Here's a delightful project by Tom Gally, inspired by my pelican SVG benchmark. He asked Claude to help create more prompts of the form Generate an SVG of [A] [doing] …

A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows - ComposioHQ/awesome-claude-skills

Max Woolf provides an exceptional deep dive into Google's Nano Banana aka Gemini 2.5 Flash Image model, still the best available image manipulation LLM tool three months after its initial …

against chat interfaces ✦ a brief history of artificial intelligence ✦ and the (worthwhile) problem of other minds

Contribute to humanlayer/advanced-context-engineering-for-coding-agents development by creating an account on GitHub.

A curated collection of fun and creative examples generated with Nano Banana🍌, Gemini-2.5-flash-image based model. This repository showcases diverse AI-generated visuals and prompts, highlighting t...

This methodology provides a structured approach for collaborating with AI systems on software development projects. It addresses common issues like code bloat, architectural drift, and context dilu...

“Don’t use chatbots as search engines” was great advice for several years... until it wasn’t. I wrote about how good OpenAI’s o3 was at using its Bing-backed search tool back …

Developers can use their AI tool of choice for spec-driven development with this open source toolkit.

My experience creating software with LLM coding agents - Part 2 This post details my experiences creating software with LLM coding agents,...

This blog post intends to be a definitive guide to context engineering fundamentals from the perspective of an engineer who builds commercial coding assistants and harnesses for a living. Just two weeks ago, I was back over in San Francisco, and there was a big event on Model Context Protocol

Discover over 600 of the worlds best AI prompts and level up your AI game!

Effortlessly generate a context block to quickly paste into any AI chat. Works on any OS, from any editor. Removing the friction between your project/repo and AI. This is not meant to replace Agent software.

Model Context Protocol (MCP) has became the standard for tool calling when building agents, but contrary to popular belief your LLM does not need to understand MCP.

LLMs have unlocked powerful new capabilities, but the dominant pattern for using them, writing increasingly desperate prompts, is fragile, unscalable, and of...

Using an LLM to call tools in a loop is the simplest form of an agent. This architecture, however, can yield agents that are “shallow” and fail to plan and act over longer, more complex tasks. Applications like “Deep Research”, “Manus”, and “Claude Code” have gotten around this limitation by implementing a combination of four things: a planning tool, sub agents, access to a file system, and a detailed prompt. Acknowledgements: this exploration was primarily inspired by Claude Code and reports o

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference DSPy: Prompt Optimization for LM Programs Michael Ryan, Stanford It has never been easier to build amazing LLM powered applications. Unfortunately engineering reliable and trustworthy LLMs remains challenging. Instead, practitioners should build LM Programs comprised of several composable calls to LLMs which can be rigorously tested, audited, and optimized like other software systems. In this talk I will introduce the idea of LM Programs in DSPy: The library for Programming — not Prompting LMs. I will demonstrate how the LM Program abstraction allows the creation of automatic optimizers for LM Programs which can optimize both the prompts and weights in an LM Program. I will conclude with an introduction to MIPROv2: our latest and highest performing prompt optimization algorithm for LM Programs. Michael Ryan is a masters student at Stanford University working on optimization for Language Model Programs in DSPy and Personalizing Language Models. His work has been recognized with a Best Social Impact award at ACL 2024, and an honorable mention for outstanding paper at ACL 2023. Michael co-lead the creation of the MIPRO & MIPROv2 optimizers, DSPy’s most performant optimizers for Language Model Programs. His prior work has showcased unintended cultural and global biases expressed in popular LLMs. He is currently a research intern at Snowflake.

Your robot experience started simple. You typed a question into a chatbot… just to see. Can it answer that question? I'd be impressed if it did. Your query was simple. A simple knowledge question that with a little effort using legacy tools like Google, you would have discovered yourself, but the r

VS Code AI Customization - Learn to use custom instructions, prompt files, and custom chat modes to personalize AI code generation, reviews, and chat responses.

claude code system prompt. Contribute to kn1026/cc development by creating an account on GitHub.

GitHub Spark was released in public preview yesterday. It’s GitHub’s implementation of the prompt-to-app pattern also seen in products like Claude Artifacts, Lovable, Vercel v0, Val Town Townie and Fly.io’s …

Context engineering is rising in popularity because prompting alone isn't enough—we're still figuring out how to build reliable AI systems. From extracting s...

The DSPy OSS team at Databricks and beyond is excited to present DSPy 3.0, targeted for release close to DAIS 2025. We will present what DSPy is and how it evolved over the past year. We will discuss greatly improved prompt optimization and finetuning/RL capabilities, improved productionization and observability via thorough and native integration with MLflow, and lessons from usage of DSPy in various Databricks R&D and professional services contexts. Talk By: Krista Opsahl-Ong, Research Engineer, Databricks ; Omar Khattab, Research Scientist, Databricks Databricks Named a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms: https://www.databricks.com/blog/databricks-named-leader-2025-gartner-magic-quadrant-data-science-and-machine-learning Build and deploy quality AI agent systems: https://www.databricks.com/product/artificial-intelligence See all the product announcements from Data + AI Summit: https://www.databricks.com/events/dataaisummit-2025-announcements Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Large Language Models (LLMs) excel at understanding messy, real-world data, but integrating them into production systems remains challenging. Prompts can be unruly to write, vary by model and can be difficult to manage in the large context of a pipeline. In this session, we'll demonstrate incorporating LLMs into a geospatial conflation pipeline, using DSPy. We'll discuss how DSPy works under the covers and highlight the benefits it provides pipeline creators and managers. Talk By: Drew Breunig, Data Science Leader & Strategist, Overture Maps Foundation Databricks Named a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms: https://www.databricks.com/blog/databricks-named-leader-2025-gartner-magic-quadrant-data-science-and-machine-learning Build and deploy quality AI agent systems: https://www.databricks.com/product/artificial-intelligence See all the product announcements from Data + AI Summit: https://www.databricks.com/events/dataaisummit-2025-announcements Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

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Full guide on claude tips and tricks and how you can optimise your claude code the best & strive to find every command possible even hidden ones! - zebbern/claude-code-guide

Adding unreleated text to questions can cause LLMs to consistently stumble.