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Rams just passed 50,000 Skill downloads. Now it runs on every PR. Rams is automated design review for teams shipping UI without a designer. Native GitHub integration, inline fixes, 100+ rules on typography, spacing, a11y, and AI slop. Opinionated. Automatic. Installs in 60 seconds.

Eli Rousso

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26,092 görüntüleme • 6 ay önce •via X (Twitter)

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Qodo

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$HERMES AGENT NOW HAS AUTOMATION TEMPLATES. COPY-PASTE RECIPES FOR CRON JOBS AND WEBHOOKS. ANY MODEL. ANY DELIVERY PLATFORM. three trigger types: SCHEDULE → runs on a cadence (hourly, nightly, weekly) GITHUB EVENT → fires on PR opens, pushes, issues, CI results API CALL → any external service POSTs JSON to your endpoint all three deliver to Telegram, Discord, Slack, SMS, email, GitHub comments, or local files.Nous Research what templates ship right now: DEVELOPMENT: → nightly backlog triage (label + prioritize new issues) → automatic PR code review (posts review on every PR) → docs drift detection (finds code changes without doc updates) → dependency security audit (daily CVE scan, CVSS >= 7.0) DEVOPS: → deploy verification (smoke tests after every deploy) → alert triage (correlates alerts with recent changes) → uptime monitor (check endpoints every 30 min, notify only when something is down) RESEARCH: → competitive repo scout (monitor competitor PRs daily) → weekly AI news digest (headlines, papers, repos, industry) → daily arXiv scan (saves summaries to your notes) the webhook system is the part most people miss: hermes webhook subscribe github-pr-review \ --events "pull_request" \ --prompt "Review this PR for security, performance, and code quality." \ --skills "github-code-review" \ --deliver github_comment one command. every future PR gets reviewed automatically. the review posts as a comment directly on the PR. two cost-saving details from the docs: 1. use [SILENT] in prompts. "if nothing changed, respond with [SILENT]" prevents notification noise on monitoring jobs. 2. use script-only cron jobs for data collection. a Python script handles HTTP requests and file reads. the agent only sees stdout and applies reasoning. cheaper and more reliable than having the agent fetch. every template is copy-paste ready. every template works with any model. docs: full Hermes agent SOUL MD guide in the article 👇$

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AIDesigner is officially live! I think we can all agree that vibe coded apps look horrible, so I built an AI UI designer that creates actually beautiful UI in seconds. • Stunning designs from the simplest of prompts. • Design, edit, iterate all on a single canvas. • Copy styles from any URL. • Publish in a single click (subdomain or custom). • Designs for both web and mobile. • Export to code and image. Great UI design doesn't have to be difficult. Components, mobile apps, websites, AIDesigner does it all. Try it for free:

Wiz

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AI isn't just changing the tools designers use. It's changing how they build, ship, and stand out. In this episode of Design Review, Stephen Haney, founder of AI-native design tool Paper, joins YC's Aaron Epstein to demo the agent-first workflow that's making Paper one of the fastest-growing design tools since Figma. Using live redesigns of user-submitted websites as examples, they break down the most common AI design tells, show how to fix them in seconds, and explain why the biggest risk for founders isn't moving too slow, it's shipping something that looks like everyone else. 01:04 - What is Paper and why build it? 03:17 - What makes Paper agent-native 05:11 - Demo: Shaders, image generation, and brand design 11:32 - Design-to-code and the new agent stack 16:48 - Design Review: Legion Health 24:11 - How to avoid AI design slop 28:26 - Design Review: Sytex 32:42 - The biggest tells of AI-generated design 37:39 - Design Review: Moreta 41:11 - Can AI learn taste? 43:56 - How Paper uses agents internally 46:52 - Building a community around Paper 49:15 - Lessons from Steven’s first startup 53:30 - What’s next for design and Paper

Y Combinator

119,049 görüntüleme • 2 ay önce

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't. Don't want to spend a dollar for testing this? Kalshi just opened a perps exchange and gives US users $25 free to start ->

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't. Don't want to spend a dollar for testing this? Kalshi just opened a perps exchange and gives US users $25 free to start ->

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Claude Code Templates just hit 100+ Skills on Installing is easy - one click to copy the install command, paste it in your project's .claude folder, done. - 67K npm installs - 13K+ GitHub stars - fully open source Thanks to the community for contributing Skills and components. In the video I show how to add a Data Privacy Compliance Skill to your project.

Claude Code Templates just hit 100+ Skills on Installing is easy - one click to copy the install command, paste it in your project's .claude folder, done. - 67K npm installs - 13K+ GitHub stars - fully open source Thanks to the community for contributing Skills and components. In the video I show how to add a Data Privacy Compliance Skill to your project.

Daniel San

164,913 görüntüleme • 9 ay önce

Introducing Impeccable 3.5, the best way to design in production: iterate on real UI with your AI agent, in the codebase you actually ship. Turns out many popular design skills, including Impeccable and Anthropic's frontend-design, weren't actually very good at...design (the workflow was valuable, but the output didn't magically make LLMs like GPT great designers). We measured it across thousands of generations: 74% of pages used the cream AI-default background, 76% reached for extreme letter-spacing, 90%+ failed the contrast floor. So we started fixing slop systematically, specific to each model. The skill now compiles rules for the exact defects each model makes, instead of shipping one generic file to everyone. The biggest jump is in GPT-5.5 and Codex. Also new: ◆ It now knows the difference between a new project and an existing one. Existing codebase, it reads your design system and preserves your identity. Greenfield, it seeds a fresh palette from 129 hand-curated anchors so every cold start doesn't drift to the same safe colors. ◆ Live Mode is now in beta, and works at two scales. Type a direction into the new Steer bar, or speak it, and the agent reads the whole page and edits it in place. Or pick a single element, steer it with a sub-command, live-edit any copy, and accept the variant straight back to source. Insert mode scaffolds brand-new elements between the ones already there. Recovery survives HMR, hidden heroes, and dev-tool overlays. ◆ A rebuilt anti-pattern detector. Torn off jsdom and onto a real CSS cascade resolver: roughly 20x faster, dependency-free, and now small enough to run inline inside the skill, not just the CLI and extension. 14 new rules, 41 total. ◆ The skill keeps itself current, checking once a day and offering to update. Plus /impeccable init and a bare /impeccable that reads your repo and tells you the next move. Free, open source. Claude Code, Codex, Cursor, and more.

Paul Bakaus

103,451 görüntüleme • 4 ay önce

Claude Code on desktop just added an embedded loop that can run your dev server, view the app, review local changes, and watch pull requests until they merge. It can now preview a running app inside the desktop UI while it iterates on fixes. It can also monitor CI for an open PR and either fix failures or merge when checks go green. Earlier “agentic coding” workflows usually bounced between a terminal, a browser, and GitHub, so the model could not directly see what the app rendered or stay attached to CI results without manual babysitting. The new server preview flow starts and stops dev servers from a Preview control, shows the app in an embedded browser, reads logs, and can interact with the page to verify changes. That closes a common gap where a model edits code but cannot reliably confirm the UI and runtime behavior match the intent. The local “Review code” step runs before pushing, and it leaves inline comments on the diff so basic bugs and risky changes get caught earlier. For PR monitoring, the desktop app will track status and CI checks, and it can use auto-fix to attempt repairs and auto-merge to land the PR once checks pass, using GitHub tooling under the hood. Session mobility adds a /desktop command to move a CLI session into the desktop app, and sessions can be pushed to the cloud to resume from web or phone.

Claude Code on desktop just added an embedded loop that can run your dev server, view the app, review local changes, and watch pull requests until they merge. It can now preview a running app inside the desktop UI while it iterates on fixes. It can also monitor CI for an open PR and either fix failures or merge when checks go green. Earlier “agentic coding” workflows usually bounced between a terminal, a browser, and GitHub, so the model could not directly see what the app rendered or stay attached to CI results without manual babysitting. The new server preview flow starts and stops dev servers from a Preview control, shows the app in an embedded browser, reads logs, and can interact with the page to verify changes. That closes a common gap where a model edits code but cannot reliably confirm the UI and runtime behavior match the intent. The local “Review code” step runs before pushing, and it leaves inline comments on the diff so basic bugs and risky changes get caught earlier. For PR monitoring, the desktop app will track status and CI checks, and it can use auto-fix to attempt repairs and auto-merge to land the PR once checks pass, using GitHub tooling under the hood. Session mobility adds a /desktop command to move a CLI session into the desktop app, and sessions can be pushed to the cloud to resume from web or phone.

Rohan Paul

33,431 görüntüleme • 7 ay önce

THIS MIT STUDENT IS BUILDING A FULL GAME WITH ANTI-GRAVITY AI EDITOR - ASSETS, TEXTURES, ICONS AND OBJECTS ALL GENERATED ON THE FLY Anti-Gravity - Google's fork of VS Code, previously Windsurf - open on screen generating every game asset in real time as he builds icons, textures, menus, phone UI representations, objects including a horse - all generated on the fly without leaving the editor, without opening Photoshop, without hiring a designer he built this with friends and every asset they need appears the moment they describe it - no asset store, no stock libraries, no waiting for a designer to finish the game might ship on Steam daily streaks, leaderboards, premium upgrades - the same loop that turns any browser game into $21,000/month in subscriptions an MIT student building a Steam game with friends using a free AI editor that generates everything on demand - the barrier to shipping is now just having an idea

THIS MIT STUDENT IS BUILDING A FULL GAME WITH ANTI-GRAVITY AI EDITOR - ASSETS, TEXTURES, ICONS AND OBJECTS ALL GENERATED ON THE FLY Anti-Gravity - Google's fork of VS Code, previously Windsurf - open on screen generating every game asset in real time as he builds icons, textures, menus, phone UI representations, objects including a horse - all generated on the fly without leaving the editor, without opening Photoshop, without hiring a designer he built this with friends and every asset they need appears the moment they describe it - no asset store, no stock libraries, no waiting for a designer to finish the game might ship on Steam daily streaks, leaderboards, premium upgrades - the same loop that turns any browser game into $21,000/month in subscriptions an MIT student building a Steam game with friends using a free AI editor that generates everything on demand - the barrier to shipping is now just having an idea

Cortex

14,007 görüntüleme • 4 ay önce

Introducing 1st full-stack AI Designer An AI agent that can plan, generate graphic assets, Video animation, production UI code all with full context Design like this could easily cost $5~$10k just 1 year ago, but now is possible to deliver in 10 min without any design skills Learnt from Kyle Skelly and I just can't resist to build it in SuperDesign.Dev, very satisfying to have image/video/code gen all in one place with consistent context You can try this on today

Introducing 1st full-stack AI Designer An AI agent that can plan, generate graphic assets, Video animation, production UI code all with full context Design like this could easily cost $5~$10k just 1 year ago, but now is possible to deliver in 10 min without any design skills Learnt from Kyle Skelly and I just can't resist to build it in SuperDesign.Dev, very satisfying to have image/video/code gen all in one place with consistent context You can try this on today

Jason Zhou

32,121 görüntüleme • 10 ay önce

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't.

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't.

sopersone

48,482 görüntüleme • 1 ay önce

Are you kidding me? This is the best website design experience I've had in a long, long time. Shopify just won my heart with this new Winter Edition web design! Seriously, the bar for good design is so high right now. With all the AI slop out there, the only word-of-mouth you can rely on is having great design taste and building a cult around it. Just take Prime Intellect - ultimate design taste. Why wouldn't I send this to my friends or post it online organically? The moat is good design, folks - it's so important with all the AI slop we're seeing today. tobi lutke please give your design team a big big raise!

Are you kidding me? This is the best website design experience I've had in a long, long time. Shopify just won my heart with this new Winter Edition web design! Seriously, the bar for good design is so high right now. With all the AI slop out there, the only word-of-mouth you can rely on is having great design taste and building a cult around it. Just take Prime Intellect - ultimate design taste. Why wouldn't I send this to my friends or post it online organically? The moat is good design, folks - it's so important with all the AI slop we're seeing today. tobi lutke please give your design team a big big raise!

Archie Sengupta

250,690 görüntüleme • 9 ay önce