标签：#ota

You set up Puppeteer, navigate to a page, call page.screenshot() , and the bottom half of your image is blank placeholder boxes. Welcome to lazy loading. Most modern sites defer images and heavy content until the user scrolls. Your headless browser never scrolls. So those elements never load. Here's how to deal with it. The scroll trick The most common fix is to programmatically scroll down the page before taking the screenshot: async function scrollToBottom ( page ) { await page . evaluate ( async () => { const delay = ms => new Promise ( r => setTimeout ( r , ms )); const distance = 300 ; while ( window . scrollY + window . innerHeight < document . body . scrollHeight ) { window . scrollBy ( 0 , distance ); await delay ( 150 ); } window . scrollTo ( 0 , 0 ); }); } await page . goto ( " https://example.com " , { waitUntil : " networkidle2 " }); await scrollToBottom ( page ); await page . waitForTimeout ( 1000 ); await page . screenshot ({ fullPage : true }); The 150ms delay between scrolls gives IntersectionObserver -based lazy loaders time to trigger. Too fast and you'll scroll past elements before they start loading. That final waitForTimeout after scrolling back to top lets any remaining images finish rendering. Not elegant, but necessary. Why networkidle2 isn't enough You'd think waitUntil: "networkidle2" would handle this. It waits until there are no more than 2 network connections for 500ms. But lazy-loaded images haven't even been requested yet at that point — they're waiting for a scroll event that never happens. networkidle2 only helps with content that loads on page init. For scroll-triggered content, you need the scroll. The loading="eager" override Some sites use the native loading="lazy" attribute. You can override it before images load: await page . evaluateOnNewDocument (() => { Object . defineProperty ( HTMLImageElement . prototype , " loading " , { set : function ( val ) { this . setAttribute ( " loading " , " eager " ); }, get : function () { retu

Anthropic Shipped @claude for Slack. My Team Runs on Telegram. Anthropic just shipped @Claude inside Slack channels. Tag the bot, it reads the thread, does work async, posts back. Nice product. Except roughly 95% of small businesses don't live in Slack — they run on WhatsApp, Telegram, and Gmail. If you're a solopreneur or a 1-to-10-person team, here's the exact four-part recipe I use to run the same pattern in Telegram for under $12/month. What Anthropic actually shipped (and who it's for) Anthropic shipped an enterprise distribution deal wearing a product launch t-shirt. @Claude for Slack lets you tag the bot in a channel or thread, gives it channel memory, connects to your other apps, and returns work asynchronously — but only on Slack Team and Enterprise plans. That's the punchline: it lives where the annual contracts live. Look at the raw user counts. Slack's own reporting puts it around 35–40 million weekly active users globally. WhatsApp is over 2 billion. Telegram is over 900 million. Gmail sits around 1.8 billion. In the 1-to-10-employee segment outside US tech, Slack penetration is single digits. Small teams in Europe, LATAM, and most of Asia coordinate in WhatsApp groups and run pipeline out of Gmail. They are not about to add Slack seats at $15/user/month just to get an @Claude mention. That's a rational call for Anthropic — Slack is where the enterprise procurement motion already exists. It's just not a product for the operator segment. And the pattern they productized is trivially replicable on any messenger with a bot API. Platform Weekly/monthly active users Bot API Cost to run a mention-bot Slack ~35–40M WAU Yes, paid plan $15/user/mo + API Telegram ~900M MAU Yes, free ~$5–12/mo API only WhatsApp Business ~2B MAU Yes, metered $0.005–0.08/conversation + API Gmail ~1.8B MAU Pub/Sub push Free tier + API The four-part recipe (works in any messenger) Every mention-bot is the same four moving parts: a webhook that fires on mention, a context store that ho

The National Highway Traffic Safety Administration said emergency scenes are not "edge cases."

The robotaxi stopped, called 911, and waited for the San Mateo Police to show up.

Early-stage firm Magnify Ventures has raised a $46.6 million Fund II from LPs including Melinda French Gates’ Pivotal Ventures

The company may finally be ready to try to deliver on Elon Musk's years-long promise of launching a robotaxi network of its own.

Aseon Labs, which came out of Y Combinator's 2026 spring cohort, has raised $10 million from Crane Venture Partners and others.

The Department of Transportation wants to remove the brake-pedal requirement for vehicles "designed to be driven exclusively by automated driving systems."

The new Zoox robotaxi has more cushioning, lighter colors, and a better microphone and speaker for communicating with Zoox Support.

Although it's on the smaller side, this electric vehicle is not very chill.

The company has identified at least 13 instances where its robotaxis drove into highway sections closed for construction.

Mobileye apparently wants to own some of the robotaxi market, even if that puts it in direct competition with companies it supplies its self-driving system to.

The service will leverage its Moovit platform to launch in an a US city in 2027.

The incident helps shed some new light on how Waymo treats and stores the footage captured by its robotaxis.

Overview We built the Ota skill because too much "AI repo automation" is still fake confidence. An agent clones a repo, finds a plausible command, edits the right file, and looks smart right up until it does something expensive and stupid. It runs the wrong test path. It installs tools globally because local setup was unclear. It patches around a missing service as if the repo were healthy. That failure is usually blamed on the model. Most of the time it is a repo problem. The repository never made its real operating path explicit enough for the agent to follow without guessing. Ota already gives the repo a machine-readable contract through ota.yaml . The skill exists to teach agents how to behave around that contract: what to trust, what to run, and when to stop instead of improvising. It is not a replacement for ota.yaml . It is not an MCP server. It is not a hidden automation layer. It is the missing operating guide for agents working in Ota repos. Why an Ota skill exists We kept seeing the same pattern: the agent was fast, but the repo was vague. Without a repo-specific operating guide, an agent may see several possible paths: run the command from the README copy the command from CI infer setup from package.json , pyproject.toml , or go.mod run a broad test command because it looks conventional install tools globally because a local command failed patch around a missing service instead of identifying the readiness gap Some of those choices work. Some are dangerous. Some look fine locally and still miss the only verification path that matters. Our view is simple: if a repo has ota.yaml , that file should beat README prose, shell folklore, and whatever command happens to look familiar. Declared tasks, writable paths, setup requirements, and validation commands should be treated as contract facts. The skill exists to make that behavior explicit across agents that support skills. What the skill teaches an agent The official skill lives in ota-run/skills . It is aime

The launch of the Ojai minivan robotaxi comes after years of development and testing, but arrives amid a challenging time for Waymo.