The Simplest MCP Example Possible in Python

The post shows the simplest Python example of MCP (Model Context Protocol) for connecting a local LLM like Llama 3.2 to tools. It uses fastmcp and ollama packages with two scripts: mcpserver.py for time/date tools and ollamaclient.py to run the chat loop.

https://inventwithpython.com/blog/basic-mcp-python-example.html

Labb - UI components for Django

This video looks at labb - a UI component library for Django apps that builds on top of TailwindCSS, DaisyUI, django-cotton and Alpine.js. This library has over 70 components that can be dropped into Django projects, and makes it easy to add custom themes, for example using DaisyUI Theme Generator.

https://www.youtube.com/watch?v=ZZd7cvbJ-1w

DRY Often Makes Your Code Worse

A DRY refactor can make code worse when it removes duplication by hiding different behaviors behind flags and shared abstractions. Better refactoring focuses on separating responsibilities and making behavior clear, not just making the code look smaller.

https://www.youtube.com/watch?v=GmlZBdKhl9Y

aidlc-workflows

AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents.

https://github.com/awslabs/aidlc-workflows

OpenSwarm

Claude code for everything except coding.

https://github.com/VRSEN/OpenSwarm

In-Kernel Broadcast Optimization: Co-Designing Kernels for RecSys Inference

In-Kernel Broadcast Optimization (IKBO) eliminates redundant user-embedding replication by fusing broadcast logic directly into interaction kernels, significantly reducing memory bandwidth and compute waste. This co-design approach delivers up to a two-thirds reduction in latency across Meta's recommendation stack, optimized for high-performance hardware like NVIDIA H100 and Meta’s MTIA.

https://pytorch.org/blog/in-kernel-broadcast-optimization-co-designing-kernels-for-recsys-inference/

nb-cli: A Command-Line Interface for AI Agents and Notebook Automation

The article introduces nb-cli, a Rust-built command-line interface engineered to let developers and AI agents programmatically read, write, and execute Jupyter notebooks without needing a running server. It highlights an AI-optimized Markdown format that exposes structured token-efficient code and cell metadata, enabling language models and automated CI/CD pipelines to manipulate noteboo...

https://blog.jupyter.org/nb-cli-a-command-line-interface-for-ai-agents-and-notebook-automation-996ad7edacd9

semble

Fast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read.

https://github.com/MinishLab/semble

django-completion

Project-aware tab completion for Django's manage.py.

https://github.com/soldatov-ss/django-completion

CodeBoarding

Interactive architecture diagrams for codebases.

https://github.com/CodeBoarding/CodeBoarding

geo-seo-claude

GEO-first, SEO-supported. Optimize websites for AI-powered search engines.

https://github.com/zubair-trabzada/geo-seo-claude

django-q2 - Background Tasks in Django (Celery alternative!)

The video explores django-q2, a lightweight alternative to Celery for handling background jobs and asynchronous task processing in Django applications. It highlights how django-q2 simplifies setup and integration while providing built-in support for async workers, scheduled tasks, and Django Admin management features.

https://www.youtube.com/watch?v=0hRDCrxfHug

Watching for file changes on macOS

This post details how to build a lightweight tool for monitoring file system activity on macOS without relying on third-party dependencies. It explains how to implement a Swift script that interfaces directly with Apple's native FSEvents API and forwards those live change notifications to a Python environment via stdout.

https://alexwlchan.net/2026/watch-files-on-macos/

Agent Hooks: Deterministic Control for Agent Workflows

The post is about agent hooks as a control layer that makes AI behavior more deterministic by enforcing rules at specific lifecycle points, instead of relying on prompts alone. It emphasizes using hooks for policy enforcement, validation, and observability so teams can block bad actions, add guardrails, and make agent workflows more production-safe.

https://nader.substack.com/p/agent-hooks-deterministic-control

Feloxi

Self-hosted monitoring for Python task queues. Live dashboards, searchable task history, and alerting that fires.

https://github.com/thesaadmirza/feloxi

HKUDS / ViMax

"ViMax: Agentic Video Generation (Director, Screenwriter, Producer, and Video Generator All-in-One)"

https://github.com/HKUDS/ViMax