AI/ML

Generate hands-on, multi-part technical tutorials on demand, with LLM skills tuned to make content approachable. Then you work through them yourself, by hand ✋ - devenjarvis/lathe

Both sides are grappling with a real existential threat, and both sides feel like they are screaming into the void. Here's how to close the gap and get everyone pulling in the same direction.

In my predictions for 2030 I wrote that tech writers would be using specialized LLMs, running locally on powerful hardware. I see hints of this move to “local first” among engineering pundits, but we’re not there yet, in part because of how much more powerful connected frontier models are. That doesn’t mean we can’t experiment, though. That’s precisely what I did last week, trying to fine tune an instruct model to write like a software technical writer from the 80s and 90s.

JOIN THE COMMUNITY & COURSES📕 Read Sketch Your Mind: https://commu...

DeepSWE measures frontier coding agents on original, long-horizon software engineering tasks.

A deep dive into Claude Code for daily users. Covers the .claude directory, CLAUDE.md the way Boris writes it, CLAUDE.local.md, Skills with real examples, custom subagents, plugins, underused commands like /goal and /insights, MCPs, and the workflow patterns the Anthropic team actually uses.

Where open-weights local AI stands today: dense vs MoE, the model picks, the hardware picks by budget, and what would flip the picture next.

Looks like this ended up on the HN front-page: HN Thread Late last year I started writing a math blog and decided to use LLMs to polish/enhance my writin...

Scripts for agents, shared between my repositories. - steipete/agent-scripts

Today, I'm pleased to release my latest free and open source project: RemCTL, a power-user Reminders CLI that, unlike others, exposes all the latest Reminders features as of iOS and macOS 26. RemCTL supports reading and writing subtasks, tags, sections, rich links, image attachments, grocery lists, and even templates. It's available on GitHub here, and

Write professional-grade skills for agents, validate them using LLMs, and maintain a lean context window. - mgechev/skills-best-practices

Like many I was revolted by the video of Itamar Ben-Gvir taunting and humiliating courageous international citizens determined to get supplies to Palestine. If you haven’t seen it, the video shows the Israeli Minister humiliating Gaza flotilla activists, who are shown kneeling in rows, heads bowed, hands cable-tied behind their backs.

Turn plain English into real Apple Shortcuts. A Claude Code & Codex plugin from MacStories.

Good report: Executive Summary: Let’s say you wanted to make sure that your AI is secure. Can you just maximize the security and privacy benchmark and call it a day? Nope, because benchmarks don’t actually work for measuring AI capabilities (even when they are NOT emergent systemic properties like security). So let’s take a step back: how do you measure security in the first place? Good question. Over the last 30 years, security engineering for software evolved from black box penetration testing, through whitebox code analysis and architectural risk analysis to de facto process-driven standards like the Building Security In Maturity Model (BSIMM). Software had a very deep impact on business operations, and it appears that AI is going to have an even deeper impact. Will a software security-like measurement move work for AI? Probably. In the meantime we can make real progress in AI security by cleaning up our WHAT piles and managing risk by identifying and applying good assurance processes. (Spoiler alert: no matter what we do, we still don’t get a security meter for AI, so we need to be extra vigilant about security.)...

Do androids dream of second brains? I don't know, but in this video I pose the question anyway. I demonstrate how I use the concept of observability to expos...

We often describe our personal knowledge management systems as “second brains” — but can we really say they think for themselves? In this video, I make the case for instrumenting your vault with an observability stack and layering AI on top, not because it’ll turn your notes into a brain, but because it might get us closer than anything else has. This is the video version of the talk I gave at PKM Summit 2026 in Utrecht earlier this year, with the live demos cleaner and the dashboards working without the conference wifi gods getting in the way.

Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm

These are commands I use with agents, mostly Claude - villainscode/pi-agent

Most AI coding tools can generate diagrams, but they look terrible (wrong spacing, overlapping elements, no visual hierarchy, etc.). I spent weeks building a...

Sub-agents for pi with Claude Code look and feel — parallel execution, live widget, custom agent types, mid-run steering and more ... - tintinweb/pi-subagents

Hello guys! Today i want to share my Pi agent setup, i think i got something in hands here that can benefit the community to really get a...

My personal pi coding agent configuration - skills and extensions - HazAT/pi-config

The setup I use for pi. Changes a ton, don't recommend hard copying it, just a taste of what's possible with it - davis7dotsh/my-pi-setup

Scott's Dope Skills

As I mentioned in a recent issue of MacStories Weekly for Club members, I believe that reliable dictation and text-to-speech are largely solved problems in the AI industry right now for most languages. There are certainly subtle differences between the latest models and not-so-subtle discrepancies when you consider local (and free) transcription models versus cloud-hosted

A meaningful text can be hidden inside another, completely different yet still coherent and plausible, text of the same length. For example, a tweet containing a harsh political critique could be embedded in a tweet that celebrates the same political leader, or an ordinary product review could conceal a secret manuscript. This uncanny state of affairs is now possible thanks to Large Language Models, and in this paper we present Calgacus, a simple and efficient protocol to achieve it. We show that even modest 8-billion-parameter open-source LLMs are sufficient to obtain high-quality results, and a message as long as this abstract can be encoded and decoded locally on a laptop in seconds. The existence of such a protocol demonstrates a radical decoupling of text from authorial intent, further eroding trust in written communication, already shaken by the rise of LLM chatbots. We illustrate this with a concrete scenario: a company could covertly deploy an unfiltered LLM by encoding its answers within the compliant responses of a safe model. This possibility raises urgent questions for AI safety and challenges our understanding of what it means for a Large Language Model to know something.

Check out Oracle’s post on agents memory: https://fandf.co/4dd3HOw---Obsidian was always my favorite note taking system where I've been happily building and ...