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  1. July 20, 2026
    1. πŸ”— HexRaysSA/plugin-repository commits sync repo: +2 plugins, +2 releases, ~2 changed rss 
      sync repo: +2 plugins, +2 releases, ~2 changed

## New plugins
- [ida-taskr](https://github.com/mahmoudimus/ida-taskr) (1.0.3)
- [idavator](https://github.com/mahmoudimus/idavator) (0.1.1)

## Changes
- [SigMaker](https://github.com/mahmoudimus/ida-sigmaker):
  - 1.14.0: archive contents changed, download URL changed
  - 1.13.0: archive contents changed, download URL changed
    2. πŸ”— tonsky.me Looking for work rss

      Hey, Niki here. This is a bit unusual. My sabbatical is coming to an end, and I am looking for a new opportunity. Full-time or contract, startup or research, remote or Berlin, individual contributor, ideallyβ€”tight team, ambitious product.

      I am a software engineer first and foremost with 20+ years of experience. I work on technically challenging products, foundational technology, dev tools. I’ve been doing Clojure and web recently, but I'm also very excited to explore closer-to-the-metal programming.

      I have an eye for design, user interfaces, UX, DX. I would love to work with a team that takes interface quality seriously. Or to work with graphics!

      I am pretty sure I am good at explaining stuff, including what we are building, why, why this way, why is it important, etc. For example.

      The overarching theme is to understand computers deeply, and then use that to make better and simpler software. If you care about that too, we might be a great match!

      Recent work

      Instant DB is a US startup building a modern Firebase. I worked on the sync algorithm, performance, DX. A summary of my commit log.

      Roam Research is an OG personal knowledge manager. I worked on database optimization and a plugin system.

      At JetBrains, I developed a new Skia renderer for Fleet and Jetpack Compose Desktop.

      I’ve built many open-source libraries, including a database, a GUI toolkit, a Clojure dev environment, a React wrapper, a well-known font... More recently, Clojure+ gives you a taste of my approach to DX, and Fast EDNβ€”to performance.

      I maintain several active projects β€” AlleKinos.de, Grumpy Website, this site.

      If you want to dive deeper, here’s the usual stuff: Projects / Talks / LinkedIn / GitHub

      Why this post?

      It’s an attempt to reach beyond my immediate network. I’ve been doing Clojure for a long time, and now want to explore.

      If you are working on a compiler, a database, an IDE, a programming language or another technically ambitious product, touching graphics, typography, algorithms, low-level programming, and you think my experience can help, let’s talk: niki@tonsky.me.

  2. July 19, 2026
    1. πŸ”— r/LocalLLaMA HuggingFace security incident report: "the attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails" rss

      HuggingFace security incident report: "the attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails" |

      Earlier this week, we detected and responded to an intrusion into part of our production infrastructure. This one was different from anything we had handled before in one important way: it was driven, end to end, by an autonomous AI agent system - and we detected and dissected it largely with AI of our own. [...] The attack was initially surfaced through AI-assisted detection. Our anomaly-detection pipeline uses LLM-based triage over security telemetry to separate real signals from the daily noise, and it was the correlation of those signals that flagged the compromise. [...] When we started the log analysis, we first used frontier models behind commercial APIs. This did not work: the analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails , which cannot distinguish an incident responder from an attacker. We ran the forensic analysis instead on GLM 5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and none of the credentials it referenced, left our environment.

      This is why it's important that frontier-tier open weight model exists and we don't have to rely on the mercy of the corporate overlord to tell us what we can use the model for. submitted by /u/Umr_at_Tawil
      [link] [comments]
      ---|---

    2. πŸ”— MetaBrainz Spotify users will need to reconnect every 6 months to ListenBrainz rss

      Spotify recently announced a drastic change in their API: connections to your account will now expire after 6 months, starting July 20th.

      If you have your Spotify account connected to ListenBrainz, this means you will have toreconnect your Spotify account every 6 months , or ListenBrainz will not be able to keep your listening history in sync.
      To get us started, all users will need to reconnect their Spotify account this coming Monday July 20th.

      In addition to sending you an email, you will see an error message at the top of the page in ListenBrainz:

      To minimize disruption and potential loss of listening history in the future, we will send you an email a month ahead, and one week ahead of the disconnection for you to disconnect and reconnect your Spotify account in your music services settings.

      This is quite the thorn in our side but alas we have no other choice as the internet continues to enshittify.

    3. πŸ”— r/LocalLLaMA Please Qwen, can we have more 3.x-35B-a3B please πŸ™ rss

      Please Qwen, can we have more 3.x-35B-a3B please πŸ™ | submitted by /u/JLeonsarmiento
      [link] [comments]
      ---|---

    4. πŸ”— r/LocalLLaMA Prepare your (v)ram - Qwen3.8 is coming! rss

      Prepare your (v)ram - Qwen3.8 is coming! | submitted by /u/xw1y
      [link] [comments]
      ---|---

    5. πŸ”— @malcat@infosec.exchange You like [#capa](https://infosec.exchange/tags/capa) but wish it would scan mastodon

      You like #capa but wish it would scan faster?
      Try out #Malcat 0.9.15, featuring a blazing fast native Capa scanner, among other improvements:

      https://malcat.fr/blog/0915-is-out-capa-scanning-at-native- speed/

    6. πŸ”— r/LocalLLaMA Ahem! Qwen is on the move again rss

      Ahem! Qwen is on the move again | https://preview.redd.it/0l8w2j67a5eh1.png?width=581&format=png&auto=webp&s=cae9d3ef7cf80cea780e0670f7dede73d1c02d49 https://x.com/Alibaba_Qwen/status/2078754377473601787?s=20 submitted by /u/Lowkey_LokiSN
      [link] [comments]
      ---|---

    7. πŸ”— r/LocalLLaMA head of strategic futures from openai on open-weight chinese models. rss

      head of strategic futures from openai on open-weight chinese models. | Dean W. Ball analyzes China's Kimi model, noting its strong performance while expressing surprise that the Chinese government permits open-sourcing such capable AI due to potential risks. He argues that open-weight models ultimately slow down AI capital expenditure and could lead to a state-controlled public infrastructure, which the US administration might counter by introducing strategic regulatory friction. submitted by /u/Formal_Drop526
      [link] [comments]
      ---|---

    8. πŸ”— Filip Filmar Cocoapuffs: Booting Fuchsia's Zircon Kernel on a RISC-V core in Artix-7 FPGA rss

      Zircon, the (non-POSIX, non-Linux) kernel powering Fuchsia, an open-source operating system under development at Google, now boots on my RISC-V based system-on-chip design, running on an AMD Artix-7 FPGA device. While this might be the first Fuchsia-powered device apart from the boards that Google works on, it is definitely the first piece of programmable hardware running Fuchsia. Why not Linux instead? I thought it would be novel and more amusing to see Fuchsia booting on a FPGA, vs Linux.

  3. July 18, 2026
    1. πŸ”— IDA Plugin Updates IDA Plugin Updates on 2026-07-18 rss

      IDA Plugin Updates on 2026-07-18

      New Releases:

      Activity:

      • ida-sigmaker
        • 8741e798: Merge pull request #85 from mahmoudimus/diff/ignore-superpowers-docs
        • ca335484: docs: correct macOS user directory
        • c5064833: Ignore local superpowers planning docs
        • 7fd35fce: Merge pull request #84 from mahmoudimus/diff/release-v1.14.0-test-fix
        • 774c332e: Keep speedups remediation test version-aware
        • 6394378c: Prepare v1.14.0 release
        • 406c3969: Merge pull request #83 from mahmoudimus/diff/xref-buffer-reuse
        • cdc32ec0: Merge pull request #81 from mahmoudimus/diff/xref-lazy-startup
        • e1950d05: Merge pull request #80 from mahmoudimus/diff/simd-extension-api-compa…
        • c480160f: Reuse buffers across xref candidates
        • 2e9d282e: Keep xref progress visible without pre-counting
        • f34a4ebe: Make xref startup cancelable
        • 78250748: Accept structurally compatible legacy speedups
      • leaknet
        • 5b9087f3: - added missing retail shaders (did NOT replace ANY beta shaders)
      • Luc-Nhan
        • 299ea389: feat(history): reuse empty active tab when opening a chat
        • 7e7c27c4: Merge branch 'worktree-chat-history-on-demand': chat history on-demand
        • d37adc23: feat(history): chat history on-demand
      • re-sbz
    2. πŸ”— HexRaysSA/plugin-repository commits sync repo: +1 release rss 
      sync repo: +1 release

## New releases
- [SigMaker](https://github.com/mahmoudimus/ida-sigmaker): 1.14.0
    3. πŸ”— r/LocalLLaMA Kimi K3 ranks #1 on @AfterQuery's SpreadsheetBench 2, surpassing Claude Fable 5 rss

      Kimi K3 ranks #1 on @AfterQuery's SpreadsheetBench 2, surpassing Claude Fable 5 | submitted by /u/Charuru
      [link] [comments]
      ---|---

    4. πŸ”— Register Spill Joy & Curiosity #92 rss

      This week was busy : we shipped a lot of things, recorded quite a few things, I worked on my Laracon talk, chatted with amazing programmers in different timezones, and our local public swimming pool celebrated its 50th birthday.

      There wasn't a lot of reading this week, but a lot of thinking and wondering and questioning and aha! -ing. And I kinda can't shut up about it. So…

      Some of you might remember my original description of this newsletter: "It's very informal; it's what I'd send you if you were to ask me what's on my mind this week in an email."

      Now, here is what I'd say if you were to ask me what's on my mind this week, on a phone call:

      • Finally: Amp now has subscriptions. Yes, you read that right. Go there, get a subscription, pair it with your ChatGPT subscription so you get infinite GPT-5.6 tokens, and spawn those orbs.

      • We also shipped agent-to-agent communication in Amp: agents can now spawn other agents -- anywhere you have a Amp instance running or in an orb -- and then send messages and files to them. The number of "holy shit, it just …" messages this produced in our internal Slack is insane. To give you a taste: this morning I was hacking on something in our orb, but the agent in the orb lacked the permissions to upload an asset to our bucket. So the agent said: hey, start amp --no-tui on your machine, where you have permissions, then I'll start a thread there, send it that asset, and ask it to upload the file. And… it fucking did it! Exactly like that! I started amp --no-tui, I saw the new thread being created, I watched both of them, and saw how they sent messages to each other. Wild!

      • Raising An Agent is back! Here's the first episode of the new season: The Local Dev Env is Dead. Or listen on Spotify.

      • I know what you're thinking: "Thorsten, your voice… I need more of it." Don't worry, I got you. Dominic and Morten invited me to be a guest on the go podcast and our episode came out this week: Agentic engineering is here to stay with Thorsten Ball.

      • Yes, I know, you want more. I got more: Evan Phoenix, Quinn and I shipping from orbs to a Miren cluster. There's coding in there, but also a lot of talking about coding and developer tools and the future of software and deployments. Evan has shipped and worked on more successful developer tooling than basically anyone else (Rubinius! Puma! Hashicorp!), so him sharing his thoughts was a treat.

      • You want more? Okay, okay. I recorded a short video with thoughts on this race we're in and the forces at play that I don't think most developers are aware of. Titles I considered: "man, it must suck to be a model house", "the tectonic forces shaping software", "once the compute is available, this will all change again", and "there won't be a rugpull"

      • Hardcore Kindle reader here, but this really, really made me want to buy physical books again, even though it should probably serve as a warning to not do that: "Mendel Uminer faced a crisis when his landlord objected to the 10,000 volumes in his New York studio apartment."

      • Fabien Sanglard: Don't you mean extinct? Lovely article. You need to read this for the Phil Tippett story alone.

      • Another amazing Fabien Sanglard article: Jurassic Park computers in excruciating detail. Jurassic Park is one of my favorite movies of all time. Easy top five. I love it. And I'm sure its depiction of computers had an influence on my life. But one thing I hadn't noticed until reading this article is that Oppenheimer portrait.

      • After 7 years in production, Scarf has reluctantly moved away from Haskell. I'm honestly not sure what to say about the skeptics any more. Maybe this: for decades now, some programmers were really lucky in that what they loved to do, what they saw as their craft and their passion, was valuable to businesses. Now that's not the case anymore. And if you don't adapt, then, well, you end up not being valuable to businesses anymore.

      • Holy moly: Measuring input latency on Linux: X11 vs Wayland, VRR, and DXVK. If you're in the mood to find out how deep a rabbit hole can go, then read this. Very fascinating. Also: I can't believe it's 2026 and we're still talking about X11 vs. Wayland. Wayland was released in 2008.

      • John Carmack is smart.

      • Linus Torvalds on the Linux kernel mailing list: "There are other questions around AI (like what the economy of it will actually look like in the end), but 'is it useful' is no longer one of those questions. Anybody who doubts that clearly hasn't actually used it. Yes, it can also be a somewhat painful tool, both for maintainer

      workloads and just from a 'it keeps finding embarrassing bugs' standpoint. But the solution is not to put your head in the sand and sing 'La La La, I can't hear you' at the top of your voice like some people seem to do."

      • There is this whole debate going on around whether you should still read the code agents produce. antirez now chimed in too: Control the ideas, not the code. He writes: "But if I had my hands free, you know what I would do, instead? Use all the time that the review is taking me to do more QA, to think at the next optimization idea and apply it, and to use LLMs to write a DESIGN.md file where each data structure is described in human language, with the ideas it contains, the implementation tricks, the design. That, in the future, is going to be much more useful." I think he's onto something here. I personally do spot checks of code and mostly don't care about single functions anymore, except when the blast radius would be huge or when it's super critical. But it ties back to what antirez writes: I want to control the ideas, not the code.

      • And here's Sean Goedecke: In defense of not understanding your codebase. As always, very good post. I agree. People who say "you have to review every line" make me think that either they haven't worked with (a) a model that was released in 2026 or (b) other people in a multi-team engineering org.

      • Justin Jackson on the value of software in a Fable world: "Generally, the economy rewards difficulty and rarity. If something is hard to do or make, you get to charge more. So if AI reduces the time it takes to build software, what happens to the value of software?" See also my thoughts on software & oil here.

      • What working at Google feels like: "Have you ever changed a flat tire on the shoulder of the freeway? When you get out of your car and stand by the side of the road, you realize you are in a world scaled for 30,000-pound tractor trailers, not for human beings. The white stripes between the lanes that usually flash by like little punctuation marks are actually ten feet long and thirty feet apart. Even the road signs look absurdly out of scale, like those textbook-sized large-print editions of bestsellers the library stocks for elderly people. And then one of those tractor trailers hurtles by at seventy miles per hour, inches from your fragile body, and it feels like God himself is screaming in your face. That's exactly what working at Google feels like at first. You realize very quickly you are inhabiting an environment that was not designed for humans to experience with their naked minds. Even the smallest problems--which customers are we allowed to send this email to? What countries will have special legal requirements around the deployment of this tiny feature?--are so mind-numbingly complex that they make you want to shrink down into a fetal ball on the side of the freeway and just let the traffic shriek past."

      • "I had a french professor who once said if you just did something like going to the supermarket and experienced it fully without the goggles of habit and categories you would go crazy with pure sense and joy. I think about it all the time. In a way this is all for him." And I had a french teacher once who said that bean soup is the poor man's piano. I think about him every time I eat beans. So there's that.

      If you liked my phone call, you should subscribe:

    5. πŸ”— r/LocalLLaMA What kind of dark magic is Deepseek using? rss

      What kind of dark magic is Deepseek using? | I was taking a look at Kimi K3 scores on the Artificial analysis leaderboard and was quite baffled when I saw this chart. Granted, Deepseek has always been the king of price to performance, but this is still incredible. Is it just API subsidization or have they optimized their models truly this much? submitted by /u/Fuckinglivemealone
      [link] [comments]
      ---|---

    6. πŸ”— Ampcode News Subscriptions, At Last rss

      Today we're launching Amp Subscriptions in Beta. You can now subscribe monthly to Amp and explore the frontier with us, with cheaper and more predictable pricing:

      Subscription FAQs

      If you subscribe on or before Sunday, July 19[^1], you'll get bonus 2x usage for orbs and agents in the first month.

      Amp Is Not (Necessarily) Expensive Anymore

      Amp just got a lot cheaper for many of you, especially if you link your ChatGPT subscription.

      We know you've been asking for this for a long time. Until now, Amp's pricing model has been pay-as-you-go for tokens at API prices, no subscription. Compared to other agents on monthly subscriptions, this made Amp more expensiveβ€”"the Apple or Porsche of agentic coding tools", to put it nicely.

      But everything is changing. Great tokens are reasonably priced. Good-enough tokens are downright cheap (like GLM-5.2 in our new low mode). Being on the frontier no longer requires using the most expensive models.

      You can still pay-as-you-go in Amp; monthly subscriptions aren't required.

      And, to be clear, to use Amp beyond your subscription's included monthly limits, you need to link your ChatGPT subscription or add paid credits.

      The Frontier Runs in Orbs, Not Your Laptop

      The frontier is now about agents working for you in parallel, without your supervision, on remote machines. We call these "orbs", and Amp's monthly subscriptions include so much orbs usage you don't need to worry about counting the minutes.

      We want you to finally be able to (and want to) kill your singleton local dev environment.

      We want you to make your agents go further to prove to you their work is correct, with videos and screenshots and local dev portals, and much less manual code review.

      Remember last year, when other agents asked you to approve the agent's work step-by-step, edit-by-edit? Amp users realized before anyone else that was dumb and slow, and Amp never did that.

      This shift feels similar to us. It's inevitable, and we want it to go as fast as possible. We hope this subscription makes it easy for you to explore this new frontier with us.

  4. July 17, 2026
    1. πŸ”— IDA Plugin Updates IDA Plugin Updates on 2026-07-17 rss

      IDA Plugin Updates on 2026-07-17

      New Releases:

      Activity:

    2. πŸ”— r/LocalLLaMA Kimi K3 is top of nextjs eval rss

      Kimi K3 is top of nextjs eval | submitted by /u/Charuru
      [link] [comments]
      ---|---

    3. πŸ”— @binaryninja@infosec.exchange Going live! Join us to learn about everything that's new in Sidekick 26: mastodon

      Going live! Join us to learn about everything that's new in Sidekick 26: https://www.youtube.com/live/S5hAxyopaQk

    4. πŸ”— HexRaysSA/plugin-repository commits sync repo: +1 plugin, +5 releases, ~1 changed rss 
      sync repo: +1 plugin, +5 releases, ~1 changed

## New plugins
- [SigMaker](https://github.com/mahmoudimus/ida-sigmaker) (1.13.0)

## New releases
- [IDASQL](https://github.com/allthingsida/idasql): 0.0.18
- [hrtng](https://github.com/kasperskylab/hrtng): 3.9.108
- [ida-rpc](https://github.com/bkerler/ida_rpc): 0.1.8, 0.1.7

## Changes
- [IDASQL](https://github.com/allthingsida/idasql):
  - 0.0.8: archive contents changed, download URL changed
    5. πŸ”— @binaryninja@infosec.exchange Our Firmware Reverse Engineering class is just over a week away! Join us to mastodon

      Our Firmware Reverse Engineering class is just over a week away! Join us to learn what's involved in analyzing bare-metal software and how to overcome those challenges! https://shop.binary.ninja/products/fre- july-26

      https://youtube.com/shorts/486zHriqGMA

    6. πŸ”— r/LocalLLaMA Bonsai 27B runs locally on an iPhone - a 27B model in 3.9GB rss

      Bonsai 27B runs locally on an iPhone - a 27B model in 3.9GB | PrismML built Bonsai on top of Qwen3.6-27B by quantizing the weights down to 1-bit. That takes it from ~54GB to 3.9GB, small enough to fit and run on a phone, while keeping ~90% of the benchmark scores It's true binary quantization ("binary g128") - every weight is a single sign bit and each group of 128 shares one FP16 scale, so it lands at ~1.125 bits/weight with no high-precision escape hatches. Even the embeddings, attention/MLP projections and the LM head are binary, which is the surprising part, most 1-bit schemes keep some layers higher Across 15 benchmarks it averages 76.1 vs 85.1 for the FP16 model (~89.5%). Math holds up best (91.7), knowledge and reasoning take the biggest hit (73.4 vs 83.2), which is exactly where you'd notice it dropping the odd details. Memory stays friendly too: ~5.2GB at 4K context, ~6.8GB at 100K with 4-bit KV cache All credit to PrismML for the model: https://huggingface.co/prism-ml/Bonsai-27B-mlx-1bit
      Running it on iPhone 15 Pro Max (8GB RAM) via https://github.com/AtomicBot- ai/Atomic-Chat (I'm on the Atomic team, happy to answer questions) submitted by /u/ElmBark
      [link] [comments]
      ---|---

    7. πŸ”— r/LocalLLaMA Chinese President Xi Jinping speaks at World AI Conference and reaffirms commitment to open source to promote"openness and win-win" rss

      Chinese President Xi Jinping speaks at World AI Conference and reaffirms commitment to open source to promote"openness and win-win" | From Vincent Chow on 𝕏: https://x.com/vince_chow1/status/2077947375964791028 submitted by /u/Nunki08
      [link] [comments]
      ---|---

    8. πŸ”— r/LocalLLaMA Anyone else completely tuning out these massive "open weight" drops? rss

      Tbh the benchmarks on stuff like GLM-5.2 look insane. 753B params, 1M context, MIT license... everyone is throwing a party on the front page right now. But like... what is actually "local" about this anymore? A 700B+ MoE isn't fitting on anyone's home rig. Even if you absolutely crush it down to a q1 or q2 GGUF, you're still not running it. I've got a dual-GPU setup running on a solid x8/x8 bifurcation board, and even heavily optimized under AMD ROCm, these behemoths are physically impossible to load without an enterprise server rack. I miss when this sub was actually about self-hosting. The vibe used to be sharing compile tricks, fighting with llama.cpp ⁠--batch⁠ sizes, testing new quants, and actually squeezing models into our hardware. Now half the posts are basically just free marketing for models that 99% of us can only use by paying for APIs or renting cloud instances. Which completely defeats the purpose. Don't get me wrong, it's cool that the weights are actually published instead of locked in a vault. But practically speaking? They might as well be closed source for normal people. Maybe I'm just salty about being VRAM poor lol, but the hype for these giant unrunnable drops is totally dead for me. Anyone else feeling this?

      submitted by /u/Mountain_Patience231
      [link] [comments]

    9. πŸ”— Julia Evans Learning a few things about running SQLite rss

      Hello! I've been working on a Django site recently, and I decided to use SQLite as the database. When I was getting started with using SQLite as database for a website I read a bunch of blog posts about how it is totally fine to use SQLite in production for a small site and I think it is totally fine, but what I did not fully appreciate is that SQLite is still a database, databases are complicated, and I do not know a lot about operating databases.

      So here are a couple of small things I've been learning about running SQLite. This is the 4th website I've used SQLite for, and I think this one is harder because with the power of the Django ORM I've been making the database do more work than I was previously without Django.

      I started by turning on WAL mode like all the blog posts said to do and hoping for the best.

      ANALYZE is apparently important

      Today I was running a query (using SQLite's FTS5 for full-text search) on a table with 4000 rows and it took 5 seconds. That seemed wrong to me: computers are fast!

      It turned out that what I needed to do was to run ANALYZE! Immediately the problem query went from taking 5 seconds to like 0.05 seconds (or some other number small enough that I didn't care to investigate further). I still don't know exactly what went wrong in the query plan, but my best guess is that it was some sort of accidentally quadratic thing.

      ANALYZE generates "statistics" (I guess about the number of rows in each table? and presumably other things?) so that the query planner can make better choices.

      Maybe one day I'll learn to read a query plan.

      cleaning up the database is tricky

      Occasionally I've run into situations where I accidentally put a bunch of rows in my database that I don't want to be there (for example completed tasks from django-tasks-db), and I want to clean them up.

      What's happened to me a few times in this case is:

      1. I run some kind of command to clean up the rows
      2. The command takes more than 5 seconds, since there are a lot of rows (though I still have some questions about why these DELETE statements are so slow honestly, maybe there's a bunch of Python code running inside a transaction, I'm not sure)
      3. One of the other workers tries to write the database while this is happening, and times out after 5 seconds (I have a timeout of 5 seconds set)
      4. The worker crashes because it couldn't write to the database and the VM shuts down

      My approach so far has been to just do these cleanup operations in small batches so that I don't need to do database queries that take more than 5 seconds to run. This whole experience has given me more of an appreciation for why someone might want to use a "real" database like Postgres which can have more than one writer at the same time though.

      Maybe in the future I'll just take the site down for scheduled maintenance instead when I need to do this kind of thing, but I haven't figured out a workflow for that yet.

      no notes on performance of ORM queries yet

      So far I've been using Django's ORM to make any query I want without paying any attention at all to query performance and it's mostly been going okay other than the ANALYZE thing. The database is pretty small (maybe 10000 rows?) and I expect it to stay pretty small forever, so I'm hoping that that plan will keep working.

      backing up sqlite

      I've done SQLite backups a couple of ways. I don't think I've actually tested restoring from my backups but I do usually try to monitor them with a dead man's switch.

      way 1: restic

      sqlite3 /data/calendar.db "VACUUM INTO '/tmp/calendar.sqlite'"
gzip /tmp/calendar.sqlite

# Upload backup to S3
# Sometimes the backup gets OOM killed and so it stays locked, do an unlock
restic -r s3://s3.amazonaws.com/some_bucket/ unlock
# Do the backup & prune old backups
restic -r s3://s3.amazonaws.com/some_bucket/ backup /tmp/calendar.sqlite.gz
restic -r s3://s3.amazonaws.com/some_bucket/ snapshots
restic -r s3://s3.amazonaws.com/some_bucket/ forget -l 1 -H 6 -d 2 -w 2 -m 2 -y 2
restic -r s3://s3.amazonaws.com/some_bucket/ prune

      way 2:litestream

      I started trying out Litestream recently because I felt like doing incremental backups might be more efficient: my restic backups were sometimes getting OOM killed, and I was a bit tired of it. Basically I just write a config file and run:

      litestream replicate -config litestream.yml

      I set retention: 400h in my config file in an attempt to retain some amount of history of the database but I have no idea if it works.

      I've been backing up to AWS, which is always a pain because it's annoying to navigate the AWS console to generate credentials. Maybe one day I'll move away to some other S3-compatible alternative.

      you can use multiple databases

      My current project only has one database, but one trick I used with Mess with DNS was to split the tables into three separate database files because I didn't actually need my tables to be in the same db. I think it was helpful.

      Mess with DNS has been running on SQLite for 4 years now (since 2022) and it's been great, I think the move from Postgres was a great choice for that project.

      that's all!

      It's always kind of fun to see how long it takes me to learn sort of basic things about the technologies I'm using. I think I used SQLite for a web project for the first time in 2022 and I only learned that ANALYZE existed today! I imagine in a year or two I'll be learning about some other very basic feature.

      some references

      Some blog posts I've looked at, other than the official docs:

    10. πŸ”— New Music Releases TiΓ«sto - Echo Sax Finale rss

      TiΓ«sto - a new release is available:

      • 2026-07-17: Echo Sax Finale (Single)

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

      Visit muspy for more information.

    11. πŸ”— New Music Releases Periphery - The Marigold Nocturne rss

      Periphery - a new release is available:

      • 2026-07-17: The Marigold Nocturne (Single)

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

      Visit muspy for more information.

    12. πŸ”— New Music Releases Haken - in a fever dream rss

      Haken - a new release is available:

      • 2026-07-17: in a fever dream (EP)

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

      Visit muspy for more information.

    13. πŸ”— Ampcode News From Agent to Agent rss

      You can now ask your agents in Amp to spawn other agents. In orbs, your local machine [^1], or on any other machine.

      They can send messages and files to each other, too.

      An Amp agent creating a new thread in an orb and uploading the changed news post

      You can have agents in orbs work on side quests while you continue your work:

      Spin up an orb thread with what you know about this unrelated bug,
ask it to fix it, then keep working here.

      Or fan out work:

      Run four low-mode threads in parallel to test this flow in Chrome
at four screen sizes and report back with screenshots.

      Find and continue old work by pulling in the important files:

      Pull the files from my abandoned prototype thread into this workspace
and integrate the useful parts into our current approach.

      Offload work to another machine:

      Start a new thread on cloud-dev-box and upload this test matrix
we created. Ask it to run through each row at least 10 times.

      Coordinate cross-project work:

      Spawn an agent in the docs project, send it what it needs to
document this API change, and ask it to report back.

      Agents running locally, or in orbs, or anywhere else, and sending messages and files to each other? It's a whole new world.

generated: July 20, 2026 at 05:58:27