chore: sync content to repo

Co-authored-by: kamranahmedse <4921183+kamranahmedse@users.noreply.github.com>

src/data/roadmaps/ai-agents/content/acting--tool-invocation@sHYd4KsKlmw5Im3nQ19W8.md

@@ -5,4 +5,4 @@ Acting, also called tool invocation, is the step where the AI chooses a tool and
 Visit the following resources to learn more:
 
 - [@article@What are Tools in AI Agents?](https://huggingface.co/learn/agents-course/en/unit1/tools)
-- [@article@What is Tool Calling in Agents?](https://www.useparagon.com/blog/ai-building-blocks-what-is-tool-calling-a-guide-for-pms)
+- [@article@What is Tool Calling in Agents?](https://www.useparagon.com/blog/ai-building-blocks-what-is-tool-calling-a-guide-for-pms)

src/data/roadmaps/ai-agents/content/agent-loop@Eih4eybuYB3C2So8K0AT3.md

@@ -5,4 +5,4 @@ An agent loop is the cycle that lets an AI agent keep working toward a goal. Fir
 Visit the following resources to learn more:
 
 - [@article@What is an Agent Loop?](https://huggingface.co/learn/agents-course/en/unit1/agent-steps-and-structure)
-- [@article@Let's Build your Own Agentic Loop](https://www.reddit.com/r/AI_Agents/comments/1js1xjz/lets_build_our_own_agentic_loop_running_in_our/)
+- [@article@Let's Build your Own Agentic Loop](https://www.reddit.com/r/AI_Agents/comments/1js1xjz/lets_build_our_own_agentic_loop_running_in_our/)

src/data/roadmaps/ai-agents/content/anthropic-tool-use@1EZFbDHA5J5_5BPMLMxXb.md

@@ -4,4 +4,4 @@ Anthropic Tool Use lets you connect a Claude model to real software functions so
 
 Visit the following resources to learn more:
 
-- [@official@Anthropic Tool Use](https://docs.anthropic.com/en/docs/build-with-claude/tool-use/overview)
+- [@official@Anthropic Tool Use](https://docs.anthropic.com/en/docs/build-with-claude/tool-use/overview)

src/data/roadmaps/ai-agents/content/api-requests@52qxjZILV-X1isup6dazC.md

@@ -5,4 +5,4 @@ API requests let an AI agent ask another service for data or for an action. The
 Visit the following resources to learn more:
 
 - [@article@Introduction to APIs - MDN Web Docs](https://developer.mozilla.org/en-US/docs/Learn_web_development/Extensions/Client-side_APIs/Introduction)
-- [@article@How APIs Power AI Agents: A Comprehensive Guide](https://blog.treblle.com/api-guide-for-ai-agents/)
+- [@article@How APIs Power AI Agents: A Comprehensive Guide](https://blog.treblle.com/api-guide-for-ai-agents/)

src/data/roadmaps/ai-agents/content/basic-backend-development@VPI89s-m885r2YrXjYxdd.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Introduction to the server-side](https://developer.mozilla.org/en-US/docs/Learn/Server-side/First_steps/Introduction)
 - [@article@What is a REST API? - Red Hat](https://www.redhat.com/en/topics/api/what-is-a-rest-api)
-- [@article@What is a Database? - Oracle](https://www.oracle.com/database/what-is-database/)
+- [@article@What is a Database? - Oracle](https://www.oracle.com/database/what-is-database/)

src/data/roadmaps/ai-agents/content/chain-of-thought-cot@qwdh5pkBbrF8LKPxbZp4F.md

@@ -5,4 +5,4 @@ Chain of Thought (CoT) is a way for an AI agent to think out loud. Before giving
 Visit the following resources to learn more:
 
 - [@article@Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://arxiv.org/abs/2201.11903)
-- [@article@Evoking Chain of Thought Reasoning in LLMs - Prompting Guide](https://www.promptingguide.ai/techniques/cot)
+- [@article@Evoking Chain of Thought Reasoning in LLMs - Prompting Guide](https://www.promptingguide.ai/techniques/cot)

src/data/roadmaps/ai-agents/content/closed-weight-models@tJYmEDDwK0LtEux-kwp9B.md

@@ -4,8 +4,8 @@ Closed-weight models are AI systems whose trained parameters—the numbers that
 
 Visit the following resources to learn more:
 
-- [@article@Open-Source LLMs vs Closed LLMs](https://hatchworks.com/blog/gen-ai/open-source-vs-closed-llms-guide/)
-- [@article@2024 Comparison of Open-Source Vs Closed-Source LLMs](https://blog.spheron.network/choosing-the-right-llm-2024-comparison-of-open-source-vs-closed-source-llms)
 - [@official@Open AI's GPT-4](https://openai.com/gpt-4)
 - [@official@Claude](https://www.anthropic.com/claude)
 - [@official@Gemini](https://deepmind.google/technologies/gemini/)
+- [@article@Open-Source LLMs vs Closed LLMs](https://hatchworks.com/blog/gen-ai/open-source-vs-closed-llms-guide/)
+- [@article@2024 Comparison of Open-Source Vs Closed-Source LLMs](https://blog.spheron.network/choosing-the-right-llm-2024-comparison-of-open-source-vs-closed-source-llms)

src/data/roadmaps/ai-agents/content/code-execution--repl@mS0EVCkWuPN_GkVPng4A2.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@What is a REPL?](https://docs.replit.com/getting-started/intro-replit)
 - [@article@Code Execution AI Agent](https://docs.praison.ai/features/codeagent)
 - [@article@Building an AI Agent's Code Execution Environment](https://murraycole.com/posts/ai-code-execution-environment)
-- [@article@Python Code Tool](https://python.langchain.com/docs/integrations/tools/python/)
+- [@article@Python Code Tool](https://python.langchain.com/docs/integrations/tools/python/)

src/data/roadmaps/ai-agents/content/code-generation@PK8w31GlvtmAuU92sHaqr.md

@@ -4,6 +4,6 @@ Code-generation agents take a plain language request, understand the goal, and t
 
 Visit the following resources to learn more:
 
+- [@official@GitHub Copilot](https://github.com/features/copilot)
 - [@article@Multi-Agent-based Code Generation](https://arxiv.org/abs/2312.13010)
-- [@article@From Prompt to Production: GitHub Blog](https://github.blog/ai-and-ml/github-copilot/from-prompt-to-production-building-a-landing-page-with-copilot-agent-mode/)
-- [@official@GitHub Copilot](https://github.com/features/copilot)
+- [@article@From Prompt to Production: GitHub Blog](https://github.blog/ai-and-ml/github-copilot/from-prompt-to-production-building-a-landing-page-with-copilot-agent-mode/)

src/data/roadmaps/ai-agents/content/context-windows@dyn1LSioema-Bf9lLTgUZ.md

@@ -8,4 +8,4 @@ Visit the following resources to learn more:
 
 - [@article@What is a Context Window in AI?](https://www.ibm.com/think/topics/context-window)
 - [@article@Scaling Language Models with Retrieval-Augmented Generation (RAG)](https://arxiv.org/abs/2005.11401)
-- [@article@Long Context in Language Models - Anthropic's Claude 3](https://www.anthropic.com/news/claude-3-family)
+- [@article@Long Context in Language Models - Anthropic's Claude 3](https://www.anthropic.com/news/claude-3-family)

src/data/roadmaps/ai-agents/content/creating-mcp-servers@1NXIN-Hbjl5rPy_mqxQYW.md

@@ -5,4 +5,4 @@ An MCP server stores and shares conversation data for AI agents using the Model
 Visit the following resources to learn more:
 
 - [@official@Model Context Protocol (MCP) Specification](https://www.anthropic.com/news/model-context-protocol)
-- [@article@How to Build and Host Your Own MCP Servers in Easy Steps?](https://collabnix.com/how-to-build-and-host-your-own-mcp-servers-in-easy-steps/)
+- [@article@How to Build and Host Your Own MCP Servers in Easy Steps?](https://collabnix.com/how-to-build-and-host-your-own-mcp-servers-in-easy-steps/)

src/data/roadmaps/ai-agents/content/dag-agents@Ep8RoZSy_Iq_zWXlGQLZo.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@Airflow: Directed Acyclic Graphs Documentation](https://airflow.apache.org/docs/apache-airflow/stable/concepts/dags.html)
 - [@article@What are DAGs in AI Systems?](https://www.restack.io/p/version-control-for-ai-answer-what-is-dag-in-ai-cat-ai)
-- [@video@DAGs Explained Simply](https://www.youtube.com/watch?v=1Yh5S-S6wsI)
+- [@video@DAGs Explained Simply](https://www.youtube.com/watch?v=1Yh5S-S6wsI)

src/data/roadmaps/ai-agents/content/data-analysis@wKYEaPWNsR30TIpHaxSsq.md

@@ -5,4 +5,4 @@ AI agents can automate data analysis by pulling information from files, database
 Visit the following resources to learn more:
 
 - [@article@How AI Will Transform Data Analysis in 2025](https://www.devfi.com/ai-transform-data-analysis-2025/)
-- [@article@How AI Has Changed The World Of Analytics And Data Science](https://www.forbes.com/councils/forbestechcouncil/2025/01/28/how-ai-has-changed-the-world-of-analytics-and-data-science/k)
+- [@article@How AI Has Changed The World Of Analytics And Data Science](https://www.forbes.com/councils/forbestechcouncil/2025/01/28/how-ai-has-changed-the-world-of-analytics-and-data-science/k)

src/data/roadmaps/ai-agents/content/data-privacy--pii-redaction@rdlYBJNNyZUshzsJawME4.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@GDPR Compliance Overview](https://gdpr.eu/)
 - [@article@Protect Sensitive Data with PII Redaction Software](https://redactor.ai/blog/pii-redaction-software-guide)
-- [@article@A Complete Guide on PII Redaction](https://enthu.ai/blog/what-is-pii-redaction/)
+- [@article@A Complete Guide on PII Redaction](https://enthu.ai/blog/what-is-pii-redaction/)

src/data/roadmaps/ai-agents/content/database-queries@sV1BnA2-qBnXoKpUn-8Ub.md

@@ -4,4 +4,4 @@ Database queries let an AI agent fetch, add, change, or remove data stored in a
 
 Visit the following resources to learn more:
 
-- [@article@Building Your Own Database Agent](https://www.deeplearning.ai/short-courses/building-your-own-database-agent/)
+- [@article@Building Your Own Database Agent](https://www.deeplearning.ai/short-courses/building-your-own-database-agent/)

src/data/roadmaps/ai-agents/content/deepeval@0924QUH1wV7Mp-Xu0FAhF.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@official@DeepEval - The Open-Source LLM Evaluation Framework](https://www.deepeval.com/)
 - [@opensource@DeepEval GitHub Repository](https://github.com/confident-ai/deepeval)
 - [@article@Evaluate LLMs Effectively Using DeepEval: A Pratical Guide](https://www.datacamp.com/tutorial/deepeval)
-- [@video@DeepEval - LLM Evaluation Framework](https://www.youtube.com/watch?v=ZNs2dCXHlfo)
+- [@video@DeepEval - LLM Evaluation Framework](https://www.youtube.com/watch?v=ZNs2dCXHlfo)

src/data/roadmaps/ai-agents/content/email--slack--sms@qaNr5I-NQPnfrRH7ynGTl.md

@@ -5,4 +5,4 @@ Email, Slack, and SMS are message channels an AI agent can use to act on tasks a
 Visit the following resources to learn more:
 
 - [@official@Twilio Messaging API](https://www.twilio.com/docs/usage/api)
-- [@official@Slack AI Agents](https://slack.com/ai-agents)
+- [@official@Slack AI Agents](https://slack.com/ai-agents)

src/data/roadmaps/ai-agents/content/embeddings-and-vector-search@UIm54UmICKgep6s8Itcyv.md

@@ -5,7 +5,4 @@ Embeddings turn words, pictures, or other data into lists of numbers called vect
 Visit the following resources to learn more:
 
 - [@official@OpenAI Embeddings API Documentation](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings)
-- [@article@Understanding Embeddings and Vector Search (Pinecone Blog)](https://www.pinecone.io/learn/vector-embeddings/)
-- [@video@What are Word Embeddings?](https://youtu.be/wgfSDrqYMJ4?si=8bS9_cVChpTzl2z6)
-- [@video@What is a Vector Database? Powering Semantic Search & AI Applications](https://youtu.be/gl1r1XV0SLw?si=StU9dl8yQTNxdDaI)
-- [@video@What is a Vector Database?](https://youtu.be/t9IDoenf-lo?si=QG0WD3di9zIliBPC)
+- [@article@Understanding Embeddings and Vector Search (Pinecone Blog)](https://www.pinecone.io/learn/vector-embeddings/)

src/data/roadmaps/ai-agents/content/episodic-vs-semantic-memory@EfCCNqLMJpWKKtamUa5gK.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@What Is AI Agent Memory? - IBM](https://www.ibm.com/think/topics/ai-agent-memory)
 - [@article@Episodic Memory vs. Semantic Memory: The Key Differences](https://www.magneticmemorymethod.com/episodic-vs-semantic-memory/)
-- [@article@Memory Systems in LangChain](https://python.langchain.com/docs/how_to/chatbots_memory/)
+- [@article@Memory Systems in LangChain](https://python.langchain.com/docs/how_to/chatbots_memory/)

src/data/roadmaps/ai-agents/content/file-system-access@BoJqZvdGam4cd6G6yK2IV.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@Filesystem MCP server for AI Agents](https://playbooks.com/mcp/mateicanavra-filesystem)
 - [@article@File System Access API](https://developer.mozilla.org/en-US/docs/Web/API/File_System_Access_API)
 - [@article@Understanding File Permissions and Security](https://linuxize.com/post/understanding-linux-file-permissions/)
-- [@video@How File Systems Work?](https://www.youtube.com/watch?v=KN8YgJnShPM)
+- [@video@How File Systems Work?](https://www.youtube.com/watch?v=KN8YgJnShPM)

src/data/roadmaps/ai-agents/content/fine-tuning-vs-prompt-engineering@5OW_6o286mj470ElFyJ_5.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@OpenAI Fine Tuning](https://platform.openai.com/docs/guides/fine-tuning)
 - [@article@Prompt Engineering Guide](https://www.promptingguide.ai/)
 - [@article@Prompt Engineering vs Prompt Tuning: A Detailed Explanation](https://medium.com/@aabhi02/prompt-engineering-vs-prompt-tuning-a-detailed-explanation-19ea8ce62ac4)
-- [@video@RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models](https://youtu.be/zYGDpG-pTho?si=pFeWqbjSN1RM4WiZ)
+- [@video@RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models](https://youtu.be/zYGDpG-pTho?si=pFeWqbjSN1RM4WiZ)

src/data/roadmaps/ai-agents/content/git-and-terminal-usage@McREk2zHOlIrqbGSKbX-J.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@Git Basics](https://git-scm.com/doc)
 - [@official@Introduction to the Terminal](https://ubuntu.com/tutorials/command-line-for-beginners#1-overview)
-- [@video@Git and Terminal Basics Crash Course (YouTube)](https://www.youtube.com/watch?v=HVsySz-h9r4)
+- [@video@Git and Terminal Basics Crash Course (YouTube)](https://www.youtube.com/watch?v=HVsySz-h9r4)

src/data/roadmaps/ai-agents/content/haystack@XS-FsvtrXGZ8DPrwOsnlI.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@Haystack](https://haystack.deepset.ai/)
 - [@official@Haystack Overview](https://docs.haystack.deepset.ai/docs/intro)
-- [@opensource@deepset-ai/haystack](https://github.com/deepset-ai/haystack)
+- [@opensource@deepset-ai/haystack](https://github.com/deepset-ai/haystack)

src/data/roadmaps/ai-agents/content/helicone@MLxP5N0Vrmwh-kyvNeGXn.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@Helicone](https://www.helicone.ai/)
 - [@official@Helicone OSS LLM Observability](https://docs.helicone.ai/getting-started/quick-start)
-- [@opensource@Helicone/helicone](https://github.com/Helicone/helicone)
+- [@opensource@Helicone/helicone](https://github.com/Helicone/helicone)

src/data/roadmaps/ai-agents/content/human-in-the-loop-evaluation@rHxdxN97ZcU7MPl8L1jzN.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@Human in the Loop · Cloudflare Agents](https://developers.cloudflare.com/agents/concepts/human-in-the-loop/)
 - [@article@What is Human-in-the-Loop: A Guide](https://logifusion.com/what-is-human-in-the-loop-htil/)
 - [@article@Human-in-the-Loop ML](https://docs.aws.amazon.com/sagemaker/latest/dg/sms-human-review-workflow.html)
-- [@article@The Importance of Human Feedback in AI (Hugging Face Blog)](https://huggingface.co/blog/rlhf)
+- [@article@The Importance of Human Feedback in AI (Hugging Face Blog)](https://huggingface.co/blog/rlhf)

src/data/roadmaps/ai-agents/content/iterate-and-test-your-prompts@noTuUFnHSBzn7GKG9UZEi.md

@@ -4,6 +4,6 @@ After you write a first prompt, treat it as a draft, not the final version. Run
 
 Visit the following resources to learn more:
 
-- [@article@Master Iterative Prompting: A Guide](https://blogs.vreamer.space/master-iterative-prompting-a-guide-to-more-effective-interactions-with-ai-50a736eaec38)
 - [@course@Prompt Engineering Best Practices](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/)
-- [@video@Prompt Engineering: The Iterative Process](https://www.youtube.com/watch?v=dOxUroR57xs)
+- [@article@Master Iterative Prompting: A Guide](https://blogs.vreamer.space/master-iterative-prompting-a-guide-to-more-effective-interactions-with-ai-50a736eaec38)
+- [@video@Prompt Engineering: The Iterative Process](https://www.youtube.com/watch?v=dOxUroR57xs)

src/data/roadmaps/ai-agents/content/langchain@Ka6VpCEnqABvwiF9vba7t.md

@@ -1,11 +1,10 @@
 # LangChain
 
-LangChain is a Python and JavaScript library that helps you put large language models to work in real products. It gives ready-made parts for common agent tasks such as talking to many tools, keeping short-term memory, and calling an external API when the model needs fresh data. You combine these parts like Lego blocks: pick a model, add a prompt template, chain the steps, then wrap the chain in an “agent” that can choose what step to run next. Built-in connectors link to OpenAI, Hugging Face, vector stores, and SQL databases, so you can search documents or pull company data without writing a lot of glue code. This lets you move fast from idea to working bot, while still letting you swap out parts if your needs change.
+LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). It provides tools and abstractions to connect LLMs to various data sources, create chains of calls to LLMs or other utilities, and build agents that can interact with their environment. Essentially, it helps developers structure, chain, and orchestrate different AI components to build more complex and capable AI applications.
 
 Visit the following resources to learn more:
 
 - [@official@LangChain Documentation](https://python.langchain.com/docs/introduction/)
 - [@opensource@langchain-ai/langchain](https://github.com/langchain-ai/langchain)
-- [@article@Building Applications with LLMs using LangChain](https://www.pinecone.io/learn/series/langchain/)
 - [@article@AI Agents with LangChain and LangGraph](https://www.udacity.com/course/ai-agents-with-langchain-and-langgraph--cd13764)
-- [@video@LangChain Crash Course - Build LLM Apps Fast (YouTube)](https://www.youtube.com/watch?v=nAmC7SoVLd8)
+- [@video@LangChain Crash Course - Build LLM Apps Fast (YouTube)](https://www.youtube.com/watch?v=nAmC7SoVLd8)

src/data/roadmaps/ai-agents/content/langfuse@UoIheaJlShiceafrWALEH.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@official@LangFuse](https://langfuse.com/)
 - [@official@LangFuse Documentation](https://langfuse.com/docs)
 - [@opensource@langfuse/langfuse](https://github.com/langfuse/langfuse)
-- [@article@Langfuse: Open Source LLM Engineering Platform](https://www.ycombinator.com/companies/langfuse)
+- [@article@Langfuse: Open Source LLM Engineering Platform](https://www.ycombinator.com/companies/langfuse)

src/data/roadmaps/ai-agents/content/langsmith@SS8mGqf9wfrNqenIWvN8Z.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@official@LangSmith](https://smith.langchain.com/)
 - [@official@LangSmith Documentation](https://docs.smith.langchain.com/)
 - [@official@Harden your application with LangSmith Evaluation](https://www.langchain.com/evaluation)
-- [@article@What is LangSmith and Why should I care as a developer?](https://medium.com/around-the-prompt/what-is-langsmith-and-why-should-i-care-as-a-developer-e5921deb54b5)
+- [@article@What is LangSmith and Why should I care as a developer?](https://medium.com/around-the-prompt/what-is-langsmith-and-why-should-i-care-as-a-developer-e5921deb54b5)

src/data/roadmaps/ai-agents/content/langsmith@xp7TCTRE9HP60_rGzTUF6.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@official@LangSmith](https://smith.langchain.com/)
 - [@official@LangSmith Documentation](https://docs.smith.langchain.com/)
 - [@official@Harden your application with LangSmith Evaluation](https://www.langchain.com/evaluation)
-- [@article@What is LangSmith and Why should I care as a developer?](https://medium.com/around-the-prompt/what-is-langsmith-and-why-should-i-care-as-a-developer-e5921deb54b5)
+- [@article@What is LangSmith and Why should I care as a developer?](https://medium.com/around-the-prompt/what-is-langsmith-and-why-should-i-care-as-a-developer-e5921deb54b5)

src/data/roadmaps/ai-agents/content/local-desktop@iBtJp24F_kJE3YlBsW60s.md

@@ -6,5 +6,5 @@ Visit the following resources to learn more:
 
 - [@article@Build a Simple Local MCP Server](https://blog.stackademic.com/build-simple-local-mcp-server-5434d19572a4)
 - [@article@How to Build and Host Your Own MCP Servers in Easy Steps](https://collabnix.com/how-to-build-and-host-your-own-mcp-servers-in-easy-steps/)
-- [@article@Expose localhost to Internet](https://ngrok.com/docs)  
-- [@video@Run a Local Server on Your Machine](https://www.youtube.com/watch?v=ldGl6L4Vktk)  
+- [@article@Expose localhost to Internet](https://ngrok.com/docs)
+- [@video@Run a Local Server on Your Machine](https://www.youtube.com/watch?v=ldGl6L4Vktk)

src/data/roadmaps/ai-agents/content/long-term-memory@Ue633fz6Xu2wa2-KOAtdP.md

@@ -5,7 +5,7 @@ Long term memory in an AI agent stores important information for future use, lik
 Visit the following resources to learn more:
 
 - [@article@Long Term Memory in AI Agents](https://medium.com/@alozie_igbokwe/ai-101-long-term-memory-in-ai-agents-35f87f2d0ce0)
-- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)  
-- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)  
+- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)
+- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)
 - [@article@Short-Term vs Long-Term Memory in AI Agents](https://adasci.org/short-term-vs-long-term-memory-in-ai-agents/)
-- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)  
+- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)

src/data/roadmaps/ai-agents/content/manual-from-scratch@US6T5dXM8IY9V2qZnTOFW.md

@@ -4,7 +4,7 @@ Building an AI agent from scratch means writing every part of the system yoursel
 
 Visit the following resources to learn more:
 
-- [@article@A Step-by-Step Guide to Building an AI Agent From Scratch](https://www.neurond.com/blog/how-to-build-an-ai-agent)  
-- [@article@How to Build AI Agents](https://wotnot.io/blog/build-ai-agents)  
+- [@article@A Step-by-Step Guide to Building an AI Agent From Scratch](https://www.neurond.com/blog/how-to-build-an-ai-agent)
+- [@article@How to Build AI Agents](https://wotnot.io/blog/build-ai-agents)
 - [@article@Build Your Own AI Agent from Scratch in 30 Minutes](https://medium.com/@gurpartap.sandhu3/build-you-own-ai-agent-from-scratch-in-30-mins-using-simple-python-1458f8099da0)
-- [@video@Building an AI Agent From Scratch](https://www.youtube.com/watch?v=bTMPwUgLZf0)
+- [@video@Building an AI Agent From Scratch](https://www.youtube.com/watch?v=bTMPwUgLZf0)

src/data/roadmaps/ai-agents/content/max-length@Bn_BkthrVX_vOuwQzvPZa.md

@@ -4,9 +4,9 @@ Max Length sets the maximum number of tokens a language model can generate in on
 
 Visit the following resources to learn more:
 
-- [@official@OpenAI Token Usage](https://platform.openai.com/docs/guides/gpt/managing-tokens)  
-- [@official@Size and Max Token Limits](https://docs.anthropic.com/claude/docs/size-and-token-limits)  
-- [@article@Utilising Max Token Context Window of Anthropic Claude](https://medium.com/@nampreetsingh/utilising-max-token-context-window-of-anthropic-claude-on-amazon-bedrock-7377d94b2dfa)  
-- [@article@Controlling the Length of OpenAI Model Responses](https://help.openai.com/en/articles/5072518-controlling-the-length-of-openai-model-responses)  
+- [@official@OpenAI Token Usage](https://platform.openai.com/docs/guides/gpt/managing-tokens)
+- [@official@Size and Max Token Limits](https://docs.anthropic.com/claude/docs/size-and-token-limits)
+- [@article@Utilising Max Token Context Window of Anthropic Claude](https://medium.com/@nampreetsingh/utilising-max-token-context-window-of-anthropic-claude-on-amazon-bedrock-7377d94b2dfa)
+- [@article@Controlling the Length of OpenAI Model Responses](https://help.openai.com/en/articles/5072518-controlling-the-length-of-openai-model-responses)
 - [@article@Max Model Length in AI](https://www.restack.io/p/ai-model-answer-max-model-length-cat-ai)
 - [@video@Understanding ChatGPT/OpenAI Tokens](https://youtu.be/Mo3NV5n1yZk)

src/data/roadmaps/ai-agents/content/mcp-client@CGVstUxVXLJcYZrwk3iNQ.md

@@ -4,7 +4,7 @@ The MCP Client is the part of an AI agent that talks to the language model API.
 
 Visit the following resources to learn more:
 
-- [@opensource@Model Context Protocol](https://github.com/modelcontextprotocol/modelcontextprotocol)
 - [@official@Model Context Protocol](https://modelcontextprotocol.io/introduction)
-- [@official@OpenAI API Reference](https://platform.openai.com/docs/api-reference)  
-- [@official@Anthropic API Documentation](https://docs.anthropic.com/claude/reference)  
+- [@official@OpenAI API Reference](https://platform.openai.com/docs/api-reference)
+- [@official@Anthropic API Documentation](https://docs.anthropic.com/claude/reference)
+- [@opensource@Model Context Protocol](https://github.com/modelcontextprotocol/modelcontextprotocol)

src/data/roadmaps/ai-agents/content/mcp-hosts@9FryAIrWRHh8YlzKX3et5.md

@@ -4,7 +4,7 @@ MCP Hosts are computers or services that run the Model Context Protocol. They ha
 
 Visit the following resources to learn more:
 
-- [@official@Vercel Serverless Hosting](https://vercel.com/docs)  
+- [@official@Vercel Serverless Hosting](https://vercel.com/docs)
+- [@opensource@punkeye/awesome-mcp-servers](https://github.com/punkpeye/awesome-mcp-servers)
 - [@article@The Ultimate Guide to MCP](https://guangzhengli.com/blog/en/model-context-protocol)
-- [@article@AWS MCP Servers for Code Assistants](https://aws.amazon.com/blogs/machine-learning/introducing-aws-mcp-servers-for-code-assistants-part-1/)
-- [@opensource@punkeye/awesome-mcp-servers](https://github.com/punkpeye/awesome-mcp-servers)
+- [@article@AWS MCP Servers for Code Assistants](https://aws.amazon.com/blogs/machine-learning/introducing-aws-mcp-servers-for-code-assistants-part-1/)

src/data/roadmaps/ai-agents/content/mcp-servers@yv_-87FVM7WKn5iv6LW9q.md

@@ -4,7 +4,7 @@ An MCP Server is the main machine or cloud service that runs the Model Context P
 
 Visit the following resources to learn more:
 
-- [@article@Introducing the Azure MCP Server ](https://devblogs.microsoft.com/azure-sdk/introducing-the-azure-mcp-server/)  
+- [@opensource@punkeye/awesome-mcp-servers](https://github.com/punkpeye/awesome-mcp-servers)
+- [@article@Introducing the Azure MCP Server ](https://devblogs.microsoft.com/azure-sdk/introducing-the-azure-mcp-server/)
 - [@article@The Ultimate Guide to MCP](https://guangzhengli.com/blog/en/model-context-protocol)
-- [@article@AWS MCP Servers for Code Assistants](https://aws.amazon.com/blogs/machine-learning/introducing-aws-mcp-servers-for-code-assistants-part-1/)
-- [@opensource@punkeye/awesome-mcp-servers](https://github.com/punkpeye/awesome-mcp-servers)
+- [@article@AWS MCP Servers for Code Assistants](https://aws.amazon.com/blogs/machine-learning/introducing-aws-mcp-servers-for-code-assistants-part-1/)

src/data/roadmaps/ai-agents/content/metrics-to-track@v8qLnyFRnEumodBYxQSXQ.md

@@ -5,6 +5,6 @@ To judge how well an AI agent works, you need clear numbers. Track accuracy, pre
 Visit the following resources to learn more:
 
 - [@article@Robustness Testing for AI](https://mitibmwatsonailab.mit.edu/category/robustness/)
-- [@article@Complete Guide to Machine Learning Evaluation Metrics](https://medium.com/analytics-vidhya/complete-guide-to-machine-learning-evaluation-metrics-615c2864d916)  
-- [@article@Measuring Model Performance](https://developers.google.com/machine-learning/crash-course/classification/accuracy)  
-- [@article@A Practical Framework for (Gen)AI Value Measurement](https://medium.com/google-cloud/a-practical-framework-for-gen-ai-value-measurement-5fccf3b66c43)  
+- [@article@Complete Guide to Machine Learning Evaluation Metrics](https://medium.com/analytics-vidhya/complete-guide-to-machine-learning-evaluation-metrics-615c2864d916)
+- [@article@Measuring Model Performance](https://developers.google.com/machine-learning/crash-course/classification/accuracy)
+- [@article@A Practical Framework for (Gen)AI Value Measurement](https://medium.com/google-cloud/a-practical-framework-for-gen-ai-value-measurement-5fccf3b66c43)

src/data/roadmaps/ai-agents/content/model-context-protocol-mcp@1B0IqRNYdtbHDi1jHSXuI.md

@@ -4,8 +4,8 @@ Model Context Protocol (MCP) is a rulebook that tells an AI agent how to pack ba
 
 Visit the following resources to learn more:
 
-- [@opensource@Model Context Protocol](https://github.com/modelcontextprotocol/modelcontextprotocol)
-- [@official@Model Context Protocol](https://modelcontextprotocol.io/introduction)
-- [@article@Introducing the Azure MCP Server ](https://devblogs.microsoft.com/azure-sdk/introducing-the-azure-mcp-server/)  
-- [@article@The Ultimate Guide to MCP](https://guangzhengli.com/blog/en/model-context-protocol)
 - [@course@MCP: Build Rich-Context AI Apps with Anthropic](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/)
+- [@official@Model Context Protocol](https://modelcontextprotocol.io/introduction)
+- [@opensource@Model Context Protocol](https://github.com/modelcontextprotocol/modelcontextprotocol)
+- [@article@Introducing the Azure MCP Server ](https://devblogs.microsoft.com/azure-sdk/introducing-the-azure-mcp-server/)
+- [@article@The Ultimate Guide to MCP](https://guangzhengli.com/blog/en/model-context-protocol)

src/data/roadmaps/ai-agents/content/npc--game-ai@ok8vN7VtCgyef5x6aoQaL.md

@@ -4,5 +4,5 @@ Game studios use AI agents to control non-player characters (NPCs). The agent ob
 
 Visit the following resources to learn more:
 
-- [@official@Unity – AI for NPCs](https://dev.epicgames.com/documentation/en-us/unreal-engine/artificial-intelligence-in-unreal-engine?application_version=5.3)  
+- [@official@Unity – AI for NPCs](https://dev.epicgames.com/documentation/en-us/unreal-engine/artificial-intelligence-in-unreal-engine?application_version=5.3)
 - [@article@AI-Driven NPCs: The Future of Gaming Explained](https://www.capermint.com/blog/everything-you-need-to-know-about-non-player-character-npc/)

src/data/roadmaps/ai-agents/content/observation--reflection@ZJTrun3jK3zBGOTm1jdMI.md

@@ -4,5 +4,5 @@ Observation and reflection form the thinking pause in an AI agent’s loop. Firs
 
 Visit the following resources to learn more:
 
-- [@official@Best Practices for Prompting and Self-checking](https://platform.openai.com/docs/guides/prompt-engineering)  
-- [@article@Self-Reflective AI: Building Agents That Learn by Observing Themselves](https://arxiv.org/abs/2302.14045)  
+- [@official@Best Practices for Prompting and Self-checking](https://platform.openai.com/docs/guides/prompt-engineering)
+- [@article@Self-Reflective AI: Building Agents That Learn by Observing Themselves](https://arxiv.org/abs/2302.14045)

src/data/roadmaps/ai-agents/content/open-weight-models@DSJAhQhc1dQmBHQ8ZkTau.md

@@ -4,8 +4,8 @@ Open-weight models are neural networks whose trained parameters, also called wei
 
 Visit the following resources to learn more:
 
-- [@official@BLOOM BigScience](https://bigscience.huggingface.co/)  
-- [@official@Falcon LLM – Technology Innovation Institute (TII)](https://falconllm.tii.ae/)  
-- [@official@Llama 2 – Meta's Official Announcement](https://ai.meta.com/llama/)  
-- [@official@Hugging Face – Open LLM Leaderboard (Top Open Models)](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)  
-- [@official@EleutherAI – Open Research Collective (GPT-Neo, GPT-J, etc.)](https://www.eleuther.ai/)  
+- [@official@BLOOM BigScience](https://bigscience.huggingface.co/)
+- [@official@Falcon LLM – Technology Innovation Institute (TII)](https://falconllm.tii.ae/)
+- [@official@Llama 2 – Meta's Official Announcement](https://ai.meta.com/llama/)
+- [@official@Hugging Face – Open LLM Leaderboard (Top Open Models)](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+- [@official@EleutherAI – Open Research Collective (GPT-Neo, GPT-J, etc.)](https://www.eleuther.ai/)

src/data/roadmaps/ai-agents/content/openai-assistant-api@37GBFVZ2J2d5r8bd1ViHq.md

@@ -4,7 +4,7 @@ The OpenAI Assistants API lets you add clear, task-specific actions to a chat wi
 
 Visit the following resources to learn more:
 
-- [@official@OpenAI Documentation – Assistants API Overview](https://platform.openai.com/docs/assistants/overview)  
-- [@official@OpenAI Blog – Introducing the Assistants API](https://openai.com/blog/assistants-api)  
-- [@official@OpenAI Cookbook – Assistants API Example](https://github.com/openai/openai-cookbook/blob/main/examples/Assistants_API_overview_python.ipynb)  
-- [@official@OpenAI API Reference – Assistants Endpoints](https://platform.openai.com/docs/api-reference/assistants)  
+- [@official@OpenAI Documentation – Assistants API Overview](https://platform.openai.com/docs/assistants/overview)
+- [@official@OpenAI Blog – Introducing the Assistants API](https://openai.com/blog/assistants-api)
+- [@official@OpenAI Cookbook – Assistants API Example](https://github.com/openai/openai-cookbook/blob/main/examples/Assistants_API_overview_python.ipynb)
+- [@official@OpenAI API Reference – Assistants Endpoints](https://platform.openai.com/docs/api-reference/assistants)

src/data/roadmaps/ai-agents/content/openai-functions-calling@AQtxTTxmBpfl8BMgJbGzc.md

@@ -4,8 +4,8 @@ OpenAI Function Calling lets you give a language model a list of tools and have
 
 Visit the following resources to learn more:
 
-- [@official@OpenAI Documentation – Function Calling](https://platform.openai.com/docs/guides/function-calling)  
-- [@official@OpenAI Cookbook – Using Functions with GPT Models](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_call_functions_with_chat_models.ipynb)  
-- [@officialOpenAI Blog – Announcing Function Calling and Other Updates](https://openai.com/blog/function-calling-and-other-api-updates)  
-- [@officialOpenAI API Reference – Functions Section](https://platform.openai.com/docs/api-reference/chat/create#functions)  
-- [@officialOpenAI Community – Discussions and Examples on Function Calling](https://community.openai.com/tag/function-calling)  
+- [@official@OpenAI Documentation – Function Calling](https://platform.openai.com/docs/guides/function-calling)
+- [@official@OpenAI Cookbook – Using Functions with GPT Models](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_call_functions_with_chat_models.ipynb)
+- [@article@@officialOpenAI Blog – Announcing Function Calling and Other Updates](https://openai.com/blog/function-calling-and-other-api-updates)
+- [@article@@officialOpenAI API Reference – Functions Section](https://platform.openai.com/docs/api-reference/chat/create#functions)
+- [@article@@officialOpenAI Community – Discussions and Examples on Function Calling](https://community.openai.com/tag/function-calling)

src/data/roadmaps/ai-agents/content/openllmetry@7UqPXUzqKYXklnB3x-tsv.md

@@ -4,7 +4,7 @@ openllmetry is a small Python library that makes it easy to watch what your AI a
 
 Visit the following resources to learn more:
 
-- [@official@OpenTelemetry Documentation](https://www.traceloop.com/blog/openllmetry)  
-- [@official@What is OpenLLMetry? - traceloop](https://www.traceloop.com/docs/openllmetry/introduction)  
+- [@official@OpenTelemetry Documentation](https://www.traceloop.com/blog/openllmetry)
+- [@official@What is OpenLLMetry? - traceloop](https://www.traceloop.com/docs/openllmetry/introduction)
 - [@official@Use Traceloop with Python](https://www.traceloop.com/docs/openllmetry/getting-started-python)
 - [@opensource@traceloop/openllmetry](https://github.com/traceloop/openllmetry)

src/data/roadmaps/ai-agents/content/perception--user-input@LU76AhCYDjxdBhpMQ4eMU.md

@@ -5,4 +5,4 @@ Perception, also called user input, is the first step in an agent loop. The agen
 Visit the following resources to learn more:
 
 - [@article@Perception in AI: Understanding Its Types and Importance](https://marktalks.com/perception-in-ai-understanding-its-types-and-importance/)
-- [@article@What Is AI Agent Perception? - IBM](https://www.ibm.com/think/topics/ai-agent-perception)
+- [@article@What Is AI Agent Perception? - IBM](https://www.ibm.com/think/topics/ai-agent-perception)

src/data/roadmaps/ai-agents/content/personal-assistant@PPdAutqJF5G60Eg9lYBND.md

@@ -5,4 +5,4 @@ A personal assistant AI agent is a smart program that helps one person manage da
 Visit the following resources to learn more:
 
 - [@article@A Complete Guide on AI-powered Personal Assistants](https://medium.com/@alexander_clifford/a-complete-guide-on-ai-powered-personal-assistants-with-examples-2f5cd894d566)
-- [@article@9 Best AI Personal Assistants for Work, Chat and Home](https://saner.ai/best-ai-personal-assistants/)
+- [@article@9 Best AI Personal Assistants for Work, Chat and Home](https://saner.ai/best-ai-personal-assistants/)

src/data/roadmaps/ai-agents/content/pricing-of-common-models@B8dzg61TGaknuruBgkEJd.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@OpenAI Pricing](https://openai.com/api/pricing/)
 - [@article@Executive Guide To AI Agent Pricing](https://www.forbes.com/councils/forbesbusinesscouncil/2025/01/28/executive-guide-to-ai-agent-pricing-winning-strategies-and-models-to-drive-growth/)
-- [@article@AI Pricing: How Much Does Artificial Intelligence Cost In 2025?](https://www.internetsearchinc.com/ai-pricing-how-much-does-artificial-intelligence-cost/)
+- [@article@AI Pricing: How Much Does Artificial Intelligence Cost In 2025?](https://www.internetsearchinc.com/ai-pricing-how-much-does-artificial-intelligence-cost/)

src/data/roadmaps/ai-agents/content/prompt-injection--jailbreaks@SU2RuicMUo8tiAsQtDI1k.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Prompt Injection vs. Jailbreaking: What's the Difference?](https://learnprompting.org/blog/injection_jailbreaking)
 - [@article@Prompt Injection vs Prompt Jailbreak](https://codoid.com/ai/prompt-injection-vs-prompt-jailbreak-a-detailed-comparison/)
-- [@article@How Prompt Attacks Exploit GenAI and How to Fight Back](https://unit42.paloaltonetworks.com/new-frontier-of-genai-threats-a-comprehensive-guide-to-prompt-attacks/)
+- [@article@How Prompt Attacks Exploit GenAI and How to Fight Back](https://unit42.paloaltonetworks.com/new-frontier-of-genai-threats-a-comprehensive-guide-to-prompt-attacks/)

src/data/roadmaps/ai-agents/content/provide-additional-context@6I42CoeWX-kkFXTKAY7rw.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@What is Context in Prompt Engineering?](https://www.godofprompt.ai/blog/what-is-context-in-prompt-engineering)
 - [@article@The Importance of Context for Reliable AI Systems](https://medium.com/mathco-ai/the-importance-of-context-for-reliable-ai-systems-and-how-to-provide-context-009bd1ac7189/)
-- [@article@Context Engineering: Why Feeding AI the Right Context Matters](https://inspirednonsense.com/context-engineering-why-feeding-ai-the-right-context-matters-353e8f87d6d3)
+- [@article@Context Engineering: Why Feeding AI the Right Context Matters](https://inspirednonsense.com/context-engineering-why-feeding-ai-the-right-context-matters-353e8f87d6d3)

src/data/roadmaps/ai-agents/content/rag-agent@cW8O4vLLKEG-Q0dE8E5Zp.md

@@ -5,4 +5,4 @@ A RAG (Retrieval-Augmented Generation) agent mixes search with language generati
 Visit the following resources to learn more:
 
 - [@article@What is RAG? - Retrieval-Augmented Generation AI Explained](https://aws.amazon.com/what-is/retrieval-augmented-generation/)
-- [@article@What Is Retrieval-Augmented Generation, aka RAG?](https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/)
+- [@article@What Is Retrieval-Augmented Generation, aka RAG?](https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/)

src/data/roadmaps/ai-agents/content/rag-and-vector-databases@wkS4yOJ3JdZQE_yBID8K7.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Understanding Retrieval-Augmented Generation (RAG) and Vector Databases](https://pureai.com/Articles/2025/03/03/Understanding-RAG.aspx)
 - [@article@Build Advanced Retrieval-Augmented Generation Systems](https://learn.microsoft.com/en-us/azure/developer/ai/advanced-retrieval-augmented-generation)
-- [@article@What Is Retrieval-Augmented Generation, aka RAG?](https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/)
+- [@article@What Is Retrieval-Augmented Generation, aka RAG?](https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/)

src/data/roadmaps/ai-agents/content/ragas@YzEDtGEaMaMWVt0W03HRt.md

@@ -5,5 +5,5 @@ Ragas is an open-source tool used to check how well a Retrieval-Augmented Genera
 Visit the following resources to learn more:
 
 - [@official@Ragas Documentation](https://docs.ragas.io/en/latest/)
-- [@article@Evaluating RAG Applications with RAGAs](https://towardsdatascience.com/evaluating-rag-applications-with-ragas-81d67b0ee31a/n)
 - [@opensource@explodinggradients/ragas](https://github.com/explodinggradients/ragas)
+- [@article@Evaluating RAG Applications with RAGAs](https://towardsdatascience.com/evaluating-rag-applications-with-ragas-81d67b0ee31a/n)

src/data/roadmaps/ai-agents/content/react-reason--act@53xDks6JQ33fHMa3XcuCd.md

@@ -5,4 +5,4 @@ ReAct is an agent pattern that makes a model alternate between two simple steps:
 Visit the following resources to learn more:
 
 - [@official@ReAct: Synergizing Reasoning and Acting in Language Models](https://react-lm.github.io/)
-- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)
+- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)

src/data/roadmaps/ai-agents/content/reason-and-plan@ycPRgRYR4lEBQr_xxHKnM.md

@@ -5,4 +5,4 @@ Reason and Plan is the moment when an AI agent thinks before it acts. The agent
 Visit the following resources to learn more:
 
 - [@official@ReAct: Synergizing Reasoning and Acting in Language Models](https://react-lm.github.io/)
-- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)
+- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)

src/data/roadmaps/ai-agents/content/reasoning-vs-standard-models@N3yZfUxphxjiupqGpyaS9.md

@@ -5,4 +5,4 @@ Reasoning models break a task into clear steps and follow a line of logic, while
 Visit the following resources to learn more:
 
 - [@official@ReAct: Synergizing Reasoning and Acting in Language Models](https://react-lm.github.io/)
-- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)
+- [@article@ReAct Systems: Enhancing LLMs with Reasoning and Action](https://learnprompting.org/docs/agents/react)

src/data/roadmaps/ai-agents/content/rest-api-knowledge@QtTwecLdvQa8pgELJ6i80.md

@@ -5,4 +5,4 @@ A **REST API** (Representational State Transfer) is an architectural style for d
 Visit the following resources to learn more:
 
 - [@article@What is RESTful API? - RESTful API Explained - AWS](https://aws.amazon.com/what-is/restful-api/)
-- [@article@What Is a REST API? Examples, Uses & Challenges ](https://blog.postman.com/rest-api-examples/)
+- [@article@What Is a REST API? Examples, Uses & Challenges ](https://blog.postman.com/rest-api-examples/)

src/data/roadmaps/ai-agents/content/short-term--memory@M3U6RfIqaiut2nuOibY8W.md

@@ -2,26 +2,25 @@
 
 Short term memory are the facts which are passed as a part of the prompt to the LLM e.g. there might be a prompt like below:
 
-```text
-Users Profile:
-- name: {name}
-- age: {age}
-- expertise: {expertise}
-
-User is currently learning about {current_topic}. User has some goals in mind which are:
-- {goal_1}
-- {goal_2}
-- {goal_3}
-
-Help the user achieve the goals.
-```
+    Users Profile:
+    - name: {name}
+    - age: {age}
+    - expertise: {expertise}
+    
+    User is currently learning about {current_topic}. User has some goals in mind which are:
+    - {goal_1}
+    - {goal_2}
+    - {goal_3}
+    
+    Help the user achieve the goals.
+    
 
 Notice how we injected the user's profile, current topic and goals in the prompt. These are all short term memories.
 
 Visit the following resources to learn more:
 
-- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)  
+- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)
 - [@article@Build Smarter AI Agents: Manage Short-term and Long-term Memory](https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/)
-- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)  
+- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)
 - [@article@Short-Term vs Long-Term Memory in AI Agents](https://adasci.org/short-term-vs-long-term-memory-in-ai-agents/)
-- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)  
+- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)

src/data/roadmaps/ai-agents/content/smol-depot@eWxQiBrxIUG2JNcrdfIHS.md

@@ -4,6 +4,6 @@ Smol Depot is an open-source kit that lets you bundle all the parts of a small A
 
 Visit the following resources to learn more:
 
-- [@official@smol.ai - Continuous Fine-tuning Platform for AI Engineers](https://smol.candycode.dev/)  
+- [@official@smol.ai - Continuous Fine-tuning Platform for AI Engineers](https://smol.candycode.dev/)
 - [@article@5-min Smol AI Tutorial](https://www.ai-jason.com/learning-ai/smol-ai-tutorial)
-- [@video@Smol AI Full Beginner Course](https://www.youtube.com/watch?v=d7qFVrpLh34)  
+- [@video@Smol AI Full Beginner Course](https://www.youtube.com/watch?v=d7qFVrpLh34)

src/data/roadmaps/ai-agents/content/specify-length-format-etc@wwHHlEoPAx0TLxbtY6nMA.md

@@ -4,5 +4,5 @@ When you give a task to an AI, make clear how long the answer should be and what
 
 Visit the following resources to learn more:
 
-- [@article@Mastering Prompt Engineering: Format, Length, and Audience](https://techlasi.com/savvy/mastering-prompt-engineering-format-length-and-audience-examples-for-2024/)  
-- [@article@Ultimate Guide to Prompt Engineering](https://promptdrive.ai/prompt-engineering/)
+- [@article@Mastering Prompt Engineering: Format, Length, and Audience](https://techlasi.com/savvy/mastering-prompt-engineering-format-length-and-audience-examples-for-2024/)
+- [@article@Ultimate Guide to Prompt Engineering](https://promptdrive.ai/prompt-engineering/)

src/data/roadmaps/ai-agents/content/stopping-criteria@K0G-Lw069jXUJwZqHtybd.md

@@ -5,4 +5,4 @@ Stopping criteria tell the language model when to stop writing more text. Withou
 Visit the following resources to learn more:
 
 - [@article@Defining Stopping Criteria in Large Language Models](https://www.metriccoders.com/post/defining-stopping-criteria-in-large-language-models-a-practical-guide)
-- [@article@Stopping Criteria for Decision Tree Algorithm and Tree Plots](https://aieagle.in/stopping-criteria-for-decision-tree-algorithm-and-tree-plots/)
+- [@article@Stopping Criteria for Decision Tree Algorithm and Tree Plots](https://aieagle.in/stopping-criteria-for-decision-tree-algorithm-and-tree-plots/)

src/data/roadmaps/ai-agents/content/structured-logging--tracing@zs6LM8WEnb0ERWpiaQCgc.md

@@ -1,6 +1,6 @@
 # Structured Logging & Tracing
 
-Structured logging and tracing are ways to record what an AI agent does so you can find and fix problems fast. Instead of dumping plain text, the agent writes logs in a fixed key-value format, such as time, user_id, step, and message. Because every entry follows the same shape, search tools can filter, sort, and count events with ease. Tracing links those log lines into a chain that follows one request or task across many functions, threads, or microservices. By adding a unique trace ID to each step, you can see how long each part took and where errors happened. Together, structured logs and traces offer clear, machine-readable data that helps developers spot slow code paths, unusual behavior, and hidden bugs without endless manual scans.
+Structured logging and tracing are ways to record what an AI agent does so you can find and fix problems fast. Instead of dumping plain text, the agent writes logs in a fixed key-value format, such as time, user\_id, step, and message. Because every entry follows the same shape, search tools can filter, sort, and count events with ease. Tracing links those log lines into a chain that follows one request or task across many functions, threads, or microservices. By adding a unique trace ID to each step, you can see how long each part took and where errors happened. Together, structured logs and traces offer clear, machine-readable data that helps developers spot slow code paths, unusual behavior, and hidden bugs without endless manual scans.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/ai-agents/content/summarization--compression@jTDC19BTWCqxqMizrIJHr.md

@@ -5,4 +5,4 @@ Summarization or compression lets an AI agent keep the gist of past chats withou
 Visit the following resources to learn more:
 
 - [@article@Evaluating LLMs for Text Summarization](https://insights.sei.cmu.edu/blog/evaluating-llms-for-text-summarization-introduction/)
-- [@article@The Ultimate Guide to AI Document Summarization](https://www.documentllm.com/blog/ai-document-summarization-guide)
+- [@article@The Ultimate Guide to AI Document Summarization](https://www.documentllm.com/blog/ai-document-summarization-guide)

src/data/roadmaps/ai-agents/content/temperature@L1zL1GzqjSAjF06pIIXhy.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@What Temperature Means in Natural Language Processing and AI](https://thenewstack.io/what-temperature-means-in-natural-language-processing-and-ai/)
 - [@article@LLM Temperature: How It Works and When You Should Use It](https://www.vellum.ai/llm-parameters/temperature)
 - [@article@What is LLM Temperature? - IBM](https://www.ibm.com/think/topics/llm-temperature)
-- [@article@How Temperature Settings Transform Your AI Agent's Responses](https://docsbot.ai/article/how-temperature-settings-transform-your-ai-agents-responses)
+- [@article@How Temperature Settings Transform Your AI Agent's Responses](https://docsbot.ai/article/how-temperature-settings-transform-your-ai-agents-responses)

src/data/roadmaps/ai-agents/content/tokenization@GAjuWyJl9CI1nqXBp6XCf.md

@@ -5,4 +5,4 @@ Tokenization is the step where raw text is broken into small pieces called token
 Visit the following resources to learn more:
 
 - [@article@Explaining Tokens — the Language and Currency of AI](https://blogs.nvidia.com/blog/ai-tokens-explained/)
-- [@article@What is Tokenization? Types, Use Cases, Implementation](https://www.datacamp.com/blog/what-is-tokenization)
+- [@article@What is Tokenization? Types, Use Cases, Implementation](https://www.datacamp.com/blog/what-is-tokenization)

src/data/roadmaps/ai-agents/content/tool-definition@qakbxB8xe7Y8gejC5cZnK.md

@@ -5,4 +5,4 @@ A tool is any skill or function that an AI agent can call to get a job done. It
 Visit the following resources to learn more:
 
 - [@article@Understanding the Agent Function in AI: Key Roles and Responsibilities](https://pingax.com/ai/agent/function/understanding-the-agent-function-in-ai-key-roles-and-responsibilities/)
-- [@article@What is an AI Tool?](https://www.synthesia.io/glossary/ai-tool)
+- [@article@What is an AI Tool?](https://www.synthesia.io/glossary/ai-tool)

src/data/roadmaps/ai-agents/content/tool-sandboxing--permissioning@UVzLGXG6K7HQVHmw8ZAv2.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@AI Sandbox | Harvard University Information Technology](https://www.huit.harvard.edu/ai-sandbox)
 - [@article@How to Set Up AI Sandboxes to Maximize Adoption](https://medium.com/@emilholmegaard/how-to-set-up-ai-sandboxes-to-maximize-adoption-without-compromising-ethics-and-values-637c70626130)
-- [@article@Sandboxes for AI - The Datasphere Initiative](https://www.thedatasphere.org/datasphere-publish/sandboxes-for-ai/)
+- [@article@Sandboxes for AI - The Datasphere Initiative](https://www.thedatasphere.org/datasphere-publish/sandboxes-for-ai/)

src/data/roadmaps/ai-agents/content/top-p@icbp1NjurQfdM0dHnz6v2.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Nucleus Sampling](https://nn.labml.ai/sampling/nucleus.html)
 - [@article@Sampling Techniques in Large Language Models (LLMs)](https://medium.com/@shashankag14/understanding-sampling-techniques-in-large-language-models-llms-dfc28b93f518)
-- [@article@Temperature, top_p and top_k for chatbot responses](https://community.openai.com/t/temperature-top-p-and-top-k-for-chatbot-responses/295542)
+- [@article@Temperature, top_p and top_k for chatbot responses](https://community.openai.com/t/temperature-top-p-and-top-k-for-chatbot-responses/295542)

src/data/roadmaps/ai-agents/content/transformer-models-and-llms@ZF5_5Y5zqa75Ov22JACX6.md

@@ -5,4 +5,4 @@ Transformer models are a type of neural network that read input data—like word
 Visit the following resources to learn more:
 
 - [@article@Exploring Open Source AI Models: LLMs and Transformer Architectures](https://llmmodels.org/blog/exploring-open-source-ai-models-llms-and-transformer-architectures/)
-- [@article@How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/)
+- [@article@How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/)

src/data/roadmaps/ai-agents/content/tree-of-thought@Nmy1PoB32DcWZnPM8l8jT.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Tree of Thoughts (ToT) | Prompt Engineering Guide](https://www.promptingguide.ai/techniques/tot)
 - [@article@What is tree-of-thoughts? - IBM](https://www.ibm.com/think/topics/tree-of-thoughts)
-- [@article@The Revolutionary Approach of Tree-of-Thought Prompting in AI](https://medium.com/@WeavePlatform/the-revolutionary-approach-of-tree-of-thought-prompting-in-ai-eb7c0872247b)
+- [@article@The Revolutionary Approach of Tree-of-Thought Prompting in AI](https://medium.com/@WeavePlatform/the-revolutionary-approach-of-tree-of-thought-prompting-in-ai-eb7c0872247b)

src/data/roadmaps/ai-agents/content/understand-the-basics-of-rag@qwVQOwBTLA2yUgRISzC8k.md

@@ -7,4 +7,4 @@ Visit the following resources to learn more:
 - [@article@What Is RAG in AI and How to Use It?](https://www.v7labs.com/blog/what-is-rag)
 - [@article@An Introduction to RAG and Simple & Complex RAG](https://medium.com/enterprise-rag/an-introduction-to-rag-and-simple-complex-rag-9c3aa9bd017b)
 - [@video@Learn RAG From Scratch](https://www.youtube.com/watch?v=sVcwVQRHIc8)
-- [@video@What is Retrieval-Augmented Generation (RAG)?](https://www.youtube.com/watch?v=T-D1OfcDW1M)
+- [@video@What is Retrieval-Augmented Generation (RAG)?](https://www.youtube.com/watch?v=T-D1OfcDW1M)

src/data/roadmaps/ai-agents/content/user-profile-storage@QJqXHV8VHPTnfYfmKPzW7.md

@@ -5,4 +5,4 @@ User profile storage is the part of an AI agent’s memory that holds stable fac
 Visit the following resources to learn more:
 
 - [@article@Storage Technology Explained: AI and Data Storage](https://www.computerweekly.com/feature/Storage-technology-explained-AI-and-the-data-storage-it-needs)
-- [@partner@The Architect's Guide to Storage for AI - The New Stack](https://thenewstack.io/the-architects-guide-to-storage-for-ai/)
+- [@article@The Architect's Guide to Storage for AI - The New Stack](https://thenewstack.io/the-architects-guide-to-storage-for-ai/)

src/data/roadmaps/ai-agents/content/what-are-tools@2zsOUWJQ8e7wnoHmq1icG.md

@@ -5,4 +5,4 @@ Tools are extra skills or resources that an AI agent can call on to finish a job
 Visit the following resources to learn more:
 
 - [@article@Compare 50+ AI Agent Tools in 2025 - AIMultiple](https://research.aimultiple.com/ai-agent-tools/)
-- [@article@AI Agents Explained in Simple Terms for Beginners](https://www.geeky-gadgets.com/ai-agents-explained-for-beginners/)
+- [@article@AI Agents Explained in Simple Terms for Beginners](https://www.geeky-gadgets.com/ai-agents-explained-for-beginners/)

src/data/roadmaps/ai-agents/content/what-is-agent-memory@TBH_DZTAfR8Daoh-njNFC.md

@@ -5,7 +5,7 @@ Agent memory is the part of an AI agent that keeps track of what has already hap
 Visit the following resources to learn more:
 
 - [@article@Agentic Memory for LLM Agents](https://arxiv.org/abs/2502.12110)
-- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)  
-- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)  
+- [@article@Memory Management in AI Agents](https://python.langchain.com/docs/how_to/chatbots_memory/)
+- [@article@Storing and Retrieving Knowledge for Agents](https://www.pinecone.io/learn/langchain-retrieval-augmentation/)
 - [@article@Short-Term vs Long-Term Memory in AI Agents](https://adasci.org/short-term-vs-long-term-memory-in-ai-agents/)
-- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)  
+- [@video@Building Brain-Like Memory for AI Agents](https://www.youtube.com/watch?v=VKPngyO0iKg)

src/data/roadmaps/ai-agents/content/what-is-prompt-engineering@Y8EqzFx3qxtrSh7bWbbV8.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@roadmap@Visit Dedicated Prompt Engineering Roadmap](https://roadmap.sh/prompt-engineering)
 - [@article@What is Prompt Engineering? - AI Prompt Engineering Explained - AWS](https://aws.amazon.com/what-is/prompt-engineering/)
-- [@article@What is Prompt Engineering? A Detailed Guide For 2025](https://www.datacamp.com/blog/what-is-prompt-engineering-the-future-of-ai-communication)  
+- [@article@What is Prompt Engineering? A Detailed Guide For 2025](https://www.datacamp.com/blog/what-is-prompt-engineering-the-future-of-ai-communication)

src/data/roadmaps/cyber-security/content/authentication-vs-authorization@WG7DdsxESm31VcLFfkVTz.md

@@ -1,12 +1,10 @@
 # Authentication vs. Authorization
 
-Authentication verifies *who* a user is, confirming their identity using credentials like usernames and passwords. Authorization, on the other hand, determines *what* a user is allowed to access after they've been authenticated. In essence, authentication proves you are who you say you are, while authorization dictates what you can do.
+Authentication verifies who a user is, confirming their identity using credentials like usernames and passwords. Authorization, on the other hand, determines what a user is allowed to access after they've been authenticated. In essence, authentication proves you are who you say you are, while authorization dictates what you can do.
 
 Visit the following resources to learn more:
 
 - [@article@Two-factor authentication (2FA)](https://authy.com/what-is-2fa/)
 - [@article@Biometrics (fingerprint, facial recognition, etc.)](https://me-en.kaspersky.com/resource-center/definitions/biometrics)
 - [@article@Security tokens or certificates](https://www.comodo.com/e-commerce/ssl-certificates/certificate.php)
-- [@article@Role-based access control (RBAC)](https://en.wikipedia.org/wiki/Role-based_access_control)
-- [@article@Access Control Lists (ACLs)](https://en.wikipedia.org/wiki/Access-control_list)
-- [@article@Attribute-based access control (ABAC)](https://en.wikipedia.org/wiki/Attribute-based_access_control)
+- [@article@Role-based access control (RBAC)](https://en.wikipedia.org/wiki/Role-based_access_control)

src/data/roadmaps/cyber-security/content/aws@0LztOTc3NG3OujCVwlcVU.md

@@ -7,5 +7,4 @@ Visit the following resources to learn more:
 - [@roadmap@Visit Dedicated AWS Roadmap](https://roadmap.sh/aws)
 - [@course@AWS Complete Tutorial](https://www.youtube.com/watch?v=B8i49C8fC3E)
 - [@official@AWS](https://aws.amazon.com)
-- [@article@How to create an AWS account](https://grapplingdev.com/tutorials/how-to-create-aws-account)
 - [@video@AWS Overview](https://www.youtube.com/watch?v=a9__D53WsUs)

src/data/roadmaps/cyber-security/content/bash@tao0Bb_JR0Ubl62HO8plp.md

@@ -5,6 +5,6 @@ Bash (Bourne Again Shell) is a widely-used Unix shell and scripting language tha
 Visit the following resources to learn more:
 
 - [@roadmap@Visit the Dedicated Shell/Bash Roadmap](https://roadmap.sh/shell-bash)
-- [@official@Bash](https://www.gnu.org/software/bash/)
 - [@course@Beginners Guide To The Bash Terminal](https://www.youtube.com/watch?v=oxuRxtrO2Ag)
-- [@course@Start learning bash](https://linuxhandbook.com/bash/)
+- [@course@Start learning bash](https://linuxhandbook.com/bash/)
+- [@official@Bash](https://www.gnu.org/software/bash/)

src/data/roadmaps/cyber-security/content/dd@9xbU_hrEOUtMm-Q09Fe6t.md

@@ -1,4 +1,4 @@
-# `dd` for Incident Response and Discovery
+# dd for Incident Response and Discovery
 
 `dd` (data duplicator) is a command-line utility used primarily for copying and converting data. It operates at a low level, reading and writing data block by block. This makes it extremely useful for creating exact bit-by-bit copies of storage devices, such as hard drives or memory sticks, and creating forensic images in raw or other formats.
 

src/data/roadmaps/cyber-security/content/directory-traversal@L0ROYh2DNlkybNDO2ezJY.md

@@ -7,5 +7,4 @@ Visit the following resources to learn more:
 - [@course@TryHackMe's room on Path Traversal & File Inclusion](https://tryhackme.com/r/room/filepathtraversal)
 - [@course@HackTheBox Academy's module on File Inclusion & Path Traversal](https://academy.hackthebox.com/course/preview/file-inclusion)
 - [@official@OWASP's article on Path Traversal](https://owasp.org/www-community/attacks/Path_Traversal)
-- [@article@Portswigger's guide on File Path Traversal](https://portswigger.net/web-security/file-path-traversal)
-- [@article@Acunetix's article on directory traversal](https://www.acunetix.com/websitesecurity/directory-traversal/)
+- [@article@Portswigger's guide on File Path Traversal](https://portswigger.net/web-security/file-path-traversal)

src/data/roadmaps/cyber-security/content/dlp@iolsTC-63d_1wzKGul-cT.md

@@ -4,5 +4,5 @@ Data Loss Prevention (DLP) refers to a set of strategies, tools, and processes u
 
 Visit the following resources to learn more:
 
-- [@article@What is DLP (data loss prevention)?](https://www.cloudflare.com/es-es/learning/access-management/what-is-dlp/)
+- [@article@What is DLP (data loss prevention)?](https://www.cloudflare.com/en-gb/learning/access-management/what-is-dlp/)
 - [@article@What is Data Loss Prevention (DLP)?](https://www.techtarget.com/whatis/definition/data-loss-prevention-DLP)

src/data/roadmaps/cyber-security/content/dns@r1IKvhpwg2umazLGlQZL1.md

@@ -1,6 +1,6 @@
 # DNS
 
-The Domain Name System (DNS) is like the internet's phonebook. It translates human-readable domain names, like "google.com," into IP addresses, like "172.217.160.142," which computers use to identify each other on the network. Without DNS, we'd have to remember and type in long strings of numbers to access websites, making the internet much less user-friendly.
+The Domain Name System (DNS) is like the internet's phonebook. It translates human-readable domain names, like "[google.com](http://google.com)," into IP addresses, like "172.217.160.142," which computers use to identify each other on the network. Without DNS, we'd have to remember and type in long strings of numbers to access websites, making the internet much less user-friendly.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/cyber-security/content/dos-vs-ddos@IF5H0ZJ72XnqXti3jRWYF.md

@@ -1,6 +1,6 @@
 # DoS vs DDoS
 
-A Denial-of-Service (DoS) attack is a type of cyberattack where an attacker attempts to make a machine or network resource unavailable to its intended users by overwhelming it with malicious traffic or requests, originating from a *single* source. A Distributed Denial-of-Service (DDoS) attack is similar, but the attack traffic comes from *multiple* compromised systems, creating a larger and more difficult-to-mitigate disruption.
+A Denial-of-Service (DoS) attack is a type of cyberattack where an attacker attempts to make a machine or network resource unavailable to its intended users by overwhelming it with malicious traffic or requests, originating from a _single_ source. A Distributed Denial-of-Service (DDoS) attack is similar, but the attack traffic comes from _multiple_ compromised systems, creating a larger and more difficult-to-mitigate disruption.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/cyber-security/content/linux@4frVcjYI1VlVU9hQgpwcT.md

@@ -7,6 +7,4 @@ Visit the following resources to learn more:
 - [@roadmap@Visit Linux Roadmap](https://roadmap.sh/linux)
 - [@course@Linux from scratch - Cisco](https://www.netacad.com/courses/os-it/ndg-linux-unhatched)
 - [@article@Linux Commands Cheat Sheet](https://cdn.hostinger.com/tutorials/pdf/Linux-Commands-Cheat-Sheet.pdf)
-- [@video@Linux in 100 Seconds](https://www.youtube.com/watch?v=rrB13utjYV4)
-- [@video@Introduction to Linux](https://youtu.be/sWbUDq4S6Y8)
-- [@feed@Explore top posts about Linux](https://app.daily.dev/tags/linux?ref=roadmapsh)
+- [@video@Introduction to Linux](https://youtu.be/sWbUDq4S6Y8)

src/data/roadmaps/cyber-security/content/operating-systems@UY6xdt_V3YMkZxZ1hZLvW.md

@@ -4,6 +4,6 @@
 
 Visit the following resources to learn more:
 
+- [@article@What is an operating system? - IBM](https://www.ibm.com/think/topics/operating-systems)
 - [@article@What is a Operating System?](https://en.wikipedia.org/wiki/Operating_system)
-- [@article@8 Different Types of Operating Systems With Examples](https://techspirited.com/different-types-of-operating-systems)
 - [@video@What is an operating system as fast as possible](https://www.youtube.com/watch?v=pVzRTmdd9j0)

src/data/roadmaps/cyber-security/content/port-scanners@iJRQHzh5HXADuWpCouwxv.md

@@ -4,5 +4,5 @@ Port scanners are essential tools in the troubleshooting and cybersecurity lands
 
 Visit the following resources to learn more:
 
-- [@article@Top 5 Best Port Scanners](https://securitytrails.com/blog/best-port-scanners)
+- [@article@Top 5 Free Open Port Check Tools in 2026](https://www.upguard.com/blog/best-open-port-scanners)
 - [@video@How To Use Nmap To Scan For Open Ports](https://www.youtube.com/watch?v=ifbwTt3_oCg)

src/data/roadmaps/cyber-security/content/power-shell@paY9x2VJA98FNGBFGRXp2.md

@@ -5,6 +5,6 @@ PowerShell is a command-line shell and scripting language developed by Microsoft
 Visit the following resources to learn more:
 
 - [@official@PowerShell.org](https://powershell.org/)
-- [@opensource@Learning PowerShell GitHub Repository](https://github.com/PowerShell/PowerShell/tree/master/docs/learning-powershell)
+- [@opensource@PowerShell for beginners](https://gist.github.com/devops-school/43dfcd57c0c807e83d01fc6a9639d3d9)
 - [@article@Microsoft's PowerShell Documentation](https://docs.microsoft.com/en-us/powershell/)
 - [@video@PowerShell Course](https://www.youtube.com/watch?v=ZOoCaWyifmI)

src/data/roadmaps/cyber-security/content/siem@c2kY3wZVFKZYxMARhLIwO.md

@@ -6,6 +6,4 @@ Visit the following resources to learn more:
 
 - [@article@Security 101: What is a SIEM? - Microsoft](https://www.microsoft.com/security/business/security-101/what-is-siem)
 - [@video@SIEM Explained - Professor Messer](https://www.youtube.com/watch?v=JEcETdy5WxU)
-- [@video@Wazuh | Open source SIEM](https://www.youtube.com/watch?v=3CaG2GI1kn0)
-- [@video@Splunk | The Complete Beginner Tutorial](https://www.youtube.com/playlist?list=PLY2f3p7xyMiTUbUo0A_lBFEwj6KdH0nFy)
-- [@video@Elastic Security | Build a powerful home SIEM](https://www.youtube.com/watch?v=2XLzMb9oZBI)
+- [@video@Wazuh | Open source SIEM](https://www.youtube.com/watch?v=3CaG2GI1kn0)

src/data/roadmaps/cyber-security/content/understand-the-definition-of-risk@ggAja18sBUUdCfVsT0vCv.md

@@ -1,6 +1,6 @@
 # Understanding Risk in Cybersecurity
 
-Risk, at its core, stems from the interplay of three components: a threat, a vulnerability, and the potential impact. A *threat* represents any actor or event with the potential to harm an asset. A *vulnerability* is a weakness or gap in security controls that a threat can exploit. The *impact* reflects the potential damage or loss that would occur if the threat successfully exploits the vulnerability. Analyzing these three aspects together allows us to quantify and manage risk effectively.
+Risk, at its core, stems from the interplay of three components: a threat, a vulnerability, and the potential impact. A _threat_ represents any actor or event with the potential to harm an asset. A _vulnerability_ is a weakness or gap in security controls that a threat can exploit. The _impact_ reflects the potential damage or loss that would occur if the threat successfully exploits the vulnerability. Analyzing these three aspects together allows us to quantify and manage risk effectively.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/cyber-security/content/urlscan@lMiW2q-b72KUl-2S7M6Vb.md

@@ -1,6 +1,6 @@
 # urlscan
 
-urlscan.io is a free service used to analyze websites. When you submit a URL to urlscan.io, it browses the site in an automated fashion, much like a real user. During this process, urlscan.io records the HTTP requests the site makes, screenshots of the page, and information about the technologies used. This data is then made available in a structured format, allowing users to identify potentially malicious or suspicious activities.
+[urlscan.io](http://urlscan.io) is a free service used to analyze websites. When you submit a URL to [urlscan.io](http://urlscan.io), it browses the site in an automated fashion, much like a real user. During this process, [urlscan.io](http://urlscan.io) records the HTTP requests the site makes, screenshots of the page, and information about the technologies used. This data is then made available in a structured format, allowing users to identify potentially malicious or suspicious activities.
 
 Visit the following resources to learn more:
 

src/data/roadmaps/cyber-security/content/wps@HSCGbM2-aTnJWUX6jGaDP.md

@@ -4,6 +4,6 @@ Wi-Fi Protected Setup (WPS) is a network security standard designed to make it e
 
 Visit the following resources to learn more:
 
-- [@article@What Is WPS and Why Is It Dangerous?](https://blog.pulsarsecurity.com/what-is-wps-why-is-it-dangerous)
 - [@article@WPS – What is it, and how does it work?](https://passwork.pro/blog/what-is-wps/)
+- [@article@Wi-Fi Protected Setup](https://en.wikipedia.org/wiki/Wi-Fi_Protected_Setup)
 - [@video@What is WPS in WiFi](https://www.youtube.com/watch?v=pO1r4PWf2yg)

src/data/roadmaps/golang/content/mocks-and-stubs@LjLbm4JEZ19howOkju7zQ.md

@@ -4,7 +4,7 @@ Mocks and stubs replace dependencies with controlled implementations for isolate
 
 Visit the following resources to learn more:
 
-- [@article@Test-Driven Development in Golang: Stubbing vs Mocking vs Not Mocking]((https://blog.stackademic.com/test-driven-development-in-golang-stubbing-vs-mocking-vs-not-mocking-5f23f25b3a63))
+- [@article@Test-Driven Development in Golang: Stubbing vs Mocking vs Not Mocking](https://blog.stackademic.com/test-driven-development-in-golang-stubbing-vs-mocking-vs-not-mocking-5f23f25b3a63)
 - [@article@Mock Solutions for Golang Unit Test](https://laiyuanyuan-sg.medium.com/mock-solutions-for-golang-unit-test-a2b60bd3e157)
 - [@article@Writing unit tests in Golang Part 2: Mocking](https://medium.com/nerd-for-tech/writing-unit-tests-in-golang-part-2-mocking-d4fa1701a3ae)
 - [@video@Mocks (Mocking), Stubs, and Fakes in Software Testing](https://www.youtube.com/watch?v=Ir7dl7XX9r4)

src/data/roadmaps/linux/content/tr@O9Vci_WpUY-79AkA4HDx3.md

@@ -5,4 +5,4 @@ The `tr` command in Linux is a command-line utility that translates or substitut
 Visit the following resources to learn more:
 
 - [@article@tr Command in Linux: 6 Useful Examples](https://linuxhandbook.com/tr-command/)
-- [@article@Linux tr Command: Character Translating](https://labex.io/tutorials/linux-linux-tr-command-character-translating-388064)
+- [@article@Linux tr Command with Practical Examples](https://labex.io/tutorials/linux-linux-tr-command-with-practical-examples-422963)

src/data/roadmaps/mlops/content/data-lineage@6XgP_2NLuiw654zvTyueT.md

@@ -5,5 +5,4 @@
 Visit the following resources to learn more:
 
 - [@article@What is Data Lineage?](https://www.ibm.com/topics/data-lineage)
-- [@article@What is a Feature Store](https://www.snowflake.com/guides/what-feature-store-machine-learning/)
-- [@article@How Should We Be Thinking about Data Lineage?](https://towardsdatascience.com/how-should-we-be-thinking-about-data-lineage-541ca5ab83d0/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
+- [@article@What is a Feature Store](https://www.snowflake.com/guides/what-feature-store-machine-learning/)

src/data/roadmaps/mlops/content/experiment-tracking@fGGWKmAJ50Ke6wWJBEgby.md

@@ -5,6 +5,4 @@
 Visit the following resources to learn more:
 
 - [@article@Experiment Tracking](https://madewithml.com/courses/mlops/experiment-tracking/#dashboard)
-- [@article@ML Flow Model Registry](https://mlflow.org/docs/latest/model-registry.html)
-- [@article@What is a Model Registry?](https://jfrog.com/learn/mlops/model-registry/)
-- [@video@Introduction to Experiment Tracking](https://www.youtube.com/watch?v=hctZDeB14-s)
+- [@article@ML Flow Model Registry](https://mlflow.org/docs/latest/model-registry.html)

src/data/roadmaps/mlops/content/lime@pVSlVHXIap0unFxLGM-lQ.md

@@ -1,9 +1,9 @@
-# Airflow
+# LIME
 
-Airflow is a platform to programmatically author, schedule, and monitor workflows. Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command-line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.
+LIME (Local Interpretable Model-agnostic Explanations) is a technique used to understand the predictions of machine learning models by approximating them locally with a more interpretable model. It focuses on explaining individual predictions by perturbing the input data around a specific instance and observing how the model's prediction changes. This allows one to identify which features are most important for that particular prediction, even if the underlying model is complex and opaque.
 
 Visit the following resources to learn more:
 
-- [@official@Airflow](https://airflow.apache.org/)
-- [@official@Airflow Documentation](https://airflow.apache.org/docs)
-- [@feed@Explore top posts about Apache Airflow](https://app.daily.dev/tags/apache-airflow?ref=roadmapsh)
+- [@official@lime](https://github.com/marcotcr/lime)
+- [@article@Explainable AI - Understanding and Trusting Machine Learning Models](https://www.datacamp.com/tutorial/explainable-ai-understanding-and-trusting-machine-learning-models)
+- [@video@Understanding LIME | Explainable AI](https://www.youtube.com/watch?v=CYl172IwqKs)

src/data/roadmaps/mlops/content/machine-learning-fundamentals@ulka7VEVjz6ls5SnI6a6z.md

@@ -5,7 +5,7 @@ Machine learning fundamentals encompass the key concepts and techniques that ena
 Visit the following resources to learn more:
 
 - [@roadmap@Visit the Dedicated Machine Learning Roadmap](https://roadmap.sh/machine-learning)
-- [@article@Everything I Studied to Become a Machine Learning Engineer (No CS Background)](https://towardsdatascience.com/everything-i-studied-to-become-a-machine-learning-engineer-no-cs-background/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
 - [@course@Fundamentals of Machine Learning - Microsoft](https://learn.microsoft.com/en-us/training/modules/fundamentals-machine-learning/)
 - [@course@MLCourse.ai](https://mlcourse.ai/)
-- [@course@Fast.ai](https://course.fast.ai)
+- [@course@Fast.ai](https://course.fast.ai)
+- [@article@Everything I Studied to Become a Machine Learning Engineer (No CS Background)](https://towardsdatascience.com/everything-i-studied-to-become-a-machine-learning-engineer-no-cs-background/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)

src/data/roadmaps/postgresql-dba/content/object-model@RoYP1tYw5dvhmkVTo1HS-.md

@@ -6,4 +6,4 @@ Visit the following resources to learn more:
 
 - [@official@Object Model](https://www.postgresql.org/docs/current/tutorial-concepts.html)
 - [@article@Understanding PostgreSQL: The Power of an Object-Relational](https://medium.com/@asadbukhari886/understanding-of-postgresql-the-power-of-an-object-relational-database-b6ae349c3f40)
-- [@article@PostgreSQL Server and Database Objects](https://www.postgresqltutorial.com/postgresql-tutorial/postgresql-server-and-database-objects/)
+- [@article@PostgreSQL Server and Database Objects](https://neon.com/postgresql/postgresql-tutorial/postgresql-server-and-database-objects)

src/data/roadmaps/rust/content/box@WjpkWH7f38y-bHUJ6ruGG.md

@@ -0,0 +1,9 @@
+# Box
+
+A `Box` in Rust is a smart pointer that allocates memory on the heap. It's primarily used to store data that has a size that's not known at compile time, or when you want to transfer ownership of data without copying it. Think of it as a way to put data on the heap and access it through a pointer, ensuring that the data is automatically deallocated when the `Box` goes out of scope.
+
+Visit the following resources to learn more:
+
+- [@official@Using Box<T> to Point to Data on the Heap](https://doc.rust-lang.org/book/ch15-01-box.html)
+- [@official@Smart Pointers](https://doc.rust-lang.org/book/ch15-00-smart-pointers.html#smart-pointers)
+- [@video@The Box Smart Pointer in Rust](https://www.youtube.com/watch?v=m76sRj2VgGo)

src/data/roadmaps/rust/content/rc@U9Bd-GO0QwYVLvESR4PTb.md

@@ -4,5 +4,4 @@
 
 Visit the following resources to learn more:
 
-- [@official@Rc<T> in std::rc](https://doc.rust-lang.org/std/rc/struct.Rc.html)
 - [@official@rct - The Reference Counted Smart Pointer](https://doc.rust-lang.org/book/ch15-04-rc.html#rct-the-reference-counted-smart-pointer)