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This week's tooling landscape is quieter on the AI-native side but dense with infrastructure moves that affect how AI-driven workloads actually run in production. Cloudflare's Workflows scaling overhaul is the clearest signal: agent-triggered execution is now an assumed pattern, not a novelty, and platforms are rearchitecting accordingly. The rest of the week rounds out with a kernel maintenance drop, a meaningful abstraction removal in tRPC, and a Biome beta that's finally making ESLint replacement feel plausible. Linux 7.1 Released with Driver and Networking Fixes 7.1 is a maintenance release. No architectural changes, no new subsystems—just patches you should care about if you're running affected hardware or kernel-adjacent tooling. The two fixes worth flagging are heap overflows in the USB serial io_ti driver ( get_manuf_info() and build_i2c_fw_hdr() ), plus memory leak corrections scattered across drivers and networking subsystems. Trace tooling also gets updates, which matters if you're doing kernel-level performance analysis on production systems. One operational note: Torvalds is traveling, so merge window latency may be irregular. If you're tracking pull request timelines for custom kernel builds, plan for slippage. Verdict: Ship — if you're on 7.0 and running USB serial hardware or affected networking paths, upgrade on your normal kernel cycle. No breaking changes, no new dependencies, nothing to validate beyond your existing regression suite. tRPC Drops Abstraction Layer for React Query This is the kind of change that looks small in a changelog and feels large in daily development. The new tRPC client exposes native TanStack Query interfaces— QueryOptions and MutationOptions —directly, rather than wrapping them in tRPC-specific hooks. The practical effect: if you're already using TanStack Query elsewhere in your app, you stop context-switching between two similar-but-different mental models. You call .queryOptions() and .mutationOptions() factories and pa

Third-party iOS app stores are coming to Brazil.

Plaintiffs in the class action complaint allege Rivian falsely promised for years it would bring hands-free driving to its first-generation R1 vehicles.

Doomscrolling on social media is a very common problem and can feel like an endless loop of constantly losing track of time. Instead of tackling this issue with strict limits, a new mindful screen time app called Mivo Scrolling is trying to shake things up. Launched last month, Mivo doesn’t look super different from other […]

“You would not believe the texts I got from these tech guys,” NYT reporters Maggie Haberman and Jonathan Swan quote Donald Trump as telling associates in an upcoming book.

One previously unreported SpaceX investor has ties to Chinese military contractors.

submitted by /u/CircumspectCapybara [link] [留言]

Do you often find yourself shopping at the big blue, or perhaps you’re just looking for an alternative to Amazon? Either way, Walmart is currently offering a year of its Walmart Plus subscription for $49, which typically costs $98. The membership includes perks like free delivery on orders over $35, free next-day and two-day shipping […]

“People just really want to take back control of their time, their lives, their attention... They’re down for whatever helps them do that.”

Biggest AI firms will likely recoil at Bernie Sanders' AI wealth fund.

OpenAI introduces new spend controls and usage analytics for ChatGPT Enterprise, helping organizations manage costs and scale AI with confidence.

The Onion's InfoWars officially has a launch date: On July 2nd, the conspiracy network previously run by Alex Jones will return as a comedy and media platform. The reboot comes more than a year and a half after news broke that the satirical news site was working to acquire the property owned by Jones, a […]

Karamo Brown, famous for his pep talks on Netflix’s “Queer Eye,” has jumped into the wellness and AI space with his new app, Kē. After spending a year and a half focusing on his own journey—from fitness and nutrition to meditation, sobriety, relationships, and personal growth—Brown wants to help others do the same. Kē offers […]

submitted by /u/craigkerstiens [link] [留言]

Thinking about indexing, we know a only a big picture that uses B-Tree structures in memory, but in modern DBMs systems there are some enhancements introduced in indexing where systems like PostgreSQL are utilizing some new OS system calls like io_uring to make syncrhonous IO reading, also direct retrieval of record from disk using functions like fseek() and in memory optimization of traversing like applying binary search on leaf page. PostgreSQL always keeps a file for indexing, unlike MySQL where it only keeps an indexing file for non-clustered indexing, and clustered indexing is calculated directly from the table, it is interesting to study the indexing file structure as well Index file structure has line pointers, TID called as tuple ID Tuple is the column value, the same column you registered for indexing, by using which Postgres calculates the actual physical address of the records from the disk to fetch it directly. Postgres has another interesting feature, while creating an index, it always sorts data and maintains ranges of pages in page 0 of the indexing, where Postgres can identify which page to look for and then load that page into memory, and then it becomes a leaf page, then binary search is performed to get the actual TID so that the record can be fetched directly For an in-depth explanation about the index file structure, loading the index file into memory, and then searching for the actual record's address, check out the given link submitted by /u/Ok_Stomach6651 [link] [留言]

I had always wondered, why ";"? And the number of times, I have been frustrated because of this little guy, missing it somewhere, adding an extra somewhere, I really wanted to learn about it. So today I did, and I thought I might share it with you guys! Story of Semicolon. submitted by /u/Mastbubbles [link] [留言]

When three Amazon software engineers testified earlier this month at Seattle City Council hearings about data centers, they started their testimony by citing a city law barring employment discrimination over political speech. Now, they're accusing their employer of breaking that law by retaliating against them. On June 10th - one week after the hearing, and […]

Learn how pull request limits can help manage contribution volume in your repositories, and see what’s next on the roadmap. The post How pull request limits are cutting down the noise appeared first on The GitHub Blog .

Most SaaS ideas don’t fail because of bad ideas. They fail because the execution gets stuck in an endless setup loop. You start with energy, then slowly get buried in: auth systems, billing, dashboards, SEO, analytics, and infrastructure decisions. By the time the “real product” should begin, momentum is already gone. Here are 7 practical alternatives to building SaaS in a way that never gets finished. 1. Nexora (start with a working SaaS foundation) Instead of rebuilding everything, Nexora gives you a production-ready base so you can focus on actual features. Includes: Authentication system Stripe billing User dashboards SEO pages Blog + docs structure Clean Next.js architecture 🔗 https://nexora.collabtower.com/ 👉 Best for founders who want to ship instead of setup. 2. Build-from-scratch Next.js projects The most common approach. You get: Full control Flexible architecture But you also get: Weeks of setup Repeated boilerplate work High chance of burnout before launch 3. SaaS boilerplates (minimal versions) Lightweight starter kits with: Auth Basic UI Simple Stripe setup But usually missing: Real dashboards SEO systems Production-level structure 4. Supabase-first builds Backend-focused setups. You get: Database Auth APIs But still need to build: Billing UI system Marketing pages SaaS structure 5. Low-code SaaS tools Fast visual builders. Pros: Quick UI creation No heavy coding Cons: Limited flexibility Hard to scale complex SaaS logic Platform dependency 6. AI-generated starter apps AI tools can scaffold SaaS apps instantly. Pros: Fast starting point Cons: Inconsistent structure Requires cleanup Not production-ready out of the box 7. Tutorial-based SaaS builds Many developers still learn SaaS by following tutorials step-by-step. Pros: Educational Cons: Slow Fragmented Hard to turn into real production apps Final takeaway Most SaaS workflows fail before launch because they repeat the same mistake: They start from zero every single time. That creates unnecessary setup

Bash is the easiest language for AI to write and the easiest language to get devastating output from. A 20-line script that "just cleans up old files" can recursively delete a home directory because the model assumed a variable would always be set. A "simple log shipper" can write your secrets to a remote server because the model used set -x for debugging and forgot to remove it. I have run AI-generated bash that I should not have. Most engineers I know have too. After enough close calls, there's a short checklist that catches the worst of it. This is that checklist. The five things to check before running any AI-generated bash 1. Does it start with a strict pragma? The first lines of any non-trivial bash script should be: #!/usr/bin/env bash set -euo pipefail IFS = $' \n\t ' What each does: set -e — exit on any command failure. Without this, a failure in line 5 doesn't stop the script from happily running lines 6-50. set -u — error on undefined variables. This is the one that saves you from rm -rf $UNDEFINED/ . set -o pipefail — propagate failures through pipes. Without it, failing-command | grep something succeeds because grep succeeds. IFS=$'\n\t' — sane field splitting. Defends against word-splitting bugs in filenames. If the AI-generated script doesn't have these, add them and re-read the script. You'll often discover bugs the pragma now flags. 2. Is every variable expansion quoted? # Wrong rm -rf $TARGET_DIR # Right rm -rf " $TARGET_DIR " The wrong version is what causes the "I deleted the root directory" stories. If $TARGET_DIR is empty or contains a space, the command becomes rm -rf (delete current directory) or rm -rf foo bar (delete two unintended things). Models default to the wrong version about half the time because the right version is harder to write in chat ("escape the quotes!") and the wrong version is what most blogs show. Fix: When reading AI bash, mentally check every $VAR for quotes. Add them if missing. This is the single biggest source of bas