Am I the only one who prefers coding with V4 Flash over V4 Pro? Flash is way faster and I can get more iterations in a shorter period of time, and the result is better after a few iterations with Flash than it is with one run of Pro. Also, because of the fast feedback loop, coding feels more rewarding, like driving a sports car compared to a grocery getter.

For really complex and heavy work, I'll switch to Pro. But for general coding and website building, I don't default to V4 Pro. I build with Flash first and wait until I run into a problem where I need more intelligence and reasoning.

Does anyone else do the same, or have anything to add to that?

note: running on a mac mini m4 16gb ram.

I get twenty plus emails a day. Newsletters, invoices, shipping confirmations, phishing attempts, client inquiries, server alerts. Most of it is noise. Some of it is critical. A small percentage is dangerous.

I wanted my Hermes agent to read my emails and draft replies. But I did not want Hermes to have access to everything. Specifically not 2FA codes, password resets, or banking notifications. If my agent ever got compromised, those should never be within reach.

Gmail filters check the sender, not the content. They can't tell the difference between a legitimate password notification from GitHub and a fake one from a phishing domain. And forwarding everything to a cloud AI means your password resets and 2FA codes end up in someone else's chat history. That was not an option. So everything runs locally.

The Core Idea: Two macOS Accounts

Hermes runs as a standard user. The email gatekeeper runs as an admin user. They communicate through a shared directory with read-only access. Hermes can read filtered summaries and create drafts. It can never access IMAP credentials, raw emails before filtering, or the .env file with passwords.

If Hermes ever got compromised, an attacker would find filtered summaries and the ability to search. But not the login credentials. Not the raw inbox. Not the 2FA emails. The separation is enforced by the operating system. No configuration can bypass it.

How It Works

Every 60 seconds, a Python script checks all mailboxes via IMAP. It grabs the newest unread emails. But here is the important part. It reads them with BODY.PEEK, which means they stay marked as unread in your inbox. Nothing changes on the server side.

First, every email goes through a data leak filter. Regex patterns catch passwords, IBANs, credit card numbers, and 2FA codes before anything else sees them. Those get redacted immediately.

Then the cleaned version goes to a local Ollama instance running llama3.1:8b. The model decides. Is this safe to forward? Is it spam? Is it a phishing attempt? It returns a verdict in strict JSON format.

If Ollama is down, every email gets blocked. If the model returns something unexpected, every email gets blocked. If the script crashes, a lock file prevents restarts for five minutes. Fail-closed, not fail-open. A false positive is annoying. A false negative is a data leak.

What Gets Through

Invoices, newsletters, server alerts, client inquiries, tracking updates, support tickets, appointment reminders, GitHub notifications, package deliveries. The ordinary noise of running a small business.

What Gets Blocked

Phishing attempts, password reset emails, 2FA codes, bank transfer notifications containing IBANs, emails applying pressure to act fast, requests to change email forwarding settings, logins from unknown devices. Anything that could be used against you if the system were compromised.

Supported Providers

Yahoo, Gmail, iCloud. I run all three through the same pipeline. The gatekeeper checks them in sequence, applies the same filters, sends the same verdict structure to the shared directory. Hermes never knows which mailbox an email came from. Only that it survived the filter.

What I Learned

Email gatekeeping needs to be paranoid by design. Not because someone is targeting you specifically. But because automation changes the risk profile. When you give an agent access to your inbox, the blast radius of a compromise is your entire digital life. The only way to sleep well is to architect that radius as small as possible before the agent ever sees a single email.

The two-account separation was the key insight. It costs nothing. macOS already supports it. It requires no additional infrastructure. And it is provably secure. You can test that user A genuinely cannot read files owned by user B. Everything else, the LLM judge, the regex filter, the fail-closed pipeline, is just implementation detail. The architecture is what makes it safe.

note: running on a mac mini m4 16gb ram.

Does anyone know why Mercedes chose to mark the 30-35 km/h and 50-60 km/h ranges orange? On the W210

Today I finished all my exams for my first semester of my Bachelor's and drove home on the autobahn no speed limit Mercedes W210.

I know my websites aren't AI slop. I have put in a lot of work and effort, but I still have the question: do these websites give off an AI slop vibe or a high-quality, well-built website vibe?

Also, if yes, what should I change?

Note: Please don't be respectful. Although I have built these with AI, it's not like these were spit out with one prompt. It was still a lot of effort.

I had to get rid of it — it didn't fit my lifestyle and I don't have time for it right now. But I really, really miss that bike.

I had to get rid of it — it didn't fit my lifestyle and I don't have time for it right now. But I really, really miss that bike.

Is wearing driving gloves a yay or a nay? 😉☺️

My girlfriend and I both agree that driving gloves look awesome, feel better, and are more sophisticated — they also fit our clothes.

It's not like we have to wear them, but when we're driving our cars and the gloves are nearby, we just tend to put them on. I don't know why, but I think if you put something on automatically, it's because it's more comfortable and you enjoy the experience more.

Have you tried driving gloves before?

The last picture showed the car as it was when I got it.
Now I have the short license plate as shown in the later pictures.
The thing I'm most proud of is the wood steering wheel and airbag that I got both for 400 bucks. (Super cheap in Germany - they normally sell for 1000+.) I traveled to Italy and the Netherlands with it, and I have to say road trips are a dream in this car.

The last picture showed the car as it was when I got it. Now I have the short license plate as shown in the later pictures.

The thing I'm most proud of is the wood steering wheel and airbag that I got both for 400 bucks. (Super cheap in Germany – they normally sell for 1000+.)

As the title says, this tool collects all of my receipts and analyzes them using Google Gemini Vision, then extracts vendor name, invoice number, cash amounts (brutto & netto), and category, auto-fills everything, and hosts each receipt on my own VPS under randomized, unguessable links — one for inline viewing and one for direct download.

It then pushes the full structured data plus both links into a Notion database, where I can export a clean CSV for my tax attorney. Bonus: I get a real-time spending overview without leaving Notion, because the upload form embeds right into the page as an iFrame (Basic Auth via JavaScript — no cookie headaches with Notion's third-party blocking).

I'm not worried about uploading private receipts — these are purchase receipts, not secrets. And even in the vanishingly unlikely event someone stumbles across a link, it's just a random receipt, not a security incident.

Is it the most polished or most reliable setup out there? Definitely not. But it works for me, it fits my workflow, and I genuinely enjoy using it. Curious what you think. ☺️😉

I run 28 cron jobs and 30+ custom skills. Every single one was built with Hermes, not downloaded. This is exactly what they do and how they work.

🌙 Dreaming — The Memory Hack

Every night at 3 AM while I sleep, Hermes reads every single conversation we had. It extracts the decisions made, projects worked on, bugs chased, people talked to, and mistakes that should not be repeated. Then it writes a structured summary to a file that loads automatically at the start of every session. That's the key insight — not the summarization itself, but where the output lands. Before Dreaming, if I coded for four hours and went to bed, Hermes woke up with zero memory of it. Now it knows exactly where I left off and what needs to happen next. But that's still a work in progress — memory still isn't perfect.

📬 Mail Gatekeeper — Secure Inbox Filtering

Four inboxes, one local AI judge running entirely on my Mac Mini via Ollama. Every incoming email gets classified as safe or blocked. Blocked means: 2FA codes, login confirmations, password resets, bank transactions, spam — all quarantined to a blocked folder. Safe emails land in a Telegram topic where I can see that they have been let through. There is no send endpoint anywhere in the system — Hermes can read and draft, but nothing can physically leave the machine. A watchdog reviews every blocked email each evening to catch false positives. No mail data ever touches an external API. That's the security model I'm comfortable with. This runs on two different users on my Mac Mini so they are completely disconnected — if you're curious, I've made a post about that.

🥗 Health Coach — Daily Nutrition & Recovery

Every day at noon, Hermes collects three data streams simultaneously. My WHOOP recovery score, strain, sleep quality, and HRV. My Apple Health steps and resting heart rate. And everything I've eaten so far that day logged through the food tracker — just a skill I created with Hermes. I tell him what I ate that day as precisely as possible, so with weight, and it tracks it. It cross-references all three against my lean bulk targets — 2,300 calories and 150 grams of protein — calculates my remaining macros, and delivers tailored coaching. What's looking good, what needs adjustment, and specific meal suggestions that fit my remaining budget. The food tracker itself is a SQLite app Hermes built for me. I log meals via Telegram with text, photo, or barcode scan, and it parses macros automatically using AI. There's a widget on my iPhone lock screen showing exactly how many calories and grams of protein I have left. The widget uses the iOS app Scriptable.

📚 Study Audit — What I Actually Learned

I time every study session in Toggl Track. At 9 PM, Hermes pulls all entries, groups them by subject — Math, Accounting, Cost Accounting, General Business Administration, Law, English — and tells me what I studied and for how long. But duration alone tells me nothing about coverage. So I also maintain a Notion database with chapter-level checkboxes for each class. As I study, I check things off. Hermes queries both data sources, cross-references them, and produces a combined report: what I studied, how long, which chapters I completed, and what's still pending. I get a complete daily learning audit every single night.

💰 Finance Review — Weekly & Monthly

 All my finances live in MySalary, a finance dashboard I built myself and host on my VPS. Every Sunday at 6 PM, Hermes hits the API and pulls my live income, expenses, liquid assets spread across all my accounts, and my investment portfolio. It calculates burn rate, compares against my budget split, and delivers a clean weekly snapshot. On the 28th of every month at 8 PM, I get the full treatment: profit and loss statement, month-over-month variance, net worth trajectory, and savings rate analysis. Both delivered with voice.

🧠 Wisdom Vault — Auto-Capture to Spaced Repetition

Every time I send Hermes an insightful link, a voice message with a business lesson, or a noteworthy quote, it automatically extracts the key wisdom and saves it to a Notion database with the source, my commentary, and a category tag. On Sundays, Hermes reviews the full vault, picks what's worth memorizing, and generates Anki cards with cloze deletions or question-answer format. Those cards sync to my iPhone and appear in my daily reviews. Every insight I encounter becomes a permanent spaced-repetition asset that I actually remember.

💬 Writing improvement — The Feedback Loop

Every time I correct something Hermes wrote — an email, a message, a post — the before-and-after gets saved to Notion with notes on what was wrong and why my version was better. On Saturdays, Hermes analyzes the full collection looking for patterns in my corrections. Too many filler words. Too formal for Telegram. Over-explains things. Then it updates its own system prompt to fix those patterns permanently. Every single correction makes my future writing slightly better. I never have to repeat the same feedback twice.

🖥️ Infrastructure Monitoring

Every four hours, Hermes checks whether all five of my hosted websites are reachable, whether Coolify on my VPS is running properly, and whether fail2ban has flagged anything suspicious. The Mac Mini itself gets temperature-logged throughout the day, since I run Ollama 24/7 and thermals matter. If a site goes down or temperatures hit concerning levels, I get an immediate alert. The entire Hermes configuration gets compressed and backed up to iCloud every morning automatically.

📋 Daily Status Report

Each morning at 6:30, I get a compact status briefing. Today's calendar events and what needs preparation. Open to-do items that require attention. System health — disk usage, memory pressure, uptime, VPS site status. Any anomalies from the overnight Dreaming run or error logs. This is not the news. This is the tactical dashboard telling me what needs my attention before the day starts.

⚠️ What Still Doesn't Work Great

Long-term memory is still the biggest unsolved problem. Dreaming helps, but session-to-session recall remains inconsistent. I built an Obsidian integration following the popular approach, but Hermes rarely reaches for it naturally — it sits there unused most of the time. Thirty-plus skills means thirty-plus things that can break when APIs or Hermes itself updates. Mail polling adds two minutes of latency, which occasionally misses urgent messages. I'm still iterating on all of these.

🔧 How I Build These Things

I outline the goal and my constraints. Hermes drafts an approach with API choices and architecture options. I review it, make changes, and ask for simplification. Then we build the first version. I test immediately — because it never works the first time. Then we fix and simplify again. Each skill is one file, one job, no dependencies. That's the whole process.

I've downloaded skills from repositories and marketplaces. They never worked as well as what we built ourselves. Self-built tools fit your workflow organically because they grew out of it. When they break, you understand what's wrong because you shaped them. And they get better with every iteration.

That's the full picture. Twenty-eight automated jobs running around the clock, from Dreaming at 3 AM to the study audit at 9 PM. A complete digital nervous system for my student life, business, health, and finances. 

Ask me anything about any of these — happy to share the exact prompts, approaches, and lessons learned. Building in public 💪

I highly encourage anyone to build your Hermes skills yourself. I have downloaded many skills for Hermes and openclaw and I can say most skills are way worse than those specifically for your setup and use case written — vibecoded, if you will — tools you create with your Hermes agent. I strongly encourage anyone who wants something done to try and build their own tool. It's so much fun, and if it breaks you kind of know what's wrong and you can fix it more easily, and most of the time you will learn a thing or two. So please spend the time and try to do it yourself. In my experience those tools got so good after a few iterations and feel so much more natural and organic to you, they become much more easily a part of your daily life.

here are my most interesting and most used skills. feel free to ask questions ☺️😁

LLMs are slowly starting to feel less alien. You no longer have to wrestle with them to get the result you're after. These days, they just do what they're supposed to – no fuss, no fight. One prompt: "Compare my fitness stats, nutrition data, and body composition in a chart." Boom💥, five seconds later, there's the chart. Another prompt: "Audit my VPS server status and check for security gaps." Five seconds later, I get a detailed security report.

This is beyond just tinkering. Donna – my AI assistant – genuinely feels like part of the team now. Real assignments, actual deadlines, even responsibility.