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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Codeamigo logo
Codeamigo
✓ verifiedFree

AI-assisted coding-tutorial tool for learning to code; now unmaintained as its creator moved to another project.

481 visits/mo
Augment Code logo
Augment Code
✓ verifiedPaid

Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.

544K visits/mo
Convex logo
Convex
✓ verifiedFreemium

TypeScript backend-as-a-service with a reactive database, server functions, auth and file storage for full-stack and AI apps.

692K visits/mo20K saves
Pricing

No public pricing

No public pricing

Business: $100/mo flat (up to 50 seats, $100 usage included)

Free trial available

Free & Starter: $0/mo (pay-as-you-go, 1-6 developers)
Professional: $25/developer/mo
Business & Enterprise: $2,500/mo minimum
Core features
  • Weekly newsletter with high-quality insights
  • Deep dives into ML topics
  • Tools used by Machine Learning engineers
  • ML System design course (coming soon)
  • YouTube channel (coming soon)
  • Archive of past articles
  • AI-powered coding tutorials
  • Interactive, developer-style lessons
  • Guided learning with modern tools
  • Demo project walkthrough
  • Waitlist sign-up (courses coming soon)
  • Context Engine for codebase understanding
  • Agents across the full SDLC
  • Model routing / bring-your-own-keys
  • Automated code review and test coverage
  • CLI, MCP and native tool integrations
  • Enterprise security (SOC 2, ISO 42001, SSO)
  • Reactive real-time database
  • TypeScript server functions (queries/mutations/actions)
  • Built-in authentication
  • Cron jobs and backend workflows
  • File storage, text and vector search
  • ACID transactions; open-source/self-host
Use cases
  • Upskilling as a Machine Learning engineer
  • Learning about ML systems at scale
  • Staying updated on the latest ML tools and techniques
  • Understanding ML system design principles
  • Learning to code with an AI assistant
  • Following interactive coding tutorials
  • Practicing with guided project examples
  • Automating PR code review
  • Raising test coverage
  • Incident investigation and remediation
  • Large-scale migrations and onboarding
  • Building real-time reactive apps
  • Backends for AI agents
  • Replacing Firebase or Supabase
  • Full-stack TypeScript development
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