Here’s an Apple secret: Success comes from culture, not technology. Like many at Apple, I worked for many years under John Brandon, our longtime head of sales. He had his “Top Ten Rules for Success” which I carried around and lived by. It’s easy to spot someone from Brandon’s team by how they collaborate. I tried to be one of them. I mopped the floor (literally at times), I shared everything I knew without gatekeeping, I always assumed the customer knew their business. I think about AI the same way. Most AI advice right now is for builders. Almost nobody is helping the marketers, sales engineers, and execs who actually have to put AI in front of customers. That’s the gap I work in. I left Apple last month after 22 years. After some thinking and a lot of conversations, I’m now doing what I did inside Apple, but for other organizations: AI positioning, helping businesses understand AI, and creating Apple-level presentations and content.

Marketing is changing faster than any other function in B2B. Decades of best practice are being upended: - Don’t be controversial > controversy sells - Use proven channels > new channels break through noise - Authoritative institutions > authentic individuals - Abstract value > concrete functionality - Consistency and consensus > speed It’s hard to relearn, but the returns are huge to those that do.

Algorithmic art with an evolving mandala of triangles, in red, blue, tan, and black #AlgorithmicArt #GenerativeArt

fun skill! Make a consistent illustration-style avatar you can re-use for any pose or purpose. I made an avatar for my Hermes Agent bot, Cadence. She is my personal assistant, health coach, and fitness coach.

My Hermes daily AI update repping @mvanhorn’s last30days

Being a blissfully unbothered optimist who brushes everything off predicts better health nearly a decade later. Ripped apart by your boss? Thank them for the feedback and forget it by dinner. Made a mistake? Useful data. Bad day? What bad day?

The highlight of WWDC for me was how much Apple are leaning into local AI. Five highlights that stood out: 1. you can now run a complete agentic loop entirely on-device ; the model reasons, calls tools, and acts without anything leaving the Mac (officially supported). 2.MLX has matured into a real platform rather than a research demo, with a full local stack: model runtime, agent loop, and tool integration. 3. Coding agents like OpenCode now run natively and integrate directly into Xcode, so the agent works inside your actual dev environment. 4. MLX can spread inference and training across multiple networked Macs over Thunderbolt, so you're no longer capped by a single machine's memory or compute (cant wait to try this) 5. Speed is no longer the catch; MLX has closed the gap enough that a local agent feels responsive rather than like a compromise.

One of my personal favorite features announced at WWDC will I suspect be a sleeper hit: container machines, allowing your Mac to run a lightweight, persistent Linux environment with your home directory and repos automatically mounted: github.com/apple/container/b…

Here’s a live, real Siri AI demo. Via Mike Rockwell.

We are in the middle of the singularity. The most interesting period in human history. And most people are too busy to care.

I'm finding Gemini image and video generation to be nearly useless due to nearly any request, even very innocuous ones, hitting guardrails.

Just out and on my reading stack @trevorpaglen’s “How to see like a machine” and @CaballeroAnaMa’s new book of poetry “Material”

Grok (dvd slot and weird screen - not good)

OpenAI

Gemini (nano banana 2)

Proto-GIF’s!!!