标签：#launch

SpaceX aims to launch Starship from Florida by the end of the year. 2027 seems more likely.

"We probably need another site that's capable of heavy and super heavy launch capability."

Taiwan's effort to develop its own satellite launcher hit a setback this week.

"We will put the booster back into service for another flight as soon as possible."

"A team of SpaceX engineers is on their way to conduct additional analysis on the vehicle."

Watch enough AI launches and they begin to blur into a single, endlessly repeating event. There is the understated title slide. The claim that we are at an inflection point. The chart showing the new model clearing a row of benchmarks. The live demo that works flawlessly. The superlatives — most capable, most advanced, our best model yet. And the closing note that all of this will roll out “over the coming weeks,” which is to say, not today, and possibly not to you. It is a genre now, with conventions as fixed as a nature documentary, and once you see the template you cannot unsee it. The conventions of the genre Every mature format has its tropes. The AI launch has assembled a reliable set: The benchmark chart — which, as we argued in our piece on benchmarks , predicts your experience far less than its prominence implies. The cherry-picked demo — a single, gorgeous example that represents the top of the model's range, not its average day. The superlative — always “most capable,” because every model is the most capable at the instant it ships, until the next one three months later. The vague availability — “rolling out over the coming weeks,” a phrase that lets the announcement bank the excitement now and deliver the substance later, to some users, eventually. The safety paragraph — a brief, serious note about responsible deployment, positioned to reassure without committing to specifics. When every launch uses the same script, the script stops conveying information and starts conveying mood. The mood is always “inevitable progress.” The relentless cadence is part of the message The sheer frequency of these launches is itself a rhetorical device, whether or not anyone intends it that way. When a major model or feature is announced every few weeks, the cumulative effect is a drumbeat of perpetual acceleration — a sense that the field is moving so fast that to pause, to doubt, or to ask whether the last release actually delivered is to risk being left behind. The pace

It turns out that the economics of rocket reuse are pretty, pretty good.

Marketers love a good list. Top 10 tools, 5 hacks, 7 habits — it's basically our love language. So it should surprise no one that GitHub, the home of programmers and their endless "awesome" repositories, has quietly become one of the best-kept libraries for marketing resources too. If you've never wandered into GitHub's "awesome list" ecosystem, here's the idea: someone starts a repo named awesome-[topic] , the community piles on links, and it snowballs into a living, crowd-sourced bible for that niche. No paywall, no email gate, just a README that keeps growing. Below are 24 of them, worth bookmarking whether you're knee-deep in SEO, building a GTM motion, or just trying to figure out where to launch your product next Tuesday. The AI Marketing Toolbox AI ate marketing's homework, and now there are entire lists dedicated to cataloguing the aftermath. Awesome AI Marketing — Where "let the robot write it" tools live: AI copy generators, AI ad optimizers, AI everything-with-a-dashboard. Awesome AI Tools — The broader net. If it has "AI" in the name and a landing page, it's probably in here somewhere. Awesome AI Copyrighting — For when you need a headline, a hundred product descriptions, or an entire blog's worth of copy before lunch. Getting Found by Robots (GEO & AI-SEO) SEO's weird cousin has arrived: optimizing not for Google's crawler, but for the chatbot that's now answering your customer's questions instead of sending them to a search results page. Awesome AI SEO — Traditional SEO, now with an AI co-pilot bolted on. Awesome GEO — Generative Engine Optimization: the art of getting cited by ChatGPT instead of just ranked by Google. Awesome AI Visibility — Tools for tracking whether the AI overlords even know your brand exists. Building the Go-To-Market Machine Before you can market anything, someone has to actually build the engine. These are the blueprints. Awesome GTM Engineering — The increasingly technical side of go-to-market: scrapers, enrichment tools, and w

Your Claude Code setup doesn't break in one dramatic moment — it degrades a few bytes at a time, and by the time you notice, you've been paying a context tax for weeks. In a previous post I covered running an unattended daily health check with launchd. This one is the follow-up: a three-layer loop that detects that quiet degradation weekly and hands the repair job to claude -p itself. The problem: environments rot quietly if you leave them alone Some things in a Claude Code environment grow just from doing your normal work. ~/.claude/rules/ and MEMORY.md keep getting appended to, until context injection quietly crosses 40KB Experimental agent definition .md files never get archived, leaving dozens to nearly a hundred files under ~/.claude/agents/ permanently loaded Stop hooks fire over and over, creating a hook spam condition Frustration-signaling words pile up in conversation logs and nobody notices A performance audit on 2026-07-11 revealed that "agents I thought I'd archived were still being injected — 99 of them," and that turned out to be the main cause of the degraded experience. That led to the question "so do I have to go check this every week myself?" — and the answer was to automate it , which is what cc-self-audit.sh does. Five degradation metrics and their thresholds The script measures five metrics and flags "red" when any of them crosses its threshold. # 閾値（env変数で上書き可） TH_INJECT_BYTES = " ${ SELF_AUDIT_TH_INJECT :- 40000 } " # rules+CLAUDE.md+MEMORY.md 合計バイト TH_AGENTS = " ${ SELF_AUDIT_TH_AGENTS :- 60 } " # ~/.claude/agents 配下 .md 総数（再帰） TH_STOPSPAM = " ${ SELF_AUDIT_TH_STOPSPAM :- 15 } " # 監査hook発火/週 TH_FRUSTRATION = " ${ SELF_AUDIT_TH_FRUST :- 8 } " # 不満ワード/週 TH_TOOLERR = " ${ SELF_AUDIT_TH_TOOLERR :- 400 } " # tool失敗/週 The first three are static metrics (state at this exact moment); the last two are dynamic metrics (trends since the previous run). That distinction maps directly onto how each one is measured, as described below. Overall design: a thr

SpaceX will likely attempt to catch Starship back at the launch pad on its next flight.

In my previous post, Monitoring Claude Code hook watchdogs with launchd , I set up liveness monitoring for hooks — and immediately ran into the next question: a healthy hook means nothing if the product behind it is down. What I really wanted was a single page I could skim in five minutes every morning and know that everything is fine. That page is daily-brief.sh . launchd runs it three times a day (8:00, 10:30, and at login), and it compiles production HTTP probes, hook latency p95, launchd exit codes, 7-day API costs broken down by model, and per-project git status into one Markdown file appended to Obsidian. The problem: checking five places by hand every morning The more you automate, the higher the risk that something breaks silently. I used to open all of these manually every morning: The Vercel dashboard (production liveness) launchctl logs (scheduled job failures) Claude Code cost usage git status for each project The hook latency JSONL Just opening them took 3–5 minutes. Two incidents slipped through unnoticed (2026-06-11: GitHub Scout silently going blank, and a server configuration error in the autolike license API). Consolidating everything into one automatically delivered page makes missing things physically impossible. Overall design: 3 triggers → 1 Markdown file → append to Obsidian launchd ├─ StartCalendarInterval: 8:00 ├─ StartCalendarInterval: 10:30 └─ RunAtLoad: true（ログイン時） ↓ ~/.claude/scripts/daily-brief.sh ↓ ~/.claude/logs/daily-brief-YYYYMMDD.md ← 正本ログ ~/.claude/logs/daily-brief-latest.md ← 最新コピー ~/Desktop/Daily Brief/today-brief-YYYYMMDD.md ~/Documents/claude-obsidian/wiki/briefs/daily/today-brief-YYYYMMDD.md Even when the second run fires at 10:30, the marker <!-- daily-brief YYYYMMDD --> prevents duplicate appends (details below). The script opens like this: #!/usr/bin/env bash # launchd で毎日 8:00 / 10:30 / ログイン時 実行（再実行してもマーカーで二重追記しない）。 # 注意: Desktop / ~/Documents(vault) は TCC 保護領域 → plist は /bin/bash 直起動（FDA付与済み）。 # /bin/zsh 経由だと FDA 未付与で書き込

"These are things that tend to be really hard."

The Trump administration is asking the Space Force to do a lot. This will require more launches.

The Trump administration is asking the Space Force to do a lot. This will require more launches.

My previous piece, " Making a launchd Job Unload Itself ," built a job that runs exactly once and then unloads itself. This time it's the mirror image: a pattern designed around the assumption that the job will die mid-run — it fires several slots a day and delivers "retry until it succeeds, then quit immediately on success." Every morning I hand Claude Code the task of updating my Obsidian Vault, and it kept dying partway through — killed by macOS sleep, no network on wake, or a claude timeout. Instead of trying to prevent every failure perfectly, I decided "it can die overnight as long as it's done by the time I wake up" was the more realistic goal, and I redesigned around that. The problem: "started but didn't finish" piles up silently There are three ways a launchd job fails to run to completion. Lid-close sleep (on battery) — caffeinate -s only works on AC power. On battery, the job freezes the instant you close the lid, and gets reaped by timeout after wake. No network — right after wake, WiFi isn't connected yet. git push and claude's API calls time out. claude timeout — an ingest that chews through 28 hours of conversation logs doesn't fit in a single slot and times out (this happened three days in a row, 2026-06-11 to 13). All three can look like "the job started, exit code 0," so you notice late. Overall design: 4 slots + a done-marker The fix is simple: stuff multiple StartCalendarInterval entries into the plist, and at the top of the script check "if today's run already succeeded, exit 0 immediately." <!-- com.shun.vault-auto-ingest.plist (StartCalendarInterval excerpt) --> <key> StartCalendarInterval </key> <array> <dict> <key> Hour </key><integer> 4 </integer><key> Minute </key><integer> 55 </integer> </dict> <dict> <key> Hour </key><integer> 8 </integer><key> Minute </key><integer> 20 </integer> </dict> <dict> <key> Hour </key><integer> 10 </integer><key> Minute </key><integer> 45 </integer> </dict> <dict> <key> Hour </key><integer> 12 </integer><key>

"Missiles are being launched at the joint force every single day in [Operation] Epic Fury."

"Now offloading propellant. Next launch attempt hopefully in a few days."

I've reviewed the launch post-mortems of dozens of indie devs who got hacked after shipping their first SaaS. The common thread isn't bad code. It's a checklist no one handed them before they clicked publish. This is that checklist. Eight items. Each one has: a curl command you can run right now, why the bug matters in plain English, and a concrete fix in under ten lines of code. If you can check all eight green before you launch, you've eliminated the majority of the low-hanging-fruit attack surface on a typical Next.js + Supabase MVP. You're not done with security — but you've moved from "will definitely get popped on launch day" to "a real attacker will have to actually work for it." No sales call required. No consulting firm. Eight items in your terminal before launch. Item 1: Every API endpoint has an auth check How to check: # Test an endpoint without a cookie/token curl -s -o /dev/null -w "%{http_code}" https://your-app.com/api/your-endpoint # Should return 401. If it returns 200, the endpoint is public — intentional? Why it matters: API routes in Next.js are not automatically protected. If you forgot to add getServerSession (or your equivalent auth check) to a route handler, it's open to the internet. The route might not be linked in the UI, but it's reachable. Fix: // At the top of every API route handler const session = await getServerSession ( authOptions ) if ( ! session ) return new Response ( ' Unauthorized ' , { status : 401 }) Run this check for every file under src/app/api/ . Better yet: write a middleware that protects all /api/ routes by default and use an explicit { public: true } annotation for routes that should be unauthenticated. Item 2: Per-tenant data scoping (BOLA / IDOR) How to check: # Log in as user A, grab a resource ID from the response # Then change the cookie/token to user B's and request the same ID curl -s -H "Cookie: your-user-b-session" https://your-app.com/api/items/YOUR-USER-A-ITEM-ID # Should return 403 or 404. If it returns

This flight will put Starship under higher pressure and test out new Starlink satellites in orbit.

Five stories moved the AI-coding world today. None are about a single model winning forever — they are about the ground shifting under who runs the agents and who pays for them. Musk puts Grok 4.5 to work at Tesla and SpaceX Tesla and SpaceX have been told to trial Grok 4.5 . The signal is not the benchmark — it is that a frontier model is being pointed at real engineering and ops inside hardware companies. When a model moves from a chatbot to a mandate inside a manufacturing and launch pipeline, the feedback loop gets brutally honest fast. Perplexity's orchestrator beats Opus on a benchmark Perplexity added Grok 4.5 to its orchestrator and reports beating Opus on the WANDR benchmark. Orchestrators are the quiet winners of this cycle: instead of one model doing everything, a router picks per-subtask. A smaller-or-cheaper mix outperforming a single flagship on a targeted benchmark is the trend to watch — it is how teams cut cost without giving up quality on the hard parts. Meta launches Muse Spark 1.1 at 25% of competitor pricing Meta shipped Muse Spark 1.1 through an API priced at roughly a quarter of what competitors charge. Price is a feature. At 25% of the field, an API becomes the default fallback router for cost-sensitive agents even if it is not the best at everything. Expect orchestrators to slot it in for the boring 80%. ByteDance rolls out Seedream 5.0 Pro ByteDance pushed Seedream 5.0 Pro across multiple platforms. Image generation keeps consolidating into a few vendor-backed models with wide distribution — relevant to coding agents the moment they need to generate UI mockups or assets inline. Cursor builds an "Office Agent" to challenge Anthropic Cursor is building a Sand AI office agent aimed at Anthropic's turf. The coding-agent wars are expanding from "writes code" to "runs the surrounding workflow" — email, docs, tickets. That is the same expansion the open-source side is feeling: oh-my-pi's model hub and OpenClaw's session fleet are both bets that th