Bora Celik

We don’t need to buy Mac Minis and become unpaid sysadmins just to run a personal AI agent. I built Mio many months before OpenClaw came out. I think it is the right architecture for personal AI. The biggest issue is memory. If AI stores our lives as markdown files, it may work for simple notes. But it breaks when we want structured long-term memory. If I ask, “How many net calories last week?”, I don’t want the AI guessing from a pile of notes. I want it hitting actual meals and exercises data tables, doing the math and returning the right number. That’s how Mio works. It has five memory layers for conversation context, recent memories, life facts, long-term learnings, and procedural skills backed by real databases. Its sleep-time processing reviews the day's conversations and distills learnings into vector memory. Under the hood, it runs on Arca, the data vault I built specifically for personal AI. Each user gets their own isolated data vault on S3 that they own - exportable and deletable. Underneath, two systems work side by side. DuckDB + Parquet files for structured data like meals, workouts, sleep, weight, todos, and anything I want to track with real SQL. LanceDB vector data files for semantic data like journals, saved articles, research notes, and memories that should be searchable by meaning, not just keywords. This is the part that excites me the most: you create apps just by talking. I can say, “Track my surf sessions. Log the spot, wave height, board, and how it felt,” and Mio creates the schema, stores the data along with a skill file that explains how to work with this data. Later, when I ask questions, it reads the skill file and knows how to correctly query the data. That’s how I’ve built mini apps inside Mio for health, meals, sleep, surfing, family logistics, Kai’s school and health notes, Luka’s training, CRM, research, reminders, travel, and my personal knowledge base. Mio has proactive actions. I tell it to do things like analyze data, send reminders, give feedback on a scheduled basis and it'll email/whatsapp/sms me. AI agents are single-player. Mio isn’t. My wife and I each have our own accounts and private vaults, but shared data like family calendar, grocery list, and our son's health/school info sync across both. Mio is available via iPhone/Mac/iMessage/Watch apps, WhatsApp, SMS, email, web and voice, without me running hardware at home. Mio has a real time voice agent using Deepgram + Cartesia + Pipecat. You can connect Mio to Claude / ChatGPT via its MCP server. It auto-ingests Apple Health data and syncs it to queryable tables. It does web research and manages your calendar. With OpenClaw and its variants, you wanted a personal AI agent, instead you got yourself a part-time sysadmin job that doesn't pay. Mio is AI that can build and run personal software with us and it's easy to use. Download Mio on the App Store, add your Anthropic API key and use it for free. Links in comments.

Sign up with Mio here: mio.fyi Download Mio on the App Store: apps.apple.com/us/app/mio-ai-… Learn about Mio's five layer memory architecture: mio.fyi/memory The private data vault Mio uses: arca.build Connect Mio to ChatGPT/Claude/n8n via the MCP: mio.fyi/mcp

We don’t need to buy Mac Minis and become unpaid sysadmins just to run a personal AI agent. I built Mio many months before OpenClaw came out. I think it is the right architecture for personal AI. The biggest issue is memory. If AI stores our lives as markdown files, it may work for simple notes. But it breaks when we want structured long-term memory. If I ask, “How many net calories last week?”, I don’t want the AI guessing from a pile of notes. I want it hitting actual meals and exercises data tables, doing the math and returning the right number. That’s how Mio works. It has five memory layers for conversation context, recent memories, life facts, long-term learnings, and procedural skills backed by real databases. Its sleep-time processing reviews the day's conversations and distills learnings into vector memory. Under the hood, it runs on Arca, the data vault I built specifically for personal AI. Each user gets their own isolated data vault on S3 that they own - exportable and deletable. Underneath, two systems work side by side. DuckDB + Parquet files for structured data like meals, workouts, sleep, weight, todos, and anything I want to track with real SQL. LanceDB vector data files for semantic data like journals, saved articles, research notes, and memories that should be searchable by meaning, not just keywords. This is the part that excites me the most: you create apps just by talking. I can say, “Track my surf sessions. Log the spot, wave height, board, and how it felt,” and Mio creates the schema, stores the data along with a skill file that explains how to work with this data. Later, when I ask questions, it reads the skill file and knows how to correctly query the data. That’s how I’ve built mini apps inside Mio for health, meals, sleep, surfing, family logistics, Kai’s school and health notes, Luka’s training, CRM, research, reminders, travel, and my personal knowledge base. Mio has proactive actions. I tell it to do things like analyze data, send reminders, give feedback on a scheduled basis and it'll email/whatsapp/sms me. AI agents are single-player. Mio isn’t. My wife and I each have our own accounts and private vaults, but shared data like family calendar, grocery list, and our son's health/school info sync across both. Mio is available via iPhone/Mac/iMessage/Watch apps, WhatsApp, SMS, email, web and voice, without me running hardware at home. Mio has a real time voice agent using Deepgram + Cartesia + Pipecat. You can connect Mio to Claude / ChatGPT via its MCP server. It auto-ingests Apple Health data and syncs it to queryable tables. It does web research and manages your calendar. With OpenClaw and its variants, you wanted a personal AI agent, instead you got yourself a part-time sysadmin job that doesn't pay. Mio is AI that can build and run personal software with us and it's easy to use. Download Mio on the App Store, add your Anthropic API key and use it for free. Links in comments.

@illscience @ekuyda but less than 10% of apps are entertainment so AI will still kill most app categories. I wrote about that here. makerswave.com/apps-no-more/

thanks ivan! high agency people tend to overestimate other people's interest in productivity - it's why agents won't kill apps @ekuyda is the one who pointed this out to me, and now I see it everywhere ....

@ivanburazin i'd heavily question that 99% number. Also what % of apps in the world are entertaining and people use them a lot. Less than 10? YT, Insta, Tiktok... The rest will fall to AI imo.

I recently heard an a16z partner on a podcast say "The average person doesn't want to save time. They want to waste time." It kinda fucked my mind. I never understood this. I don't use YouTube browse features. Don't scroll feeds. Don't go down rabbit holes. Just what do I need → get it → leave Zero tolerance for wasted time. But it seems that's not how 99% of humans work. They want to scroll through shopping sites. They want to click random videos. They want the browse interface. Text-field-only UIs won't dominate because only Sama and Elon types prioritize pure efficiency. Everyone else wants to scroll, browse, and waste their time. Entertainment disguised as productivity. All the more reason why AI won't kill traditional interfaces.

@ArtemXTech Would love to see you do a side by side comparison between QMD vs arca.build for long term memory (which uses LanceDB + DuckDB in an S3 vault)

Every influencer platform was built for humans clicking through dashboards. It's 2026 so we built one for AI agents - like Claude Code as shown in this video. Introducing gentic.co/influencer: the first ever agent-native influencer search with brand-match scoring and hyper-personalized outreach. There is no web UI. Your AI agent connects to gentic.co/influencer via MCP. A pre-defined agent skill teaches your agent the right way to run the whole campaign. You just describe what you need in plain English: "Set up my brand using our website url: [x]. Find 30 matching Instagram skincare creators in the US, 10K–80K followers, engagement above 3%, focused on ingredient breakdowns. Campaign targeting our product on this page: [x]" And your agent does the rest. - It checks your site and sets up your brand DNA and product details in a brand profile. - Then it does a vector search in Pinecone 2M+ creator profiles (and most importantly their post captions vectorized for best similarity) with verified emails to find "likely" matches" - Then runs a real-time match report by checking their profile and recent posts again (fresh data) and scores each one against your brand DNA and campaign goals. - Then it drafts hyper-personalized outreach for high match-score creators that references their actual posts, not a "we love your content" template. - Then exports everything to a CRM-ready CSV. America's beloved tea brand Harney & Sons ran this. Got 34% reply rates. Industry average is under 2%. The cost for a sample campaign workflow: → Vector search and find 100 likely-match creators: $15 → Score top 30 based on their real time posts: $10.50 → Draft hyper-personalized outreach for top 10: $3.50 → Total: $29.10 Pay only when your agent calls a tool. Go to gentic.co/influencer, grab your API key, copy/paste the docs into Claude Code / Cowork / ChatGPT and your agent will set up everything for you. Then automate the workflows with scheduled searches using @n8n_io and make it ever more powerful. Powered by gentic. Every user gets their own database in @motherduck. Your brand's data is physically separated. Literally. Let me know how it works for you.