🚂 Railway: the Anti-AWS

Hey folks,

Runway just ran a Turing test on video and we failed. In The Turing Reel, 1,000+ participants watched 20 videos (half real, half AI-generated) and tried to spot the fakes. Over 90% couldn't reliably tell the difference. Overall accuracy was 57.1%, barely above flipping a coin. For animals and architecture, participants mistook AI videos for real ones more often than the reverse. Gen-4.5 produces five-second clips with no post-processing that humans can't distinguish from footage. I don't think i’m telling you anything new, but the stats are backing up whether you need to question every video you see.

Today in AI: 
→ Railway raises $100M to fix AI's deployment problem
→ Google Antigravity: a free agentic IDE
→ How to turn YouTube videos into Reports

Let's dive in..

🚂 Railway Raises $100M to Build the Anti-AWS

Railway just raised $100 million to close the gap between AI wrote my app and my app is running in production. AWS and GCP were built for a world where developers spent weeks setting up infrastructure. That made sense when writing code took months. Now AI agents can scaffold an entire application in an afternoon, and deployment is the new bottleneck.

The numbers:

• 25 million deployments monthly

• 25,000 businesses on the platform

• Zero YAML files, zero Terraform configs

• Push code → production in minutes, not days

Railway started in 2020 with a thesis that's aged well: developers have tolerated the quiet drag of complexity for too long. Endless setup rituals, brittle infrastructure, painful friction between building and shipping. AI coding tools just made that friction more obvious.

If Claude Code or Cursor can generate a working feature in 20 minutes, waiting two days to deploy it feels absurd. Railway is betting that deployment needs to match the speed of AI-assisted development, or it becomes the thing everyone complains about.

What's next for Railway:

• Building tools specifically designed for AI-generated code

• Infrastructure optimized not for how humans write software, but for how AI agents do

For your team: If you're shipping AI-generated code and deployment is the slowest part of your workflow, Railway is worth evaluating.

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🆓 Google's Free Agentic IDE Takes on Cursor and Claude Code

What would you build if IDE costs weren't a factor?

Google launched Antigravity as an agentic development platform a few months ago, and it's currently free. No token limits on Gemini 3 Pro. Full support for Claude Sonnet 4.5 and OpenAI models. Cross-platform on Mac, Windows, and Linux.

What you get:

• Editor view: VSCode-style interface with an agent sidebar

• Manager view: Control center for orchestrating multiple agents working in parallel across workspaces

• Artifacts: Task lists, implementation plans, screenshots, and browser recordings instead of raw tool calls

• MCP server support: Connects to external tools the same way Claude Code does

The Manager view is the interesting part. You kick off tasks and check in later. The agents keep working. For teams running complex refactors or multi-file changes, this solves the one agent at a time bottleneck.

The trust problem in agentic coding has always been the same: how do you know what the AI actually did? Antigravity's answer is Artifacts. You can audit exactly what happened.

The catch:

• It's new, community is smaller

• Extensions and integrations lag behind Cursor

• Pricing TBD (free during preview, but don't expect that to last)

For your team: Worth a pilot for complex refactoring or multi-file tasks where you'd otherwise need multiple Claude Code sessions. The parallel agent coordination actually works.

🎯 How To Turn YouTube Videos Into Reports

1. Find a long-form video you want to digest (conference talk, tutorial, interview)

2. Copy the YouTube URL and paste it into NotebookLM as a source

3. Click "Report → Concept Explainer" and NotebookLM creates a report format to help explain the video for you.

4. Great for breaking down long form video and digesting over a few pages.

🐝 AI Buzz Bits

🎯 24 marketing skills for Claude Code just dropped. Corey Haines released MarketingSkills, a collection of prompts covering landing pages, SEO audits, email sequences, A/B testing, and 140+ growth tactics.

🔍 Google Search now reads your Gmail and Photos. AI Mode's new Personal Intelligence pulls context from your inbox and photo library to personalize search results. Ask about your flight and it checks your email confirmations. Search for "that restaurant from last summer" and it scans your photos.

📊 KPMG: 80% of enterprise apps will have AI agents by year-end 2026. Their Q4 AI Pulse Survey shows the shift from chatbots to autonomous workers is accelerating. The core human skill is now "intent-setting": clearly defining goals and constraints rather than executing tasks end-to-end.

🛠️ Tool Spotlight

1. Traycer — Plan-first AI coding that sits above Cursor or Claude Code. Builds structured specs before any code gets written, then verifies AI output against your constraints.

2. Livedocs — AI data scientist meets reactive notebooks. Upload CSVs or connect your database, ask questions in plain English, get charts and metrics. Cells auto-rerun when dependencies change like a spreadsheet.

3. Agentfield — Kubernetes-style infrastructure for AI agents. Deploy agents as microservices with cryptographic identity, zero-trust IAM, and audit trails.

4. Capacity — Spec-driven coding that generates full-stack React apps from natural language. Define your vision, get an implementation plan, then deploy to Vercel or AWS.

For a full list of 1500+ AI tools, visit our Supertool Directory