iFixAi

Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.

https://github.com/ifixai-ai/iFixAi

FastHTML - Build Web Apps in Pure Python!

The video demonstrates building a polling application with FastHTML, covering form creation, POST request handling, and storing polls in a database. It also shows how to define database models using Python data classes, create a voting page, and process submitted votes.

https://www.youtube.com/watch?v=Ck0w7zqshjU

strands-agents / harness-sdk

Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.

https://github.com/strands-agents/harness-sdk

ASC

ASC is a super FAST Android decompiler front-end designed for Agents/Mobile Researchers.

https://github.com/MG1937/ASC

feder-cr / invisible_playwright_mcp

Playwright MCP server undetected by anti-bots and captchas: AI agent browses the web on anti-detect stealth Firefox, Python, undetected browser automation, scraping, computer use.

https://github.com/feder-cr/invisible_playwright_mcp

Fighting for #1 in the Ultimate Tic-Tac-Toe Arena

Tom Alard details how he built a highly competitive Ultimate Tic-Tac-Toe bot using a neural network trained on over 300 million self-play positions, a custom search algorithm, and SIMD-optimized C code. He also explains how he compressed the engine and neural network into a Python submission using UTF-16 encoding to bypass CodinGame’s 100,000-character limit, reaching second place on the...

https://tomalard.github.io/posts/fighting-for-1-in-the-ultimate-tic-tac-toe-arena/

redis-lua-py

Write Redis Lua scripts as real Python functions, not strings.

https://github.com/IgnaceMaes/redis-lua-py

Reef

Continual learning infra for self-improving agents.

https://github.com/Human-Agent-Society/reef

Hardware-Agnostic Models in vLLM

The article explains how vLLM is introducing hardware-agnostic layers so it can keep supporting diverse models and accelerators even as frontier models increasingly rely on hardware-specific “flat” implementations. The new path remains compatible with torch.compile and, in tests on NVIDIA H100s, delivered total token throughput within 3.4% of the native implementation across three recent...

https://pytorch.org/blog/hardware-agnostic-models-in-vllm/

PyPy v8.0.0

PyPy 8.0.0 introduces its first Python 3.12 interpreter as a beta, alongside Python 2.7 and 3.11 releases, and raises the minimum glibc requirement for Linux binaries to 2.28. The release also advances compatibility with CPython’s limited C API and abi3 wheels, improves RPython code generation, and drops HPy as a default backend, though abi3 wheel installation support is not yet complete.

https://pypy.org/posts/2026/09/pypy-v800-release.html

Bad evals, my own: five exercises from two LLM judges

The author uses five exercises from two real LLM judges to expose evaluation pitfalls, including inconsistent results, biased test sets, misleading metrics, and pass/fail thresholds that become unreliable as test suites grow. He shows why trustworthy evaluations require representative data, clearly defined metrics, repeated testing, and preserved run artifacts, revealing flaws in his own...

https://digline.dev/blog/bad-evals-my-own/

ZeroModels

ZeroModels is an open-source Keras 3 library of pretrained models spanning vision, language, speech, depth estimation, and multimodal tasks.

https://github.com/IMvision12/ZeroModels

Kev

tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own.

https://github.com/jaredpalmer/kev

nonetrace: tells you where a None came from when Python crashes on it

When Python crashes on None, it points at the wrong line. nonetrace shows which call returned the None, why, and the fix.

https://pypi.org/project/nonetrace/

DeepTeam

DeepTeam is a framework to red team LLMs and AI agents.

https://github.com/confident-ai/deepteam

This Design Pattern Replaces an Entire Class Hierarchy

This video compares three ways to model type-based variation in Python: subclasses, storing a type value such as an enum, and representing each variation as an object. Using a subscription system, it introduces the Type Object pattern and explains when each approach is the better fit.

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

Put the Arithmetic in the Tool: an MCP Server for an AWS Waste Scanner

The article shows how to add an MCP server to a Python-based AWS cost scanner so AI agents can query computed totals, breakdowns, filters, and cleanup plans without doing arithmetic themselves. It also covers JSON-RPC over stdio, read-only tool design, end-to-end testing, rounding consistency, and integration with Claude Code.

https://dev.to/aws-builders/put-the-arithmetic-in-the-tool-an-mcp-server-for-an-aws-waste-scanner-3n79

superdesigndev / treg

OpenRouter for agent tools. Join community here: https://discord.gg/6mQYYfFMAn

https://github.com/superdesigndev/treg

Share how you use Django with Django Probe

The post introduces Django Probe, a tool that scans Django projects and anonymously aggregates how framework APIs and patterns are actually used. The goal is to give Django maintainers better data for decisions around deprecations, new features, documentation, and community priorities.

https://www.better-simple.com/django/2026/09/17/share-how-you-use-django-with-django-probe/