--- title: "Prompt-Engineering-Guide vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dair-ai-prompt-engineering-guide-vs-pguso-agents-from-scratch" tools: ["dair-ai-prompt-engineering-guide", "pguso-agents-from-scratch"] --- # Prompt-Engineering-Guide vs agents-from-scratch *GraphCanon updated Jul 15, 2026* ## Verdict Pick Prompt-Engineering-Guide when prompt-Engineering-Guide is primarily MDX; agents-from-scratch is Python; pick agents-from-scratch when agents-from-scratch is primarily Python; Prompt-Engineering-Guide is MDX. [Prompt-Engineering-Guide](https://www.promptingguide.ai/) reports 76k GitHub stars, 8.4k forks, and 274 open issues, last pushed Mar 11, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 901 stars, 226 forks, and 6 open issues, last pushed Jan 14, 2026. Figures are from public GitHub metadata via [Prompt-Engineering-Guide's repository](https://github.com/dair-ai/Prompt-Engineering-Guide) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [Prompt-Engineering-Guide](/tools/dair-ai-prompt-engineering-guide.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents | Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning. | | Stars | 76,349 | 901 | | Forks | 8,361 | 226 | | Open issues | 274 | 6 | | Language | MDX | Python | | Adopt for | Decision-critical facts for Prompt-Engineering-Guide | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Prompt-Engineering-Guide](/tools/dair-ai-prompt-engineering-guide.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Days since push | 121d | 182d | | Open issues (now) | 274 | 6 | | Owner type | Organization | User | | Full report | [trust report](/tools/dair-ai-prompt-engineering-guide/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: Prompt-Engineering-Guide - **Adopt for:** Decision-critical facts for Prompt-Engineering-Guide ## Choose when ### Choose Prompt-Engineering-Guide if… - Prompt-Engineering-Guide is primarily MDX; agents-from-scratch is Python. - Tags unique to Prompt-Engineering-Guide: agent, agents, chatgpt, deep-learning. - When you seek comprehensive documentation and educational materials specifically focused on the nuance of prompt engineering techniques. ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; Prompt-Engineering-Guide is MDX. - Tags unique to agents-from-scratch: agent-architecture, ai-education, ai-from-scratch, artificial-intelligence. - Leaner open-issue backlog (6). ## When NOT to use Prompt-Engineering-Guide - Avoid using if your focus is entirely on deep-learning frameworks without a need for detailed instructions or examples related to prompt crafting. - Not suitable when you require tools that go beyond guiding materials, such as custom prompts or direct software plugins provided by competitors focused more on practical implementation over learning. ## When NOT to use agents-from-scratch - Last GitHub push was 182 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on agents-from-scratch. - 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. ## Common questions ### What is the difference between Prompt-Engineering-Guide and agents-from-scratch? Prompt-Engineering-Guide: Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents. agents-from-scratch: Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Prompt-Engineering-Guide over agents-from-scratch? Choose Prompt-Engineering-Guide over agents-from-scratch when Prompt-Engineering-Guide is primarily MDX; agents-from-scratch is Python; Tags unique to Prompt-Engineering-Guide: agent, agents, chatgpt, deep-learning; When you seek comprehensive documentation and educational materials specifically focused on the nuance of prompt engineering techniques. ### When should I choose agents-from-scratch over Prompt-Engineering-Guide? Choose agents-from-scratch over Prompt-Engineering-Guide when agents-from-scratch is primarily Python; Prompt-Engineering-Guide is MDX; Tags unique to agents-from-scratch: agent-architecture, ai-education, ai-from-scratch, artificial-intelligence; Leaner open-issue backlog (6). ### When should I avoid Prompt-Engineering-Guide? Avoid using if your focus is entirely on deep-learning frameworks without a need for detailed instructions or examples related to prompt crafting. Not suitable when you require tools that go beyond guiding materials, such as custom prompts or direct software plugins provided by competitors focused more on practical implementation over learning. ### When should I avoid agents-from-scratch? Last GitHub push was 182 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on agents-from-scratch. 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. ### Is Prompt-Engineering-Guide or agents-from-scratch more popular on GitHub? Prompt-Engineering-Guide has more GitHub stars (76,349 vs 901). Stars measure visibility, not whether either tool fits your constraints. ### Are Prompt-Engineering-Guide and agents-from-scratch open source? Yes - both are open-source projects on GitHub (Prompt-Engineering-Guide: MIT, agents-from-scratch: MIT). ### Where can I find alternatives to Prompt-Engineering-Guide or agents-from-scratch? GraphCanon lists graph-backed alternatives at [Prompt-Engineering-Guide alternatives](/tools/dair-ai-prompt-engineering-guide/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([Prompt-Engineering-Guide markdown twin](/tools/dair-ai-prompt-engineering-guide/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/dair-ai-prompt-engineering-guide-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, Prompt-Engineering-Guide or agents-from-scratch? Prompt-Engineering-Guide: Slowing. agents-from-scratch: Slowing. 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 Prompt-Engineering-Guide and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Prompt-Engineering-Guide trust report](/tools/dair-ai-prompt-engineering-guide/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dair-ai-prompt-engineering-guide`](/api/graphcanon/graph?tool=dair-ai-prompt-engineering-guide) - 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/_