Add 14 TDS articles to ai-engineer roadmap

2026-10-24 01:08:07 +08:00 · 2026-10-07 14:51:58 +02:00
parent cfc89a1d4b
commit 283273747d
7 changed files with 21 additions and 7 deletions
@@ -6,4 +6,7 @@ Visit the following resources to learn more:

 - [@article@Building an AI Agent Tutorial - LangChain](https://python.langchain.com/docs/tutorials/agents/)
 - [@article@How to Design My First AI Agent](https://towardsdatascience.com/how-to-design-my-first-ai-agent/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
- [@video@The Complete Guide to Building AI Agents for Beginners](https://youtu.be/MOyl58VF2ak?si=-QjRD_5y3iViprJX)
+- [@video@The Complete Guide to Building AI Agents for Beginners](https://youtu.be/MOyl58VF2ak?si=-QjRD_5y3iViprJX)
+- [@article@Multi-Agent Communication with the A2A Python SDK](https://towardsdatascience.com/multi-agent-communication-with-the-a2a-python-sdk/)
+- [@article@From Data to Stories: Code Agents for KPI Narratives](https://towardsdatascience.com/from-data-to-stories-code-agents-for-kpi-narratives/)
+- [@article@Inside Google’s Agent2Agent (A2A) Protocol: Teaching AI Agents to Talk to Each Other](https://towardsdatascience.com/inside-googles-agent2agent-a2a-protocol-teaching-ai-agents-to-talk-to-each-other/)
@@ -5,4 +5,5 @@ The Hugging Face Inference SDK is a powerful tool that allows developers to easi
 Visit the following resources to learn more:

 - [@official@Inference](https://huggingface.co/docs/huggingface_hub/en/package_reference/inference_client)
- [@article@Endpoint Setup](https://www.npmjs.com/package/@huggingface/inference)
+- [@article@Endpoint Setup](https://www.npmjs.com/package/@huggingface/inference)
+- [@article@Evaluating LLMs for Inference, or Lessons from Teaching for Machine Learning](https://towardsdatascience.com/evaluating-llms-for-inference-or-lessons-from-teaching-for-machine-learning/)
@@ -5,4 +5,5 @@ LLM evaluations are structured tests that measure how well a model or AI system
 Visit the following resources to learn more:

 - [@article@LLM evaluation: a beginner's guide](https://www.evidentlyai.com/llm-guide/llm-evaluation)
- [@video@Welcome to the LLM evaluation course](https://www.youtube.com/watch?v=rHs0sP7b5fM&list=PL9omX6impEuMgDFCK_NleIB0sMzKs2boI)
+- [@video@Welcome to the LLM evaluation course](https://www.youtube.com/watch?v=rHs0sP7b5fM&list=PL9omX6impEuMgDFCK_NleIB0sMzKs2boI)
+- [@article@LLM-as-a-Judge: A Practical Guide](https://towardsdatascience.com/llm-as-a-judge-a-practical-guide/)
@@ -5,4 +5,8 @@ LLM observability is the practice of monitoring and understanding what happens i
 Visit the following resources to learn more:

 - [@article@What is LLM observability?](https://www.ibm.com/think/topics/llm-observability)
- [@article@LLM Evaluation and AI Observability for Agent Monitoring](https://blog.jetbrains.com/pycharm/2026/05/llm-evaluation-and-ai-observability-for-agent-monitoring/)
+- [@article@LLM Evaluation and AI Observability for Agent Monitoring](https://blog.jetbrains.com/pycharm/2026/05/llm-evaluation-and-ai-observability-for-agent-monitoring/)
+- [@article@Code Agents: The Future of Agentic AI](https://towardsdatascience.com/code-agents-the-future-of-agentic-ai/)
+- [@article@Can AI Truly Develop a Memory That Adapts Like Ours?](https://towardsdatascience.com/can-ai-truly-develop-a-memory-that-adapts-like-ours/)
+- [@article@Boost Your LLM Output and Design Smarter Prompts: Real Tricks from an AI Engineer’s Toolbox](https://towardsdatascience.com/boost-your-llm-outputdesign-smarter-prompts-real-tricks-from-an-ai-engineers-toolbox/)
+- [@article@Programming, Not Prompting: A Hands-On Guide to DSPy](https://towardsdatascience.com/programming-not-prompting-a-hands-on-guide-to-dspy/)
@@ -6,4 +6,5 @@ Visit the following resources to learn more:

 - [@course@Model Context Protocol (MCP) Course](https://huggingface.co/learn/mcp-course/en/unit0/introduction)
 - [@official@Understanding MCP clients](https://modelcontextprotocol.io/docs/learn/client-concepts#understanding-mcp-clients)
- [@video@The Complete Guide to Building AI Agents for Beginners](https://youtu.be/MOyl58VF2ak?si=-QjRD_5y3iViprJX)
+- [@video@The Complete Guide to Building AI Agents for Beginners](https://youtu.be/MOyl58VF2ak?si=-QjRD_5y3iViprJX)
+- [@article@Agents, APIs, and the Next Layer of the Internet](https://towardsdatascience.com/agents-apis-and-the-next-layer-of-the-internet/)
@@ -6,4 +6,7 @@ Visit the following resources to learn more:

 - [@article@4 context engineering strategies every AI engineer needs to know](https://newsletter.owainlewis.com/p/4-context-engineering-strategies)
 - [@article@Context Engineering](https://blog.langchain.com/context-engineering-for-agents/)
- [@article@Is RAG Dead? The Rise of Context Engineering and Semantic Layers for Agentic AI](https://towardsdatascience.com/beyond-rag/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
+- [@article@Is RAG Dead? The Rise of Context Engineering and Semantic Layers for Agentic AI](https://towardsdatascience.com/beyond-rag/?utm_source=roadmap&utm_medium=Referral&utm_campaign=TDS+roadmap+integration)
+- [@article@New to LLMs? Start Here](https://towardsdatascience.com/new-to-llms-start-here/)
+- [@article@How to Build an MCQ App](https://towardsdatascience.com/how-to-build-an-mcq-app/)
+- [@article@Agentic RAG Applications: Company Knowledge Slack Agents](https://towardsdatascience.com/agentic-rag-applications-company-knowledge-slack-agents/)
@@ -5,4 +5,5 @@ Tokens are fundamental units of text that LLMs process, created by breaking text
 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@Understanding Tokens and Parameters in Model Training: A Deep Dive](https://www.functionize.com/blog/understanding-tokens-and-parameters-in-model-training)
+- [@article@Understanding Tokens and Parameters in Model Training: A Deep Dive](https://www.functionize.com/blog/understanding-tokens-and-parameters-in-model-training)
+- [@article@Connecting the Dots for Better Movie Recommendations](https://towardsdatascience.com/connecting-the-dots-for-better-movie-recommendations/)