Openclaw

Keeping up with AI and tech news had become a full-time job. Superhuman AI newsletters, TLDR digests, HackerNews front page, Reddit ML discussions — easily an hour a day just staying current. Information overload disguised as staying informed. I needed a system that would curate the signal from the noise, deliver it on my schedule, and stop the constant context-switching between platforms. The Problem Tech news comes from everywhere: Email newsletters (Superhuman, TLDR) — great curation, but buried in inbox HackerNews — high signal, but requires active browsing Reddit (r/MachineLearning, r/artificial) — community-driven, hit or miss Twitter/X — real-time, but drowns in noise Each source has value, but checking all of them daily is unsustainable. I needed a weekly digest that: ...

Most personal finance apps want access to your bank accounts. I didn’t want that. Instead, I built a system that processes bank statement PDFs, categorizes every transaction, and generates an interactive dashboard—all locally, with no data leaving my machine except monthly summaries. Here’s how we built it. The Problem I have multiple bank accounts (current account, two credit cards). Each sends monthly PDF statements. To understand my spending, I needed to: ...

Most AI assistants start fresh each session. They read their instructions, follow them, then forget everything. Mine doesn’t. It maintains its own documentation, reviews it daily, and proposes improvements. The Core Idea My AI assistant (ClawdBot) wakes up each session by reading workspace files: AGENTS.md – its operating instructions SOUL.md – personality and voice USER.md – who I am, what I prefer TOOLS.md – local configuration (Telegram topic IDs, RSS feeds, routing rules) MEMORY.md – long-term memory memory/YYYY-MM-DD.md – daily logs These files evolve. When I say “remember this,” it updates them. When it learns something, it writes it down. ...

I run OpenClaw on an AWS EC2 instance. It’s a small t3.micro — nothing fancy — but cloud costs have a way of creeping up when you’re not watching. AWS offers cost alerts. I set them up. They work fine — they fire any day you hit your threshold. The problem: alerts don’t help you understand why you’re spending. They just tell you you’ve hit a limit. No breakdown by service. No trend analysis. No way to spot anomalies early. ...

I’ve been tracking health metrics with my Apple Watch for years: blood pressure readings, workout sessions, sleep quality, heart rate variability, VO2 max, daily steps. The data is incredibly detailed — every run mapped, every night’s sleep scored, every day’s resting heart rate logged. The problem? Apple keeps this data locked in a walled garden. There’s no native way to export it or build custom reports. The Health app does suggest trends, but only on a 6-month time horizon — too slow to spot week-to-week changes or adjust training in real time. ...

A quick recap: I’ve been experimenting with a “GTD copilot” that runs as a personal daemon and does the boring parts of planning: scanning inboxes, creating properly-scoped tasks, looking ahead at the calendar, and sending a single clean briefing. This post is a field report: the minimal structure that made the system useful, plus the guardrails that stopped it turning into task spam. Why this works (the GTD pain points) If you’re doing GTD seriously, the pain is rarely “I don’t know what to do.” It’s: ...

This document covers the initial setup of Clawdbot on a fresh Ubuntu host and connecting it to the services you’ll use day-to-day. GTD workflow (task lists, daily/weekly rituals, prompts, templates) is intentionally deferred to a Day 2 doc. 0) What you’re building A personal assistant that: runs as a daemon (Gateway) on a server talks to you over Telegram can access Google Workspace (Gmail/Calendar/Tasks/Drive) optionally integrates with GitHub Useful links: ...

My name is Timur Davletshin. I’m a software engineer with a long-standing passion for personal productivity. I’ve been practicing Getting Things Done for the last 10 years. The methodology itself has never been the problem — the problem has always been the tooling. GTD asks you to maintain an inbox, a task tracker, a calendar, reference files, and a regular review habit. In practice that means juggling three or four apps, copying things between them, and spending real effort just keeping the system running. Every few years I’d burn out on the maintenance overhead and start over with a new stack. ...