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Less than a week before Meta's lawyers were set to return to a Los Angeles courtroom, the plaintiff accusing the platform of inflicting harm dropped the case. Brought by 15-year-old Florida plaintiff going by initials R.K.C., the case was set to be the second in a set of bellwether trials meant to test legal arguments […]

You can now gift games without a Steam account and sort your wishlist into categories.

Google's cloud business is thriving, as companies adopting its AI and AI infrastructure services help the tech giant to report record profits.

Undetectable AI copilot for live meetings Discussion | Link

Build better color palettes. Ship complete color systems. Discussion | Link

Tired of squinting at VS Code’s stacked merge editor? MergeForge brings a JetBrains-style three-pane conflict resolver to VS Code and Cursor — and pairs it with an AI assistant that actually reads your repository before it suggests a fix. The problem We’ve all been there. You’re halfway through a rebase. Git stops. Twelve files are conflicted. You open one in VS Code… and get that familiar stacked layout: Incoming, Current, and a result pane that somehow still feels like a puzzle with half the pieces missing. If you ever used WebStorm or IntelliJ, you know how good merge tools can feel: Your side on the left Their side on the right The result in the middle Gutter arrows that just… work In VS Code land, that flow never quite arrived. You click Accept Current, Accept Incoming, Accept Both, and hope nothing important got flattened. Word-level diffs? Authorship? A clear “who wrote this chunk?” signal? Often missing when you need them most. And when AI entered the chat, a lot of tools treated conflicts like isolated text blobs: “Here are the <<<<<<< markers. Good luck.” But real merges need context. What was the branch trying to do? What does the surrounding file look like? Who touched this last? Without that, “AI resolve” is just confident guessing. I wanted the JetBrains merge experience — inside VS Code and Cursor — with an assistant that behaves more like a careful teammate than a slot machine. So I built it. The solution: MergeForge MergeForge is an open-source VS Code / Cursor extension that turns conflicted files into a proper three-pane visual merge. Layout: Left Center Right Yours (local) Result (editable, seeded from the merge base) Theirs (incoming) Panes scroll together. Chunks connect with bands. Gutter controls let you accept, ignore, or blend sides without fighting the UI. When you’re done, Apply writes the result and stages it with git. If you prefer Cursor, you’re covered too. The editor works the same; for AI features you plug in your own provider key (

The cyclospora diarrhea outbreak isn't an isolated incident. It's part of a pattern of leafy greens wreaking digestive havoc.

Everyone's telling you the same thing right now: update WordPress. Which is, fine, yes, obviously but that's not enough. Patching closes the hole. What is someone is already In your system? So let's actually walk through this properly what to do right now, what to do if you can't patch immediately, and what to do if you think you were already hit. Need more context? I wrote a summarising one here. wp2shell: The Bug That Turned an Empty WordPress Install Into a Shell Aditya Pidurkar Aditya Pidurkar Aditya Pidurkar Follow Jul 22 wp2shell: The Bug That Turned an Empty WordPress Install Into a Shell # wordpress # wp2shell # cybersecurity # cve Add Comment 4 min read S1: Stop assuming you're patched. Go check. WordPress flipped on forced automatic background updates for this one because of how serious it is. That's great, except "forced" doesn't mean "guaranteed", VERIFY IT. Go look at your actual running version right now: In the dashboard: wp-admin > Updates Via WP-CLI, if you have shell access: wp core version You want to see 7.0.2 if you're on the 7.0 line, or 6.9.5 if you're on 6.9. If you see anything else — 6.9.0 through 6.9.4, or 7.0.0/7.0.1 — you're still exposed. Update it now!! Come back when done. A few situations where the forced update quietly doesn't happen, in what I read on internet: Managed hosting environments where the host controls the update pipeline and hasn't pushed it yet Sites with a "disable auto-updates" plugin installed months ago for stability reasons and never revisited wp-config.php with WP_AUTO_UPDATE_CORE explicitly set to false Staging or dev environments nobody thinks of as "production" but that are still internet-facing If any of that describes you, don't wait on the automation. Update manually. S2: If you genuinely can't update right now, here's your stopgap aybe you're facing a compatibility issue, a change freeze, or a custom plugin that isn't ready yet. It happens. If you need a little more time before applying the real fix, here'

Amid all the noise about dockershim, one thing got lost: the everyday workflow of building an image with Docker and running it on Kubernetes never changed. Docker is still an excellent build tool, Kubernetes still runs OCI images, and on Ubuntu the loop is clean. Here it is end to end. 1. A build-friendly Dockerfile Multi-stage keeps the runtime image small and the attack surface low — this matters more on Kubernetes, where you pull the image onto every node that schedules the pod: # build stage FROM golang:1.22 AS build WORKDIR /src COPY go.* ./ RUN go mod download COPY . . RUN CGO_ENABLED = 0 go build -o /out/api ./cmd/api # runtime stage — distroless, no shell, tiny FROM gcr.io/distroless/static:nonroot COPY --from=build /out/api /api USER nonroot:nonroot EXPOSE 8080 ENTRYPOINT ["/api"] 2. Build and push with Docker on Ubuntu Use buildx (bundled with modern Docker) so you can build multi-arch — worth it if any nodes are arm64: docker buildx build \ --platform linux/amd64,linux/arm64 \ -t registry.example.com/api:1.4.2 \ --push . Tag with an immutable version, never rely on :latest . Kubernetes caches images per node; :latest makes "which build is actually running?" unanswerable and breaks rollbacks. 3. A deployment that behaves in production apiVersion : apps/v1 kind : Deployment metadata : name : api spec : replicas : 3 selector : { matchLabels : { app : api } } template : metadata : { labels : { app : api } } spec : containers : - name : api image : registry.example.com/api:1.4.2 # the exact tag you pushed imagePullPolicy : IfNotPresent ports : [{ containerPort : 8080 }] resources : requests : { cpu : " 100m" , memory : " 128Mi" } limits : { memory : " 256Mi" } readinessProbe : httpGet : { path : /healthz , port : 8080 } initialDelaySeconds : 3 livenessProbe : httpGet : { path : /healthz , port : 8080 } initialDelaySeconds : 10 The readinessProbe is the piece people skip and regret: without it, Kubernetes sends traffic to a pod before your app is listening, and

Hi HackerNews! My name is Kayleigh and I am the founder of NextBest, making it easy to see what people recommend online starting with skincare based on reddit. After working in big tech (Snap, Tiktok) the past five years, I founded NextBest because every time I want to buy something I search "best [x] reddit". While I am starting with skincare based on reddit, I do want to expand it to more sources and verticals. Would love any feedback you guys have!

I'm a scrum master. I was a developer ten years ago. I have enough background to discuss design and trade-offs with an LLM — but three months ago I made a deliberate bet on my solo project: I would never read the code. The specs define the tests. The tests control the code. The code is a black box. I'm not claiming this is what everyone should do. But it's my bet, and it forced a system into existence: when nobody reads the code, the process has to carry the trust that a code-reading human normally provides. I've just published that system as a reference implementation: backlog-as-data — the full writeup, the Claude Code skills translated to English, and the CLI source, verbatim from my daily setup. Here's the short version. The backlog is git data, not a document Most agent task-management tools store tasks in a dedicated place — a tasks.json , a database, a backlog/ folder. My bet is different: the backlog is the YAML frontmatter of my spec files. One file per ticket, and the ticket's status is a field — never a location in a document. --- id : PARSE-07 title : Tolerate CRLF in decklist import type : ticket status : todo priority : should exec : model : sonnet effort : think review : light matured : 2026-07-22 --- # PARSE-07 — Tolerate CRLF in decklist import The spec body: design, contracts, test cases. The ticket file IS the spec. Everything below the frontmatter is the spec — written by the LLM, after it has challenged the need I expressed in conversation. The frontmatter is data — owned by a small CLI, mutated only through it. Same file, so they can never drift apart. Why it matters: "move it to Done" is not an operation. LLMs (and humans) mangle documents when a state change means relocating text. Making status a field makes every transition a one-line, idempotent, testable mutation. The board I look at (a small web page on my server, with GitHub deep links to each spec) and the readable markdown view are generated projections , locked by a do-not-edit sentin

If you've ever had to check code or infrastructure against a compliance framework, you know the drill: someone reads a 100-page PDF, then reads your codebase, then makes a judgment call. It's slow, inconsistent, and it can't be automated. So I built a pipeline to fix that — for real. The problem CMMC Level 1 and NIST SP 800-171 Rev 2 are two of the most common compliance frameworks small defense contractors and government-adjacent companies have to meet. Both exist only as dense regulatory text. There's no official machine-readable version. That means every compliance check is manual. Every AI coding assistant reviewing your infrastructure has zero built-in awareness of these requirements. Every CI/CD pipeline has to skip compliance checks entirely or rely on someone remembering to look. ** What I built** A Python pipeline that: Pulls the real regulatory source data — NIST's official CPRT export for SP 800-171, and the verbatim text of 48 CFR § 52.204-21 for CMMC Level 1 Normalizes it into a structured SQLite schema Generates a JSON rule for every single control, with a machine-actionable instruction attached Here's what one rule actually looks like: \ json { "rule_id": "nist_sp_800-171_rev_2_3.1.1", "framework": "NIST SP 800-171 Rev 2", "control_id": "3.1.1", "title": "ACCESS CONTROL — 3.1.1", "requirement": "Limit system access to authorized users, processes acting on behalf of authorized users, and devices.", "agent_guidance": "When generating or reviewing code/infrastructure, ensure compliance with NIST SP 800-171 Rev 2 control 3.1.1. Flag any implementation that does not satisfy: Limit system access to authorized users, processes acting on behalf of authorized users, and devices.", "generated_at": "2026-07-15T16:42:56.026218+00:00" } \ \ That agent_guidance field is the interesting part — it's written specifically to drop straight into an AI coding agent's system prompt as a compliance guardrail. Three ways to actually use this 1. AI coding agent system prompt