Best of Prompt Engineering — October 2025

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   Article

   Simon Willison·30w

   Claude Skills are awesome, maybe a bigger deal than MCP

   Anthropic introduced Claude Skills, a new pattern for extending LLM capabilities using Markdown files with instructions, scripts, and resources. Skills are token-efficient (loading only when needed), depend on code execution environments, and are simpler to create than MCP implementations. The system enables general computer automation beyond just coding tasks, with skills shareable as single files or folders. Skills work with other models too, potentially sparking wider adoption than the Model Context Protocol.

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2. 2
   Article

   Reid Burke·28w

   claude-cookbooks/coding/prompting_for_frontend_aesthetics.ipynb at 293cde3d3fe1e29ce90b535ccfd311c289302d0c · anthropics/claude-cookbooks

   A Jupyter notebook cookbook from Anthropic demonstrating techniques for prompting Claude to generate aesthetically pleasing frontend code. Part of a collection showcasing effective ways to use Claude for coding tasks, specifically focused on improving visual design outcomes through better prompting strategies.

   66
3. 3
   Article

   Javarevisited·28w

   I’ve Read 20+ Books on AI and LLM — Here Are My Top 5 Recommendations for 2026

   A curated list of five essential books for learning AI and LLM engineering, covering practical topics from building and fine-tuning models to production deployment. The recommendations include hands-on guides for prompt optimization, retrieval-augmented generation, model evaluation, infrastructure design, and understanding transformer architectures from scratch. Each book emphasizes production-ready engineering practices including monitoring, cost optimization, and system design rather than pure theory.

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4. 4
   Article

   LangChain·28w

   Introducing LangSmith’s No Code Agent Builder

   LangSmith introduces Agent Builder, a no-code platform that enables non-developers to create AI agents without writing code. Unlike visual workflow builders, it focuses on agent-based decision-making through four core components: prompts, tools (via MCP integration), triggers, and subagents. The platform simplifies prompt creation through guided conversations and includes built-in memory that learns from corrections over time. Built on the deepagents package and informed by LangChain and LangGraph development, it targets internal productivity use cases like email assistants, chat automation, and Salesforce integrations.

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5. 5
   Article

   J-HAYER - Builders gonna build·29w

   Learn Claude's new Skills

   Claude introduces Agent Skills, a new capability that allows developers to package domain expertise into reusable modules instead of managing complex monolithic prompts. Skills are composable, portable across platforms, loaded on-demand to save context window space, and can include executable code for precise operations. Companies like Box are already using Skills to automate tasks like transforming unstructured files into branded presentations.

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6. 6
   Article

   UX Planet·31w

   UI Design with ChatGPT 5

   Demonstrates how to use ChatGPT 5 to generate UI designs for a mobile food delivery app through structured prompts. Covers the complete workflow from writing detailed markdown prompts to generating visual mockups, exporting to Figma, and producing working code. Includes practical tips for effective prompt writing, such as using markdown formatting, describing layout and style explicitly, and maintaining clear hierarchy. Shows improvements over ChatGPT 4o in following design specifications and producing cleaner outputs.

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   Article

   Daily Dose of Data Science | Avi Chawla | Substack·29w

   ARQ: A New Structured Reasoning Approach for LLMs

   Researchers introduced Attentive Reasoning Queries (ARQs), a structured reasoning approach that prevents LLM hallucinations by guiding models through explicit, domain-specific questions encoded in JSON schemas. Unlike free-form techniques like Chain-of-Thought, ARQs force LLMs to follow controlled reasoning steps, achieving a 90.2% success rate compared to 86.1% for CoT. The approach is implemented in Parlant, an open-source framework for building instruction-following agents, where ARQs are integrated into guideline proposers, tool callers, and message generators to maintain alignment throughout multi-turn conversations.

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