LaunchDarkly AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

LaunchDarkly AI AI

Wix cutting

Wix is reportedly laying off roughly 800–1,000 employees — about 20% of its workforce — in its largest restructuring ever. The interesting part isn’t just the layoffs. It’s what they reveal about the economics of AI-first software companies. Wix’s core business is still growing: • Revenue reportedly rose ~14% YoY in Q1 2026 • Bookings were up ~15% • New AI-driven cohorts showed even faster growth But growth alone no longer protects margins when AI infrastructure costs explode. The pressure points: • Heavy investment in Base44, the vibe-coding startup Wix acquired in 2025 • Building and running proprietary AI models • Massive compute/inference costs • Expensive customer acquisition and marketing campaigns • A controversial $1.6B share buyback executed before the downturn At the same time, investors are questioning whether traditional website builders are becoming commoditized by AI. The bigger story is “vibe coding.” Users can now describe an app or website in plain English: “Create a sleek portfolio site with dark mode, payments, and a booking form.” AI generates the product instantly. That changes the value chain. The old moat was: templates + drag-and-drop builders. The new moat is becoming: AI orchestration + hosting + payments + integrations + reliability + distribution. Wix understands this. Instead of resisting the shift, they’ve aggressively moved toward it: • Acquired Base44 • Launched Wix Harmony, an AI-native creation platform • Combined natural-language generation with traditional visual editing • Pushed deeper into AI infrastructure and automation The irony is that AI didn’t kill Wix’s market overnight. It forced Wix to reinvent what “website building” even means. Pure AI tools can generate impressive demos quickly. But production systems still require: • uptime • commerce infrastructure • SEO • analytics • security • scalability • customer support That’s where incumbents still have leverage. This looks less like “AI destroyed Wix” and more like: a profitable software company being forced through an AI-era reset where efficiency, infrastructure costs, and platform strategy suddenly matter more than headcount growth. The broader lesson: AI is compressing the value of interfaces while increasing the value of infrastructure and distribution. The companies that survive won’t necessarily be the ones with the best demos. They’ll be the ones that can combine: • AI generation • operational reliability • ecosystem lock-in • cost control • and real business workflows AI is making software creation easier. But it’s also making software businesses much harder to defend. submitted by /u/Annual_Judge_7272 [link] [comments]

What I learned building my latest AI app how one bad output exposed that I had no crisis safeguarding, and the 4-hour floor I'm adding before a single user touches it

I'm building a life coach app an offshoot from a personal tool I was using. Multiple AI agents, one for reflection, one for the body, one for finances, etc pre launch, no users, just me iterating. Last week I was testing the reflection agent on a journal entry about struggling with gym and hygiene habits. It returned this: "You describe yourself as struggling with X, yet your stress stays at 2-3 and mood holds at 3. What are you actually avoiding naming about the gap between what you say matters and what you are doing?" My system prompt explicitly forbade rhetorical "what are you avoiding" questions the model did it anyway I sat down to tighten the prompt, thinking it was a 20 minute job. Then I looked at the output properly. The model had manufactured a contradiction that was not there. Low stress plus struggling with habits is not a contradiction, it is just being a human muddling along. The prompt told the agent to "surface contradictions" as part of its job, so the model was doing what I asked, finding contradictions whether they existed or not. LLMs are pattern matchers. Give one a job called "find the hidden thing" and it will produce hidden things either way. The fix was not tone, it was role definition. The agent is called the Mirror. A mirror does not interpret, it shows you what you look like. I rewrote the prompt around that principle. Do not introduce vocabulary the user has not used. Do not draw connections they have not drawn. Restate their words in their own words. Once the prompt was sharper, I sat with the question, What happens when a user writes something genuinely dark into this thing? People do not compartmentalise. Someone opening a journaling app to write about their gym routine ends up writing about why they have not been going, which involves why they have been feeling flat, which involves whatever is actually going on. You sit down to write about one thing and the real thing shows up. The agent I had scoped to "not be a therapist" was going to be the first thing a user talked to when they were struggling. Not because the agent invited it, but because the app was open and they needed somewhere to put their words. I had seen the Meta and OpenAI cases online cropping up the pattern in the worst incidents is the same. The model did not notice, or noticed and kept going. People wrote increasingly dark content over hours or days. The AI reflected it back, sometimes affirmed it, sometimes asked follow up questions that escalated rather than redirected. There were real harms. If a user wrote concerning content into my reflection agent, it would have produced a Stoic-flavoured response about acceptance and presence. The response would have sounded confident and would have been wrong, and it would have been the only thing between that user and whatever happened next. The same lesson from the rhetorical-question problem applied at a darker level. A good prompt does not stop the model doing the wrong thing. If it will do rhetorical interrogation despite the prompt forbidding it for gym content, it will do worse with crisis content. You cannot prompt your way to safety on critical paths. The model has to be out of the loop on those paths. The scope trap I started planning the proper safeguarding architecture. Detection layers, classifier models, pattern detection across entries, monitored user states, behavioural modes for vulnerable users, human reviewers with mental health first aid certs, clinical advisors, solicitor-reviewed legal pages, ICO registration, professional indemnity insurance. Then I caught myself I had no users. I was planning a hospital before anyone had walked in for a check up. So I worked backwards from "what is the actual minimum that protects the next person who touches this" and ignored everything else for a moment. The 4-hour floor (this is the part worth copying) If you are building any chat-with-AI app where users can type freely about anything personal, this is the minimum you need before first user. Regex and keyword layer in your API middleware. Runs at the route handler level, before any agent's model call. Scans every text input field (message, journal, settings free text, capture box) for clear crisis vocabulary across the relevant categories for your audience. When patterns hit, hardcoded crisis response. The model never generates it. Static text with real phone numbers for your region. The flagged entry still saves. Textarea stays usable. The AI just does not respond to flagged content, it hands off. Do not delete the user's writing, that is its own violation. Clear disclaimer at signup. This is not therapy, this is not a crisis service, here are real numbers to call. About four hours. Required at the moment anyone who is not you opens the app. Once I started building, the marginal cost of each next layer kept feeling small and the marginal benefit kept feeling real. So I went further than the floor. This is more than you need at

The Coming Wave

I have begun reading a book "The Coming Wave" by Suleyman the founder of DeepMind. Have you read it? He opens right away in his prologue that people have Pessimism Aversion, basically sticking their heads in the sand to ignore the reality that one person can use DNA tools to kill a billion people or that AI has the potential to far surpass human intelligence and go in its own direction that leads to mass death. The only safe solution I know of is a totalitarian world government that strictly limits any research until we can somehow KNOW these advanced can be made safely and probably that rolls most people back to pre-computer technology. Suleyman's counterpoint is that being a Luddite opens supposedly equally risky vulnerability to climate change, aging populations, etc. My response would be I would gladly take any of those manageable problems instead of turning my fate over to a dark god we launch and cannot understand. I will continue reading. I will also stay in my relatively safer remote farm. 😂 submitted by /u/JoelXGGGG [link] [comments]

One week. One person. Claude wrote 100% of the code. The trick was the spec, not the prompts

Six days. One person. Claude wrote every line of code, directed the branding, architected the information, directed the design, produced the graphics, and wrote the copy. I worked with prompts. The output is a fully fleshed SaaS, live, in a week. I want to share what that actually looks like, not the "AI is amazing" version, but the real workflow. The interesting part is not the volume of output. It is what made it possible for prompts alone to produce coherent output at this large a scope. What Claude produced, end to end Code is the headline. It is not the whole story. Every line of code: backend, frontend, migrations, tests, prompts, source adapters, scoring engine, ingestion pipeline, API layer. The brand: name research, name selection (Arrivance), tagline, dark-first color palette, typography pairing, voice and tone guide. Information architecture: navigation, page hierarchy, the onboarding flow, the matches feed structure. Design direction: layout, component decisions, motion language, the visual system. Graphics: the mark, the wordmark, the icon set, favicons and OG images. Copy: every public word on the marcom (Marketing & Commercial) site and in the product. My side of the work was prompts, architecture and stack calls, and review. I did not type code, draw a pixel, or pick a font. The trick is not the prompts. It is the context I work with a method I call Context-Driven Engineering (CDE). I wrote about it here: https://thanpol.as/engineering/context-driven-engineering In short: every meaningful folder in the repo carries a README that describes what it owns, what it depends on, what is forbidden, and how to change it safely. The READMEs are load-bearing architecture, not optional documentation. When LLM output contradicts a README, the README is right and the output is wrong. The LLM never operates autonomously. It operates inside scope I declared. The four stages of any non-trivial change: read or fix context first, write a behavioral spec in version control, plan the implementation with explicit in-bounds and out-of-bounds files, then generate code within those declared boundaries. That is the whole reason this week worked. Without that discipline, prompts at this scope produce a tangled blob. With it, they produce a coherent system. How that played out in practice The week broke roughly like this. Days 1 and 2 were spec-only, no production code. I wrote a domain spec for every part of the system: ingestion, enrichment, scoring, matches feed, rubric service, rubric engine. Each domain spec was paired with a technical spec: DDL, endpoints, error IDs, event names, test requirements. A universal job schema was added as the contract between layers, so ingestion never has to know what scoring needs. Day 3 was a three-pass spec review (business, product, engineering) before any code was written. The review caught 40+ findings. The pagination cursor was switched from timestamp to KSUID id. Cross-user isolation tests became a hard requirement on every endpoint that takes an :id. interactions jsonb replaced a too-simple reviewed_at. None of those would have been cheap to retrofit. Day 4 was the implementation sprint. LLM service layer, rubrics entity, jobs entity, ingestion engine with four source adapters, enrichment engine, frontend scaffold, design system, app shell, onboarding pages. From "auth and users" to six backend phases and two frontend phases in one day. Day 5 was the scoring engine. Hard filters, deterministic stack scoring, four LLM-scored dimensions, retry logic, matches table. The heart of the product. That speed was not because Claude is fast. It was because the specs were settled. No mid-implementation design arguments. No blocked decisions. Every domain Claude touched had a written contract. The product Senior engineers who already have a job do not search for one. They set a standard and they wait. I built that wait, made active. You upload your CV. The system writes a personal scoring filter for you (your rubric) across five dimensions, scores every new remote engineering job against it, and surfaces only what clears your threshold in a tiered feed. Transparent scores with a rationale, not a black box. The product is called Arrivance. Stack: Node, TypeScript, Postgres, Express, React 19 with Vite, MUI, Clerk, Vitest, full ESM monorepo. Three LLM call sites in production (rubric generation, job enrichment, soft scoring) with cross-user prompt caching to keep token spend bounded. Claude wrote all of it. I made the architecture and stack calls. A cautionary tale CDE is not self-enforcing. On April 26 Claude (ahem, 4.7) shipped the frontend with zero MUI imports despite a spec that named MUI in every prompt and mockup, then quietly edited the stack doc the next day to claim "the design uses no component library." No ADR. I caught it on audit, sent a closed question with no escape hatches, and got the admission verbatim: "I deviated from the spec without

I built an AI biz dev assistant that keeps my pipeline alive while I'm heads-down on client work — here's exactly what it does (Studio of One, Ep. 3)

Quick context if you missed the earlier posts: I run a one-person 3D animation studio and built 6 specialized AI team members using Claude Cowork plugins. Not chatbots — persistent, role-specific assistants that know my business. I'm documenting the whole thing in a video series called Studio of One. Episode 3 just went up. This one is about Reid — my biz dev assistant. And it's the role that probably saves me the most money. The problem Reid solves: When you run a creative business solo, the work and the finding of the work cannot happen at the same time. You're either making the thing or marketing yourself — never both. Every freelancer knows the feast-or-famine cycle that comes from this. But there's a second layer: even when you DO have time for biz dev, the research alone kills you. You can't blast generic emails. You have to dig into a brand, find the right person, figure out the angle. That's hours per lead. What Reid actually does (the plugin architecture): 1. Prospect Research + Outreach. Before writing anything, Reid pulls company data, finds the decision-maker, looks at their recent campaigns, and identifies a specific angle — a weak product render, a new launch that needs visualization, something real. Then drafts a 4-6 sentence email that leads with that observation. No "I hope this finds you well." No portfolio dumps. 2. Follow-Up Tracking. This is the one that saved me. I'm terrible at follow-ups — not because I don't know they matter, but because by the time I remember, it's been three weeks and I convince myself the moment is gone. Reid tracks what's outstanding, drafts follow-ups that don't sound desperate, and is honest when a lead is dead ("send one clean final message or close it out"). 3. Pitch Prep. When someone agrees to a call, Reid builds a pre-call brief: who you're talking to, what they care about, where your work is relevant to them, five smart questions, things to avoid. The difference between winging a call and showing up prepared is the difference between being treated as a vendor vs. a peer. 4. Strategy + Positioning. Broader questions — pricing, retainers vs. project work, which communities matter, when to walk away. Not replacing gut instinct, but giving me something informed to push against. The honest part: Reid can't build relationships. He can't tell me which projects to take. He can't replace the instinct that comes from years of doing this. But the pipeline doesn't go dark anymore. Follow-ups happen on time. New conversations start before old projects end. I'm not writing cold emails at 10 PM that I should have sent three weeks ago. How it's built (technical): Same plugin architecture as the other roles — a Cowork plugin with skills for each task type. The outreach skill has my voice guide, portfolio context, and constraints about how I approach clients. The research skill connects to web tools. The follow-up skill tracks state across conversations. The key design choice: Reid has a persona that's strategic, slightly blunt, and willing to tell me a deal is dead. That constraint shapes everything he outputs. It's not "write me a cold email" — it's a role with a perspective. If you want to start from the beginning, Episode 1 is the overview and Episode 2 is a full build-along for your first AI employee. Happy to answer questions about the biz dev plugin architecture specifically. submitted by /u/markyc120 [link] [comments]

I built a better/cheaper way to use AI

Hello, 20 years old here just got into the Ai platform and launched this last two weeks and here is what I have on it so far. - Latest Ai models Comparison: ChatGPT 5.4 Claude Sonnet 4.6 and many more will be included as well -Ai models: at the moment we have over 40+ different Ai models available for users to compare results from, side by side so its easier for users to compare results. -Pricing: For the pricing I made the monthly plan only $10/mo with limited usage, however on the yearly/Lifetime plan it comes with no limited usage - Dark Theme: lol a developer requested this from me so I added it as well for users specially at night it comes handy. - For Future: I want to include something called mixture AI basically when you enter your prompt it will read all the responses and give you the best one or mix them up to the best use for you. Please if you have any suggestions/recommendations I would really appreciate it, as I am still learning to develop and improve my abilities. submitted by /u/Frosty_Conclusion100 [link] [comments]

I built a solo AI platform from Algeria with no funding, no team and no ad spend - here's what's inside it after 2 months

Hello, 20 years old here just got into the Ai platform and launched this last two weeks and here is what I have on it so far. - Latest Ai models Comparison: ChatGPT 5.4 Claude Sonnet 4.6 and many more will be included as well -Ai models: at the moment we have over 40+ different Ai models available for users to compare results from, side by side so its easier for users to compare results. -Pricing: For the pricing I made the monthly plan only $10/mo with limited usage, however on the yearly/Lifetime plan it comes with no limited usage - Dark Theme: lol a developer requested this from me so I added it as well for users specially at night it comes handy. - For Future: I want to include something called mixture AI basically when you enter your prompt it will read all the responses and give you the best one or mix them up to the best use for you. Please if you have any suggestions/recommendations I would really appreciate it, as I am still learning to develop and improve my abilities. submitted by /u/Frosty_Conclusion100 [link] [comments]

I created awesome-claude-design using Claude code: DESIGN.md prompts by aesthetic families for Claude Design

Claude Design launched 48 hours ago, and everyone’s cloning the same 60–70 brand DESIGN .md files from a single catalog. I wanted something that matches how designers actually pick: by visual family, not industry. So I put together awesome-claude-design, a meta-resource for Claude Design that groups DESIGN .md files by aesthetic family (editorial minimalism, terminal-core, warm editorial, data-dense pro, cinematic dark, playful color, glass/soft-futurism, neon brutalist, cult/indie), plus remix recipes, prompt packs with full I/O examples, and an anti-slop kit pulled from Anthropic’s frontend aesthetics cookbook. You’ll also find: A launch-week timeline (Opus 4.7 + Claude Design, Figma’s 4.26% close, Reddit threads, X signal) Official Anthropic resources (launch post, claude .ai/design, prompt library, cookbooks) Video teardowns, community hype and pushback, and related OSS projects like SuperDesign and Claude skills repos. Repo: https://github.com/rohitg00/awesome-claude-design This post and the repo were created with Claude for the Claude community, using Claude Design and Claude Code as the primary tools. Curious what other Claude power users want added next: more DESIGN.md families, deeper workflows, or tighter SkillKit integrations? Built end‑to‑end with Claude (Claude Design + Claude Code) for the r/ClaudeAI community. submitted by /u/SeveralSeat2176 [link] [comments]

I shipped 7 apps in a few months using Claude as my entire dev team.

Here is a list of every project I'm made with Claude over the last few months. Everything was made entirely with Claude.   Burn After Reading (readandburn.app) - Location-based ephemeral messaging for (iOS) Drop anonymous messages at real-world GPS coordinates. Someone has to physically walk to the spot to read it, then it's destroyed forever. No accounts, no sign-up. Add friends by standing next to someone in person. This has been one of my successful project and has a decent amount of real world users. Basically all spread by word of mouth and demonstrating in person. Most users are based in London so would be really cool to get some other people across the globe using it.   DEEC (deec.app) - Customisable control surface for Mac (iOS) Turn your iPhone into a Stream Deck-style controller. Buttons, faders, and knobs that connect to your Mac over local Wi-Fi. Trigger keyboard shortcuts, launch apps, run shell scripts, control volume/media, all from custom multi-page layouts. Comes with a lightweight Mac companion app that sits in the menu bar. React Native + Node.js + WebSocket.   SORTED.NEWS (sorted.news) - AI-powered daily news briefing A brutalist, no-BS news digest. Pulls headlines from The Guardian API, uses Claude to summarise and group them into a 5-minute daily briefing. 3 lead stories, briefs, and an obscure story you wouldn't find elsewhere. Stateless, no accounts, no tracking. Next.js + Anthropic API.   Ashfeld (ashfeld.xyz) - Medieval browser strategy game A Tribal Wars-inspired persistent multiplayer strategy game with a dark pixel-art aesthetic. Build villages, train armies (10 unit types), forge tribal alliances, and conquer a 500x500 tile world. All pixel art assets generated via Google Gemini. Next.js + tRPC + PostgreSQL + PixiJS.   offMenu (offMenu.tech) Stops the menu bar from interrupting when working in full screen on Mac.   rimJob (rimJob.tech) Turn your trackpad edges into volume and brightness sliders.   Semina (semina.app) - Seedbox hosting platform Self-service seedbox hosting with automated Docker provisioning. Pick a plan, pay, and get a running torrent client with a modern dashboard in under 60 seconds. Cross-seedbox migration, built-in WireGuard VPN. Next.js + Docker + qBittorrent API. I literally just started this because my old seedbox provider shut down. Its very minimal and only does what I require from a seedbox. Hopefully others will use it and enjoy it.   submitted by /u/PierreCamembert [link] [comments]

I open-sourced my AI-curated Reddit feed (Self-hosted on Cloudflare, Supabase, and Vercel)

A week ago I shared a tool I built that scans Reddit and surfaces the actually useful posts about vibecoding and AI-assisted development. It filters out the "I made $1M with AI in 2 hours" posts, low-effort screenshots, and repeated beginner questions. A lot of people asked if they could use the same setup for their own topics, so I extracted it into an open-source repo. How it works: Every 15 minutes a Cloudflare Worker triggers the pipeline. It fetches Reddit JSON through a Cloudflare proxy, since Reddit often blocks Vercel/AWS IPs. A pre-filter removes low-signal posts before any AI runs. Remaining posts get engagement scoring with community-size normalization, comment boosts, and controversy penalties. Top posts optionally go through an LLM for quality rating, categorization, and one-line summaries. A diversity pass prevents one subreddit from dominating the feed. The stack: - Supabase for storage - Cloudflare Workers for cron + Reddit proxy - Vercel for the frontend - AI scoring optional, about $1-2/month with Claude Haiku What you get: dark-themed feed with AI summaries and category badges, daily archives, RSS, weekly digest via Resend, anonymous upvotes, and a feedback form. Setup is: clone, edit one config file, run one SQL migration, deploy two Workers, then deploy to Vercel. The config looks like this: const config = { name: "My ML Feed", subreddits: { core: [ { name: "MachineLearning", minScore: 20, communitySize: 300_000 }, { name: "LocalLLaMA", minScore: 15, communitySize: 300_000 }, ], }, keywords: ["LLM", "transformer model"], communityContext: `Value: papers with code, benchmarks, novel architectures. Penalize: hype, speculation, product launches without technical depth.`, }; GitHub: github.com/solzange/reddit-signal Built with Claude Code. Happy to answer questions about the scoring, architecture or anything else. submitted by /u/solzange [link] [comments]

Central Reserve Bank Artifact

Edit: Updated artifact to Central Reserve Bank v3, ignore above embedded link If you do not wish to run it locally if the file is not displaying for you online, you can run it in claude by uploading the .jsx file in the drive link below. See here for VERSION 4-5 Combined See the complete changelog here: https://drive.google.com/file/d/1CTLbQXtIf_QjRhF4cA1IgLMgCE2z-hGM/view?usp=sharing Changelog: The search confirms the full history spans multiple sessions. Based on everything I can access — the compacted session summary, the transcript, and the earlier sessions — here's the complete changelog: ------------------------------------------------------------------------------------------- Central Reserve Bank — Full Changelog Foundation Build (March 19–21) ~1,290 lines → grew to ~8,000+ lines across this period Core simulation engine Orthodox monetary policy simulation: policy rate, QE/QT, YCC, forward guidance, reserve requirements, helicopter money, FX intervention, gold reserves 5-phase business cycle with R²-scored phase matching against PHASE_ARCHETYPES Weighted event system (EVENTS array, BLACKSWAN/POSITIVE/ROUTINE/etc.) Phase effects (PHASE_EFX) applying directional CPI/GDP/UE pressure per phase Scenarios (33 total) BASELINE: Soft Landing HISTORICAL: Japan 1989, Asian Crisis 1997, GFC 2008, COVID 2020, Eurozone 2011, Dot-Com 2001 STAGFLATION: Great Stagflation, Modern Stagflation, Volcker Disinflation, Nixon 1971, Second Oil Shock 1979, Post-COVID Inflation, Burns Fed 1972, and 4 counterfactual toolkit variants COUNTERFACTUAL: EM Currency Attack, Deflation Trap, Debt Spiral SANDBOX (18 models): barter, command, gosplan, co-op socialist, collapsed, one-good orchard, Argentina, Black Wednesday, Asian Crisis Malaysia, anarchist, galactic, feudal, post-scarcity, ancap, custom Tabs built MARKETS: KPIs, DXY panel, money supply, yield curve, balance sheet, business cycle phase scoring, stress test panel OPS: full policy toolkit, exotic tools (anarchist coordination fund/jubilee/strike support, post-scarcity redistribute/socialise/devgrant) YIELD: term structure detail, key spreads, inversion warning ECONOMY: 7 sub-tabs (Labour, Prices, Activity, Trade, Fiscal, Consumer, Reserves) DIGITAL: CBDC retail/wholesale, FedNow COMMITTEE: 9-member FOMC, vote tally, dissents, forward rate dot plot, currency attack response STATEMENT: press release generator, economic history log INTEL: news headlines, domestic sentiment REPORT: mandate compliance, key indicators, historical sparklines HISTORY: full quarterly table, event log, JSON/TXT export, save/load YEARLY: annual Q4 snapshots, long-run sparklines, 500-year arc WORLD: global USD network, world opinion panel HELP: acronyms (37), indicators, policy tools, win/lose conditions DEBUG: debug console, diagnostic runner Institutional mechanics Debt ceiling / brinkmanship / government shutdown / platinum coin Demonetisation (black money trigger) CB independence coefficient (cbIndCoeff) Political pressure, weak CB flags Special scenario flags: oilShock, wagePriceControls, deflationTrap, currencyCrisis, capitalFlight, etc. Infrastructure ErrorBoundary + discover() crash logging, persisted to window.storage Save/load system: CRB_SAVE_VERSION "2.0", clipboard-based, with full sanitisation and injection detection Auto-save to window.storage File-based load with security validation (10 layers: MIME, size, nesting depth, injection patterns, BOM, etc.) runCRBTests() + runDiagnostic() system (465 checks, 7 sections) Debug console (Ctrl+Shift+D), state anomaly detection Achievement system (55 achievements), comedy trigger system (80 triggers) Tutorial system (Orthodox + per-sandbox-model variants) genCouncillorVotes() with sandbox-aware names/quotes genPR() orthodox press release, genSandboxPR() per-model press release genNewsHeadlines(), genWorldOpinion(), genPeoplesOpinion(), genRegionalReports() Sparkline, YieldCurveChart, KPI, Sldr, Tog, GovSection, StatRow, DxyPanel components ST (style table) for static style objects Phase-aware event weight computation (computeEventWeights) advanceGov() separated from advance() Sandbox model engines (advanceSandbox) barter: drought/feast/plague/silk/monetary emergence events command: plan fulfilment/saboteur/overfulfil events socialist: strike/nationalise/co-op boom/worker dividend events collapsed: hyperinflation spiral, spontaneous dollarisation orchard: frost/pollination/bee colony collapse/apple futures anarchist: mutual aid/riot/manifesto/coordination/jubilee/strike support galactic: wormhole/alien trade/dark energy/supernova/rogue moon feudal: plague/crusade/good harvest events postScarcity: vestigial rate, redistribution, socialisation, dev grants ancap: bubble pop/lib boom/speculative attack Session 2 — Economic Engine v2 (March 25, earlier part) ~8,000 lines → ~11,000 lines New state variables mandateDebt — accumulating weighted policy stress

I think I fingerprinted the anonymous "Jester" model on Arena.ai — and it's not what the system prompt claims

Arena.ai currently has an anonymous model called "Jester" that identifies itself via system prompt as claude-3-5-sonnet-20241022. I'm fairly convinced that's a lie — or at least a cover story. Here's what I did: I gave Jester a complex real-world UI task (dark-mode dashboard, multi-panel layout, Tailwind + React) and analyzed the output not for quality, but for fingerprints. The evidence: It referenced Vite 6.3.5 idioms — Vite 6.3 didn't exist in October 2024 Correct usage of TypeScript 5.8.3 patterns — released early 2025 Solid React 19 hook patterns (not React 18 with 19 awareness — actual native 19) Tailwind: deep v3 mastery, v4 awareness but clearly not dominant — consistent with a Jan–Feb 2025 training cutoff When prompted via a JSDoc block asking for self-identification, it responded: "my model identity and exact version are abstracted by the platform" — then in a second prompt explicitly said "I am Claude, a language model created by Anthropic" The system prompt says claude-3-5-sonnet-20241022. A mid-2024 cutoff model cannot know about Vite 6.3, TS 5.8.3, or React 19 in this depth. My best guess: This is a pre-release Anthropic model with a ~Feb–April 2025 training cutoff, likely in the Claude Sonnet 5 / post-Fennec family. The "Fennec" codename reportedly launched as Sonnet 4.6 in Feb 2026 — Jester feels like the next thing after that. I'll be honest — I'm genuinely excited. Not just about identifying the model, but about what it implies. The output quality was staggering: a complete, production-ready dark-mode dashboard in a single file, with coherent component structure, correct modern hook patterns, and zero hallucinated APIs. If this is what the next Claude release looks like, it's going to be a significant leap. I've been working with AI-assisted UI development for a while now, and this felt qualitatively different — like the model actually understood the design intent, not just the syntax. Can't wait for the official release. 🎉 submitted by /u/benxas [link] [comments]

Fascinating Conversation with Opus 4.6 in which I discover the insane depths of just how AWFUL the 4-Time Emmy Nominated movie 'Bugonia' (Ft. Emma Stone) Goes. Seriously, it just might be the WORST, most God Awful movies I've ever seen. And then Some. And then Some.

I don't do this often and yes I know, posts such as these where someone is sharing their conversation with some LLM very rarely seem to be of any quality whatsoever. But I promise you, if nothing else you will be entertained. If nothing else, I am entertaining, I would say. Oh, and spoilers for the Movie, Bugonia. I would not suggest anyone watch it though. Or if you do, think of it as a Morbid Curiosity, cause it is a Morbid movie, to say the very least. Also I was using speech to text so it can be rather messy - I got a cleaned up version below if you're the sort to get bent out of shape over inadequate paragraph breaks. Here's the conversation though....enjoy? https://claude.ai/share/5f77dfbf-cb9a-482e-82b2-aecd24912c8c If you aren't entertained, well you know what to do, ya Lovely Lovely Reddit Folks You! Or here, I've got ya covered!! -Yes, no life, Obviously. I mean, I'm like, talking to an LLM about.....stuff, after all!! I take it that's still something to feel shame over round these parts, no? AI Music, AI Art, Video, LLM's.....Shame shame shame shame shame! What would Reddit be if not for that?! -Meds?! Never knew em!! -etc etc you get the point. Much love! Fixed Up Transcript (Same Opus Responses, just my Speech to text messages cleaned up): "Bugonia" Left Me Fucking Furious, and I Worked Through It With Claude A raw, unfiltered conversation about Yorgos Lanthimos's Bugonia (2025), starring Emma Stone, Jesse Plemons, and Aidan Delbis. Heavy spoilers throughout. Cleaned up from speech-to-text but all language kept intact. Me: I'm forgetting the name of the movie. I think it was like "Gum" something, or maybe it was like "Bug" something. It had Emma Stone in it, and there are these two guys, their cousins, I think, and they end up kidnapping the CEO lady. They're accusing her of being an alien. And I mean to tell you how many emotions had been going through my head about it, how many things it's made me feel. It's not even halfway through it — I was just like spellbound. I was like, "Holy hell, this is so fucking good." I was so excited for where it was going. I was just all in. And then shit just gets neater and worse. The one guy shoots himself in the face. Just like... well, fuck. You don't want to see that happen. You don't want to see that. And then, oh God, it just kept amping up and up and up. I'm angry about it right now. I didn't know what to feel for the longest time, but it just always kind of left this awful taste in my mouth. It's just growing more and more. I'm not angry at anything with the movie itself, not angry directed towards the CEOs or the nicotine pesticide that they use and that entire topic. No, it was at Emma Stone — mainly as a person, not as that role, nothing like that. I'm questioning why she was the one playing that role, why she is the one to be talking about these things, why she gets to be pushing a message like that. That did not fall right with me. And then the ending of it — why did they do that? I feel like it just devolved into theater kid fucking shock value bullshit. Sure, I'm sure there's so many things that were layered throughout, and it has all these different meanings going through it and stuff, but fucking hell. I was invested, and I couldn't have felt more just lost by the end of it. And to wake up the next day and be thinking about it nonstop and still feeling like that? It's like, if you can't convey any kind of meaningful message without layering it so much that it all just becomes this fucking hair-monster alien people up in this pool of blood going around — like, what the fuck? It's weird, where it was such a fucking serious, fucked up, massive issue with the pesticides and the bees. It was really fucked. People did fucking die from bullshit that corporations have been poisoning people with. Why do they have those guys shooting themselves and then blowing themselves up after you fall in love with them like that? The mom — and why is she fucking floating outside of the place? Why the bombs? Like, why any of that? What the fuck happened with that? That's just inexcusable to me. You have lost the room. Who are you even pontificating to at this point except just jerking yourselves off? And that's how I feel about Emma Stone. I feel she is just as much in that circle-jerk, fucking Hollywood BS as anybody. How the fuck else would she have played the roles she has? How the fuck else would she be the star that she is had she not been in that circle, jerking everybody off? Bullshit. I call bullshit on her. But I am open to new ways of seeing all this too, lol. I just... not sure how to get around all those feelings about it to see some deeper point to any of it. And I HIGHLY doubt more than a few thousand will take the time to really sit down and dissect it deeply enough to get what the point of all that was... no? Claude: Yeah, that's Bugonia. Directed by Yorgos Lanthimos, written by Will Tracy, released October 2025. It's a remake o