--- title: "ai-getting-started vs ai-engineering-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/a16z-infra-ai-getting-started-vs-rohitg00-ai-engineering-from-scratch" tools: ["a16z-infra-ai-getting-started", "rohitg00-ai-engineering-from-scratch"] --- # ai-getting-started vs ai-engineering-from-scratch *GraphCanon updated Jul 12, 2026* ## Verdict Pick ai-getting-started when ai-getting-started is primarily TypeScript; ai-engineering-from-scratch is Python; pick ai-engineering-from-scratch when ai-engineering-from-scratch is primarily Python; ai-getting-started is TypeScript. [ai-getting-started](https://ai-getting-started.com/) reports 4.1k GitHub stars, 663 forks, and 16 open issues, last pushed Aug 21, 2024. [ai-engineering-from-scratch](https://aiengineeringfromscratch.com) has 38k stars, 6.3k forks, and 96 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [ai-getting-started's repository](https://github.com/a16z-infra/ai-getting-started) and [ai-engineering-from-scratch's repository](https://github.com/rohitg00/ai-engineering-from-scratch). | | [ai-getting-started](/tools/a16z-infra-ai-getting-started.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Tagline | A Javascript AI getting started stack for weekend projects, including image/text models, vector stores, auth, and deployment configs | Learn it. Build it. Ship it for others. | | Stars | 4,141 | 37,922 | | Forks | 663 | 6,329 | | Open issues | 16 | 96 | | Language | TypeScript | Python | | Adopt for | - | Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Vector Databases, Inference & Serving, Computer Vision | LLM Frameworks, AI Agents, Developer Tools, Computer Vision | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-getting-started](/tools/a16z-infra-ai-getting-started.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 688d | 15d | | Open issues (now) | 16 | 96 | | Owner type | Organization | User | | Security scan | 31 low (31 low) | No MCP manifest | | Full report | [trust report](/tools/a16z-infra-ai-getting-started/trust.md) | [trust report](/tools/rohitg00-ai-engineering-from-scratch/trust.md) | ## Decision facts: ai-engineering-from-scratch - **Pricing:** freemium - The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up - **Adopt for:** Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. ## Choose when ### Choose ai-getting-started if… - ai-getting-started is primarily TypeScript; ai-engineering-from-scratch is Python. - Tags unique to ai-getting-started: typescript. - Also covers Vector Databases, Inference & Serving. - ai-getting-started ships Docker support for self-hosted deployment. ### Choose ai-engineering-from-scratch if… - ai-engineering-from-scratch is primarily Python; ai-getting-started is TypeScript. - Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up. - Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm. - Also covers LLM Frameworks, AI Agents, Developer Tools. - When you want to start with foundational knowledge and learn the intricacies behind AI systems. ## When NOT to use ai-getting-started - Last GitHub push was 689 days ago (dormant maintenance, Aug 21, 2024). Validate activity before betting a new project on ai-getting-started. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use ai-engineering-from-scratch - If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. - When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ## Common questions ### What is the difference between ai-getting-started and ai-engineering-from-scratch? ai-getting-started: A Javascript AI getting started stack for weekend projects, including image/text models, vector stores, auth, and deployment configs. ai-engineering-from-scratch: Learn it. Build it. Ship it for others.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-getting-started over ai-engineering-from-scratch? Choose ai-getting-started over ai-engineering-from-scratch when ai-getting-started is primarily TypeScript; ai-engineering-from-scratch is Python; Tags unique to ai-getting-started: typescript; Also covers Vector Databases, Inference & Serving; ai-getting-started ships Docker support for self-hosted deployment. ### When should I choose ai-engineering-from-scratch over ai-getting-started? Choose ai-engineering-from-scratch over ai-getting-started when ai-engineering-from-scratch is primarily Python; ai-getting-started is TypeScript; Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up; Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm; Also covers LLM Frameworks, AI Agents, Developer Tools; When you want to start with foundational knowledge and learn the intricacies behind AI systems. ### When should I avoid ai-getting-started? Last GitHub push was 689 days ago (dormant maintenance, Aug 21, 2024). Validate activity before betting a new project on ai-getting-started. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid ai-engineering-from-scratch? If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ### Is ai-getting-started or ai-engineering-from-scratch more popular on GitHub? ai-engineering-from-scratch has more GitHub stars (37,922 vs 4,141). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-getting-started and ai-engineering-from-scratch open source? Yes - both are open-source projects on GitHub (ai-getting-started: MIT, ai-engineering-from-scratch: MIT). ### Where can I find alternatives to ai-getting-started or ai-engineering-from-scratch? GraphCanon lists graph-backed alternatives at [ai-getting-started alternatives](/tools/a16z-infra-ai-getting-started/alternatives) and [ai-engineering-from-scratch alternatives](/tools/rohitg00-ai-engineering-from-scratch/alternatives) ([ai-getting-started markdown twin](/tools/a16z-infra-ai-getting-started/alternatives.md), [ai-engineering-from-scratch markdown twin](/tools/rohitg00-ai-engineering-from-scratch/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/a16z-infra-ai-getting-started-vs-rohitg00-ai-engineering-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-getting-started or ai-engineering-from-scratch? ai-getting-started: Dormant. ai-engineering-from-scratch: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for ai-getting-started and ai-engineering-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-getting-started trust report](/tools/a16z-infra-ai-getting-started/trust); [ai-engineering-from-scratch trust report](/tools/rohitg00-ai-engineering-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=a16z-infra-ai-getting-started`](/api/graphcanon/graph?tool=a16z-infra-ai-getting-started) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_