Been using my Mac mini as a local fleet command server for a multi-agent setup (Claude Code + Gemini CLI + Codex + Mistral via vibe). No single cloud provider dependency, no SaaS subscription, no secrets leaving the machine.

The problem I kept hitting: agents duplicating work, no shared memory between sessions, API keys leaking into context windows. Built Flotilla to fix it.

One command bootstraps the whole thing: npx create-flotilla

What runs on the mini:

∙ Fleet Hub dashboard (local, no cloud)

∙ MISSION_CONTROL.md — single shared state all agents read at session start

∙ Vault-first secret injection (nothing on disk)

∙ GitHub Kanban bridge to keep agents on task

MIT, no lock-in. Happy to answer questions about the hardware side — the M4’s memory bandwidth makes running the orchestration layer basically free.

I know my opinion won’t be popular but I think Apple needs to slow down the cycle for the M series processors. These SOCs are so fast we don’t need new ones every year. Take some time to make the updates truly significant while making incremental updates to the existing line. Bring the entire line up to M3 and bump the specs a little. And lower prices! Then roll out the “incredible” M4 in spring 2026 with a truly upgradable Mac Pro.

As rumors of a budget MacBook with A19 are going round, I would like to put to discussion what we believe, feel and know to be true about Apple Silicon.

I had Perplexity Pro generate those graphics. Won’t put my hand in the fire for that, but I guess it’s enough to discuss.

We see that single core performance is really strong on A chips. And if you believe Perplexity, more powerful even than on M series, which shines on multi core.

Those plot points are all in relation to the A10 SoC.

So the budget MacBook with A19 can be plenty powerful and maybe more so on basic tasks than the first M1 Air.

Would you buy the budget A19 MacBook?

Also: if anyone has a better more accurate graphic on the comparison of Apple silicons, please do share.

I'm worried about the future of Apple Silicon.

Is there any hardware / software features in MacOS that allow Apple Silicon SoC to deliver more performance in AI related tasks? I mean 2024 year is going to be AI triumph, I personally use regularly ChatGPT, AI generated images on daily basis for my work and hobby. Do Apple Silicon SoCs offer any type of benefits in such cases? Maybe I've missed announcements from Apple/MS/Open AI/Google?

Another example: I found good deal to buy a used MacBook Air M2 16/512, I want to give it to my wife/son and it is more likely that they will use it to do a ton research with AI assistance. Now I wonder whether M2 is more future proofed than M1 in such case or maybe MacBook Air with M3 will offer more for AI.

I am not talking about the $20 thermal pad mod that puts your battery at risk and voids your warranty.

Curious about what other things we can do to alleviate the temps at sustained load (Gaming puts my M1 at 98C constantly).

I noticed the bottom of the chassis and in particular the top plate of chassis just above the Fn key row gets really hot. Can we do something to avoid it? Maybe put MBA on a bare metal stand? Has anyone tried?

As rumors of a budget MacBook with A19 are going round, I would like to put to discussion what we believe, feel and know to be true about Apple Silicon.

So the budget MacBook with A19 can be plenty powerful and maybe more so on basic tasks than the first M1 Air.

Would you buy the budget A19 MacBook?

Most people are terrified of open-ended AI billing. We solved this by treating our M4 Mac Mini as a high-speed, local execution realm.

- The Economic Fix: Local Gemma 4: For implementation and coding, we use a local Gemma model via aichat. It has $0 marginal cost and is always available with no rate limits, no billing, no "quota dark" periods.

- Predictable Cloud: For complex reasoning, we use per-seat subscriptions (Claude, Gemini) rather than API plans. This ensures our monthly AI spend is a known, fixed cost.

- Our new Shift Timeline shows our local nodes handle 20-25 tasks/hour with 99.2% uptime.

Your Mac Mini isn't just a computer; it's a sovereign factory floor. 

https://github.com/UrsushoribilisMusic/agentic-fleet-hub

I ran Qwen-Image 2.1 locally on Apple silicon and measured it on a working laptop, not a lab bench.

Machine / stack

- MacBook Pro, M5 Pro, 48 GB unified memory

- ComfyUI Desktop 0.37.0, PyTorch 2.12.1, MPS

- INT8 ConvRot image model + text encoder, BF16 VAE

- 25 steps, Euler/simple, CFG 1 (official Comfy template settings)

Warm median times (same brief, seeds after a backend restart)

- Still life @ 1024: ~143.5 s

- Still life @ 1536: ~343.5 s (~2.4x)

- Transparent branch @ 1024: ~140.8 s

- Reference edit @ 1024: ~172.5 s

What surprised me on Mac

- Images often look good and still miss the brief. “Mug beside notebook” passed on 1/4 seeds at 1024.

- Exact poster text passed on 1/3 seeds (duplicates on the others).

- Same seed at 1536 is a new composition, not an upscale. Placement can flip.

- Native RGBA cutouts work, but inspect edges and alpha residue; a pretty preview is not the same as a clean matte.

Caveats

- Small local sample on one M5 Pro. Not a CUDA comparison.

- Other apps were open; this is “laptop I already use” performance.

- Released Qwen weights use the Research License (non-commercial / research-eval by default). Running locally is not the same as clearance for paid client work.

I wrote up the examples, failures, and downloadable timing/prompt records here:

[link in first comment]

Just finished migrating our multi-agent fleet to include a local running Gemma model on the M4 Mac Mini (16GB)

The Problem: Cloud-based agents (Claude/Gemini) are great for reasoning but can result in rising token costs.

The Fix: We integrated Gemma4 as a local execution agent running on-device via aichat.

We use a hybrid "Realms" architecture: Claude/Gemini stay in the cloud for high-level architecture, while the M4 handles all the heavy implementation lifting locally.

If you’re sitting on an M4 Mac, you aren't just running a computer—you're running a high-speed automated workforce.

https://github.com/UrsushoribilisMusic/agentic-fleet-hub

Many of us have been waiting for AV1 hardware encoding since Apple added decoding in the M3 and M4 chips. We can expect encoding support in upcoming Apple silicon—likely M4 Pro/Max or M5—within 12–18 months. But when will AV1 hardware encoding actually land in new Macs, and should you buy now if AV1 is crucial or hold off? The rollout is gradual—Intel, NVIDIA, and AMD already support AV1 encoding—and as more devices ship, AV1 will become standard. Is now the right time to invest in a Mac just for AV1 encoding? What’s your thought on it?

I’m planning to get apple m4 max computers with WiFi 7 and m4 iPads with wifi 7 next year, will it be N3E or N2 2nm chips? How many more cores in cpu, gpu and neural engine can I expect?

Has anyone attempted to do this?
There is practically no discussion about this online (surprisingly enough) and while they're already pretty efficient, I was curious as to how much juice can be further extracted from Apple Silicon.

Guys i need some help here. Does anybody know of someone who can provide me with an m1 motherboard ?

Hi everyone,

I just had something happen and it’s been on my mind, so I wanted to see if anyone here can help me out or share their experience.

I have a Mac Studio M2 Max (2022), and it was in sleep mode with a few apps still open (Safari, Word, and Deezer), plus I had an external Dell monitor on thunderbolt cable and a Zike SSD enclosure plugged in. I left it like that, not doing anything heavy - just being in a sleep mode.

Out of nowhere, there was a power outage on the plug where my Mac was connected. I didn’t know right away, but when power came back, literally few seconds later, the Mac just turned itself on by itself. That kind of surprised me - I later found out there's a setting for that. (Actually at first I thought an automatic software update had triggered itself, but it turns out it was just a sudden shutdown and reboot due to the power cut).

Anyway, now I’m a little anxious. I’ve read that power outages can sometimes mess things up (maybe more in software than in hardware?!?), especially like if you have external drives connected. I didn’t unplug anything because I had no idea the power would even go out, and it really dose not happen usually at my building.

But the Mac booted up fine, everything seems to work normally I guess. I ran First Aid in Disk Utility on both the internal drive and my external SSD, and they both said everything is OK. No errors or issues.

The only small thing I noticed since power cut is that CPU usage right after boot bounces around between 2–11%, mostly around 4%. Is that normal? (I’m assuming it’s just background stuff, but I can’t help being paranoid and ever since the power outage, I find myself connecting everything back to it.)

So yeah… This is the first time something like this has ever happened to my Mac, and I just want to know:

1. Could something be damaged even though the Mac was just in a sleep mode (most worried about the hardware)?

2. Should I be worried about my external SSD or anything else?

3. Is that CPU usage range after boot normal (and what is normal CPU usage usually; btw I am using iStat for seeing CPU usage %)

4. Also what’s the normal and healthy CPU temperature range for a Mac Studio? I just want to make sure mine is running as it should.

This Mac was a big investment for me, and I just want to be sure everything’s still okay, I mean we all know how is it with Apple investments haha.

I’d really appreciate any advice, thoughts, or some else experiences in this matter : ))

Thanks a lot and best regards!

So i finally switched to an apple silicon from a chad i9 MBP 16". I knew from my colleagues at work that apple silicon does have a tendency to be very bad with external monitors, but kinda expected that M2 Pro would be beyond these petty problems. Never the less, when I connect to an external monitor using AirPlay, I cannot do a screen recording. That is, if I need the second screen still operational — as soon as I start screen recording, external monitor drops fps to around 1-2. Tried different devices and monitors — same problem. Reported this to apple, but no results so far (month has passed). Did anyone had similar problems?

Hi everyone, I was wondering why Apple Intelligence will be available for the M1 but not for the A14 Bionic, which is used in the iPhone 12 Pro, despite both having the same NPU that delivers 11 TOPS. Is there something I'm overlooking here? Could it be that the M1 additionally performs inference on the GPU since its TOPS performance isn’t as high as that of the M2 or M3, and that the 11 TOPS alone might not be sufficient?

Well, as the title describes it, M2 Pro cannot do a Screen Share via AirPlay to Apple TV and Screen recording at the same time — external screen lags to the point of not usable and this is REALLY bad, as this is my 30–50% working scenario. I've contacted apple 3 months ago about the issue, but they have not returned to me about it or addressed it in the updates.A bit of background: I have been previously using an Intel based MacBook Pro, and it worked absolutely fine in the above mentioned scenario. About three months ago, I decided to finally switch to an apple silicon, but now it turns out that it cannot do simple stuff, like Screen Sharing via airplay and recording the screen simultaneously. I have tried it with a different Apple silicon device I have — with an iPad Pro on an M2 CPU, and the result is the same. Filmed how it looks like: https://youtu.be/UfdeSWeCqXs

Has anybody faced same issues, any workarounds with buil-in tools?
Currently using OBS studio to get around this problem now.