ai-engineering-from-scratch vs Hopscotch: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of ai-engineering-from-scratch and Hopscotch — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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ai-engineering-from-scratch
rohitg00
Free, open-source curriculum of 500+ hands-on lessons across 20 phases to learn and build AI engineering from math to agents.
Key features
- 523 lessons in 20 phases: A structured curriculum of about 342 hours from setup and math to LLM and agent engineering
- Multi-language code: Lessons implemented in Python, TypeScript, Rust and Julia
- Reusable artifacts: Every lesson ships a prompt, skill, agent or MCP server you can reuse
- Goal-based paths: Learning paths for coding agents, MCP, Agent Skills and product delivery
- Evidence-based workflow: Learners record the command, output and changes for each lesson
- Placement tutor skill: A start-learning skill helps decide where to begin
- Certification onboarding: Guides for Claude certification and the MCP Associate track
- Translations: Landing pages available in a dozen languages
Best for
- A developer new to AI follows Phase 0 and the math foundations to build a base
- An engineer builds production LLM applications using the LLM Engineering phase
- A team learns to write and ship Agent Skills and MCP servers through the tools and protocols phase
- A coding-agent user follows the agent-assisted engineering path to work on real repositories
- A learner prepares for the MCP Associate certification using the onboarding guide
Hopscotch
Hopscotch Labs
OpenAI-compatible LLM gateway giving one API and one balance for 500+ models, with fallbacks and spend limits per key, teammate and workspace.
Key features
- Unified OpenAI-Compatible API: Call 500+ models from Anthropic, OpenAI, Google and others by changing only the base URL, API key and model name in the OpenAI SDK.
- Routing Profiles and Fallbacks: Define an ordered list of backup models so requests fail over automatically when a provider errors or returns a 429.
- Spend Limits: Set resetting credit limits per API key, monthly limits per teammate and workspace, and a cap on how fast the account can spend.
- Activity Log and Usage Analytics: See every request with serving provider, outcome, tokens, cost and latency, export to CSV, and break spend down by model, key and teammate.
- Model Catalog with Upstream Pricing: Each model lists context window and per-million-token price, including multiple upstream providers for open-weight models.
- Side-by-Side Playground: Run one prompt on up to three models and compare answers and cost before changing code.
- Bring Your Own Keys: Use your own provider keys free with no monthly cap alongside Hopscotch credit.
Best for
- Multi-Provider Apps: Letting an application switch between Claude, GPT and Gemini without maintaining separate SDKs, accounts or bills.
- Resilient Production Traffic: Automatically falling back to another model when a primary provider is rate-limited or down.
- Team Budget Governance: Giving each developer or environment its own key with a spend ceiling so costs cannot run away.
- Model Evaluation: Comparing output quality and cost of several models on real prompts in the playground before switching.
- Cost Auditing: Exporting per-request logs to attribute LLM spend by model, provider, key and teammate.