Comparison
dust vs agents-from-scratch
Verdict
Pick dust if dust, a TypeScript and Rust-based AI agent platform for workflow acceleration; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Markdown twin · dust alternatives · agents-from-scratch alternatives
GraphCanon updated Sep 20, 2026
13views this month
vs
Trust & integrity
| Signal | dust | agents-from-scratch |
|---|---|---|
| Maintenance | Very active (0d since push) As of Aug 15, 2026 · github_public_v1 | Steady (56d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 15, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- dust
- Custom AI agent platform to speed up your work.
- agents-from-scratch
- Build AI agents locally without relying on frameworks or cloud APIs.
Stars
- dust
- 1.4k
- agents-from-scratch
- 1.0k
Forks
- dust
- 329
- agents-from-scratch
- 251
Open issues
- dust
- 315
- agents-from-scratch
- 4
Language
- dust
- TypeScript
- agents-from-scratch
- Python
Adopt for
- dust
- Dust, a TypeScript and Rust-based AI agent platform for workflow acceleration.
- agents-from-scratch
- agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Persona
- dust
- -
- agents-from-scratch
- -
Runtime
- dust
- -
- agents-from-scratch
- -
License
- dust
- MIT
- agents-from-scratch
- MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes.
Last pushed
- dust
- Aug 15, 2026
- agents-from-scratch
- Jul 25, 2026
Categories
- dust
- AI Agents
- agents-from-scratch
- AI Agents, Developer Tools
Trust and health
Maintenance
- dust
- Very active (96%)
- agents-from-scratch
- Steady (60%)
Days since push
- dust
- 0d
- agents-from-scratch
- 56d
Open issues (now)
- dust
- 315
- agents-from-scratch
- 4
Stars delta
- dust
- +23 (30d)
- agents-from-scratch
- +63 (30d)
Open issues delta
- dust
- +68 (30d)
- agents-from-scratch
- +1 (30d)
Owner type
- dust
- Organization
- agents-from-scratch
- User
Full report
- dust
- Trust report
- agents-from-scratch
- Trust report
Choose dust if…
- dust is primarily TypeScript; agents-from-scratch is Python.
- Tags unique to dust: agents, large-language-models, rust.
- dust ships Docker support for self-hosted deployment.
- Need customization in AI agents with TypeScript and Rust support
When NOT to use dust
- Prefer fully managed AI services without needing low-level tuning options
- Require integration with frameworks that do not support TypeScript or Rust
Choose agents-from-scratch if…
- agents-from-scratch is primarily Python; dust is TypeScript.
- Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs..
- Tags unique to agents-from-scratch: agent-architecture, ai-agents, local-llm, no-framework.
- Also covers Developer Tools.
- You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
When NOT to use agents-from-scratch
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks.
- If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dust-tt/dust) · observed Sep 20, 2026
- GitHub forks (dust-tt/dust) · observed Sep 20, 2026
- Last push (dust-tt/dust) · observed Aug 15, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pguso/agents-from-scratch) · observed Sep 20, 2026
- GitHub forks (pguso/agents-from-scratch) · observed Sep 20, 2026
- Last push (pguso/agents-from-scratch) · observed Jul 25, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: dust 1.4k · agents-from-scratch 1.0k (synced Sep 20, 2026).
Common questions
- What is the difference between dust and agents-from-scratch?
- dust: Custom AI agent platform to speed up your work.. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories.
- When should I choose dust over agents-from-scratch?
- Choose dust over agents-from-scratch when dust is primarily TypeScript; agents-from-scratch is Python; Tags unique to dust: agents, large-language-models, rust; dust ships Docker support for self-hosted deployment; Need customization in AI agents with TypeScript and Rust support.
- When should I choose agents-from-scratch over dust?
- Choose agents-from-scratch over dust when agents-from-scratch is primarily Python; dust is TypeScript; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, local-llm, no-framework; Also covers Developer Tools; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
- When should I avoid dust?
- Prefer fully managed AI services without needing low-level tuning options Require integration with frameworks that do not support TypeScript or Rust
- When should I avoid agents-from-scratch?
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
- Is dust or agents-from-scratch more popular on GitHub?
- dust has more GitHub stars (1,438 vs 1,017). Stars measure visibility, not whether either tool fits your constraints.
- Are dust and agents-from-scratch open source?
- Yes - both are open-source projects on GitHub (dust: MIT, agents-from-scratch: MIT).
- Where can I find alternatives to dust or agents-from-scratch?
- GraphCanon lists graph-backed alternatives at dust alternatives and agents-from-scratch alternatives (dust markdown twin, agents-from-scratch 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, dust or agents-from-scratch?
- dust: Very active. agents-from-scratch: Steady. 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 dust and agents-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dust trust report; agents-from-scratch trust report.