AI/ML

I’ve been experimenting with a pattern for LLM usage recently that’s working out really well: asynchronous code research tasks. Pick a research question, spin up an asynchronous coding agent and …

They're like riding a bike: easy, and you don't get it until you try.

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Max Mynter - Full Stack Machine Learning Engineer. Explore my blog and portfolio. Multiple years of experience in data science, software engineering, and machine learning.

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

Learn how to create custom chat modes in VS Code for GitHub Copilot to enhance your workflow in large, complex projects with specialized AI configurations.

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

The GPT-5 launch was uh, rough. A lot went wrong here, and I want to talk about what really happened...Thank you Kilo Code for sponsoring! Check them out at:...

Claude Code is the most delightful AI agent/workflow I have used so far. Not only does it make targeted edits or vibe coding throwaway tools less annoying, ...

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

Lauren Goode convinced her editors at Wired to let her spend a couple of days at a tech company called Notion learning how to vibe-code (i.e. AI-assisted computer programming): Why Did a $10 Billion Startup Let Me Vibe-Code for Them — and Why Did I Love I

We want to make Piccalilli’s position absolutely clear on LLMs and generative AI. It’s important for you, the reader, to understand our position.

AGENTS.md is a simple, open format for guiding coding agents. Think of it as a README for agents.

Personal blog of Stephen Diehl - Software engineer writing about technology, programming, and the future

Explore, build, and refine codebases with Claude Code.

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

It is wild to think that it has been only a handful of weeks. Claude Code has considerably changed my relationship to writing and maintaining code at scale. I still write code at the same level of quality, but I feel like I have a new freedom of expression which is hard to fully articulate. Claude Code has decoupled myself from writing every line of code, I still consider myself fully responsible for everything I ship to Puzzmo, but the ability to instantly create a whole scene instead of going line by line, word by word is incredibly powerful.

The glamourous AI coding agent for your favourite terminal 💘 - charmbracelet/crush

Some of my attempts to make agents work better that just didn’t work.

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.

We built a browser-based terminal controller in one day using Claude Code, named pipes, and Xterm.js. No SSH needed, just open your browser and start typing. Check and command your agents on the go!

I’m a little salty that neither Anthropic nor Google reached out to me before they released their terminal-based AI coding agents.

Will McGugan is building his own take on a terminal coding assistant, in the style of Claude Code and Gemini CLI, using his Textual Python library as the display layer. …

Build, debug, and optimize AI agents using DSPy and MLflow.

One of my favorite AI dev products today is Full Line Code Completion in PyCharm (bundled with the IDE since late 2023). It’s extremely well-thought out,...

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

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

How I'm using GitHub Copilot agent mode with MCP to supercharge my development workflow through structured planning, implementation, and testing.