--- title: "orloj vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/orlojhq-orloj-vs-pguso-agents-from-scratch" tools: ["orlojhq-orloj", "pguso-agents-from-scratch"] --- # orloj vs agents-from-scratch *GraphCanon updated Sep 20, 2026* ## Verdict Pick orloj if orloj is an orchestration runtime for multi-agent AI systems that schedules and executes agents defined in YAML files; 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. [orloj](https://orloj.dev) reports 121 GitHub stars, 18 forks, and 39 open issues, last pushed Sep 11, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 1.0k stars, 251 forks, and 4 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [orloj's repository](https://github.com/OrlojHQ/orloj) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [orloj](/tools/orlojhq-orloj.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | An orchestration runtime for multi-agent AI systems. | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 121 | 1,017 | | Forks | 18 | 251 | | Open issues | 39 | 4 | | Language | Go | Python | | Adopt for | Orloj is an orchestration runtime for multi-agent AI systems that schedules and executes agents defined in YAML files. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 - The Apache License, Version 2.0 grants permission to use, study, change, and distribute the software -- commercially or non-commercially. | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [orloj](/tools/orlojhq-orloj.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 56d | | Open issues (now) | 39 | 4 | | Stars delta | +8 (30d) | +63 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/orlojhq-orloj/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: orloj - **Requirements:** The tool is designed with a strong emphasis on declarative system definitions and orchestration through YAML files. - **Adopt for:** Orloj is an orchestration runtime for multi-agent AI systems that schedules and executes agents defined in YAML files. - **License detail:** Apache-2.0 - The Apache License, Version 2.0 grants permission to use, study, change, and distribute the software -- commercially or non-commercially. ## Decision facts: agents-from-scratch - **Requirements:** Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs. - **Adopt for:** 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. - **License detail:** MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. ## Choose when ### Choose orloj if… - orloj is primarily Go; agents-from-scratch is Python. - License: orloj is Apache-2.0, agents-from-scratch is MIT. - Requirements: The tool is designed with a strong emphasis on declarative system definitions and orchestration through YAML files.. - Tags unique to orloj: agent-framework, agentic-ai, agentic-orchestration, ai-governance. - orloj ships Docker support for self-hosted deployment. - You need an orchestration service specifically designed for managing interactions among multiple AI agents where production-grade operation is critical. ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; orloj is Go. - License: agents-from-scratch is MIT, orloj is Apache-2.0. - 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, llm, local-llm, no-framework. - 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 orloj - If your multi-agent system does not benefit from the YAML-based orchestration model or if you require a non-Go runtime environment. - When governance functionalities for your AI systems are less critical as Orloj's governance capabilities might be overkill for simpler applications. ## 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. ## Common questions ### What is the difference between orloj and agents-from-scratch? orloj: An orchestration runtime for multi-agent AI systems.. 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 orloj over agents-from-scratch? Choose orloj over agents-from-scratch when orloj is primarily Go; agents-from-scratch is Python; License: orloj is Apache-2.0, agents-from-scratch is MIT; Requirements: The tool is designed with a strong emphasis on declarative system definitions and orchestration through YAML files.; Tags unique to orloj: agent-framework, agentic-ai, agentic-orchestration, ai-governance; orloj ships Docker support for self-hosted deployment; You need an orchestration service specifically designed for managing interactions among multiple AI agents where production-grade operation is critical. ### When should I choose agents-from-scratch over orloj? Choose agents-from-scratch over orloj when agents-from-scratch is primarily Python; orloj is Go; License: agents-from-scratch is MIT, orloj is Apache-2.0; 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, llm, local-llm, no-framework; 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 orloj? If your multi-agent system does not benefit from the YAML-based orchestration model or if you require a non-Go runtime environment. When governance functionalities for your AI systems are less critical as Orloj's governance capabilities might be overkill for simpler applications. ### 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 orloj or agents-from-scratch more popular on GitHub? agents-from-scratch has more GitHub stars (1,017 vs 121). Stars measure visibility, not whether either tool fits your constraints. ### Are orloj and agents-from-scratch open source? Yes - both are open-source projects on GitHub (orloj: Apache-2.0, agents-from-scratch: MIT). ### Where can I find alternatives to orloj or agents-from-scratch? GraphCanon lists graph-backed alternatives at [orloj alternatives](/tools/orlojhq-orloj/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([orloj markdown twin](/tools/orlojhq-orloj/alternatives.md), [agents-from-scratch markdown twin](/tools/pguso-agents-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/orlojhq-orloj-vs-pguso-agents-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, orloj or agents-from-scratch? orloj: 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 orloj and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [orloj trust report](/tools/orlojhq-orloj/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=orlojhq-orloj`](/api/graphcanon/graph?tool=orlojhq-orloj) - 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/_