end shares one implementation by @BinSquare in #930
      • Pass the stub name to pack create -o in the README snapshot recipe by @NickyHeC in #934
      • Rejuvenate a forked clone's identity inside the workload rootfs so image clones stop inheriting the golden's SSH host keys by @BinSquare in #936
      • Record egress denials and surface them per machine through the CLI and serve API by @BinSquare in #937
      • Preserve container file ownership in packed machines by @BinSquare in #938
      • Move interactive-session writes to a dedicated thread so exec -i handles large piped stdin by @panta in #931
      • chore(nix): bump flake to 1.8.0 by @BinSquare in #928

      Full Changelog : v1.8.0...v1.8.1

    13. đź”— r/LocalLLaMA GLM 5.3 Released rss

      GLM 5.3 Released | Official Announcement https://z.ai/blog/glm-5.3 submitted by /u/jmorant555
      [link] [comments]
      ---|---

    14. đź”— matklad Printing Lists rss

      Printing Lists

      Aug 14, 2026

      To print a comma-separated list, a concise idiom is to optionally print the comma first, before the element:

      for (items, 0..) |item, item_index| {
    if (item_index > 0) std.debug.print(", ");
    std.debug.print("{}", .{item});
}
    15. đź”— New Music Releases Above & Beyond - When You Believe rss

      Above & Beyond - a new release is available:

      • 2026-08-14: When You Believe (Single)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    16. đź”— New Music Releases Armin van Buuren - Burn It Up rss

      Armin van Buuren - a new release is available:

      • 2026-08-14: Burn It Up (Single)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    17. đź”— New Music Releases Saliva - Breaking Through rss

      Saliva - a new release is available:

      • 2026-08-14: Breaking Through (Album)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    18. đź”— New Music Releases Ferry Corsten - Bring Me Back to Life rss

      Ferry Corsten - a new release is available:

      • 2026-08-14: Bring Me Back to Life (Single)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    19. đź”— New Music Releases Unprocessed - Lost Tapes rss

      Unprocessed - a new release is available:

      • 2026-08-14: Lost Tapes (EP)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

generated: August 17, 2026 at 21:15:03