Comparison
hello-agents vs ai-engineering-from-scratch-zh
Verdict
Pick hello-agents when license: hello-agents is Other, ai-engineering-from-scratch-zh is MIT; pick ai-engineering-from-scratch-zh when license: ai-engineering-from-scratch-zh is MIT, hello-agents is Other.
Markdown twin · hello-agents alternatives · ai-engineering-from-scratch-zh alternatives
GraphCanon updated today
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Trust & integrity
| Signal | hello-agents | ai-engineering-from-scratch-zh |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1d · github_public_v1 | Active (15d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1d · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of 1d · none | 83 low (83 low) As of today · osv@v1 |
Tagline
- hello-agents
- Course on building intelligent agents from scratch
- ai-engineering-from-scratch-zh
- Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南
Stars
- hello-agents
- 65k
- ai-engineering-from-scratch-zh
- 805
Forks
- hello-agents
- 8.1k
- ai-engineering-from-scratch-zh
- 115
Open issues
- hello-agents
- 144
- ai-engineering-from-scratch-zh
- 4
Language
- hello-agents
- Python
- ai-engineering-from-scratch-zh
- Python
Adopt for
- hello-agents
- hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.
- ai-engineering-from-scratch-zh
- -
Persona
- hello-agents
- -
- ai-engineering-from-scratch-zh
- -
Runtime
- hello-agents
- -
- ai-engineering-from-scratch-zh
- -
License
- hello-agents
- hello-agents is covered under an unconventional license which may require further review before usage.
- ai-engineering-from-scratch-zh
- MIT
Last pushed
- hello-agents
- Jul 10, 2026
- ai-engineering-from-scratch-zh
- Jun 26, 2026
Categories
- hello-agents
- AI Agents, LLM Frameworks
- ai-engineering-from-scratch-zh
- AI Agents, LLM Frameworks, Vector Databases
Trust and health
Maintenance
- hello-agents
- Very active (96%)
- ai-engineering-from-scratch-zh
- Active (82%)
Days since push
- hello-agents
- 0d
- ai-engineering-from-scratch-zh
- 15d
Open issues (now)
- hello-agents
- 144
- ai-engineering-from-scratch-zh
- 4
Owner type
- hello-agents
- Organization
- ai-engineering-from-scratch-zh
- User
Security scan
- hello-agents
- No lockfile
- ai-engineering-from-scratch-zh
- 83 low (83 low)
Full report
- hello-agents
- Trust report
- ai-engineering-from-scratch-zh
- Trust report
Choose hello-agents if…
- License: hello-agents is Other, ai-engineering-from-scratch-zh is MIT.
- Requirements: Min 4 GB RAM; Python knowledge assumed.
- Tags unique to hello-agents: agent, llm, rag, tutorial.
- You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
When NOT to use hello-agents
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application.
- Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
Choose ai-engineering-from-scratch-zh if…
- License: ai-engineering-from-scratch-zh is MIT, hello-agents is Other.
- Tags unique to ai-engineering-from-scratch-zh: agents, ai, ai-agents, ai-engineering.
- Also covers Vector Databases.
When NOT to use ai-engineering-from-scratch-zh
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (datawhalechina/hello-agents) · observed Jul 11, 2026
- GitHub forks (datawhalechina/hello-agents) · observed Jul 11, 2026
- Last push (datawhalechina/hello-agents) · observed Jul 10, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (fancyboi999/ai-engineering-from-scratch-zh) · observed Jul 11, 2026
- GitHub forks (fancyboi999/ai-engineering-from-scratch-zh) · observed Jul 11, 2026
- Last push (fancyboi999/ai-engineering-from-scratch-zh) · observed Jun 26, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: hello-agents 65k · ai-engineering-from-scratch-zh 805 (synced Jul 11, 2026).
Common questions
- What is the difference between hello-agents and ai-engineering-from-scratch-zh?
- hello-agents: Course on building intelligent agents from scratch. ai-engineering-from-scratch-zh: Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南. See the comparison table for live GitHub stats and shared categories.
- When should I choose hello-agents over ai-engineering-from-scratch-zh?
- Choose hello-agents over ai-engineering-from-scratch-zh when License: hello-agents is Other, ai-engineering-from-scratch-zh is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, rag, tutorial; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
- When should I choose ai-engineering-from-scratch-zh over hello-agents?
- Choose ai-engineering-from-scratch-zh over hello-agents when License: ai-engineering-from-scratch-zh is MIT, hello-agents is Other; Tags unique to ai-engineering-from-scratch-zh: agents, ai, ai-agents, ai-engineering; Also covers Vector Databases.
- When should I avoid hello-agents?
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
- When should I avoid ai-engineering-from-scratch-zh?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is hello-agents or ai-engineering-from-scratch-zh more popular on GitHub?
- hello-agents has more GitHub stars (65,432 vs 805). Stars measure visibility, not whether either tool fits your constraints.
- Are hello-agents and ai-engineering-from-scratch-zh open source?
- Yes - both are open-source projects on GitHub (hello-agents: Other, ai-engineering-from-scratch-zh: MIT).
- Where can I find alternatives to hello-agents or ai-engineering-from-scratch-zh?
- GraphCanon lists graph-backed alternatives at hello-agents alternatives and ai-engineering-from-scratch-zh alternatives (hello-agents markdown twin, ai-engineering-from-scratch-zh markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, hello-agents or ai-engineering-from-scratch-zh?
- hello-agents: Very active. ai-engineering-from-scratch-zh: 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 hello-agents and ai-engineering-from-scratch-zh?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; ai-engineering-from-scratch-zh trust report.