2025-04-25 –, 203
Modern work demands constant context-switching—emails, notes, meetings, and tasks pile up, leaving us overwhelmed. This talk introduces a slow productivity AI approach, inspired by Cal Newport, that leverages offline, open-source automation using Hugging Face, n8n, and Obsidian. By structuring knowledge into meaningful tasks without disrupting deep work, we can create a sustainable, low-distraction workflow—working smarter, not just faster.
In his book Slow Productivity, Cal Newport argues that modern work culture prioritizes busyness over effectiveness, leading to stress, shallow work, and burnout. But what if AI could enhance deep work rather than create more digital noise?
This talk explores AI for slow productivity, leveraging open-source automation to reduce cognitive overload, structure knowledge, and enhance focus—while remaining fully private and offline.
The Problem
Knowledge workers juggle vast amounts of unstructured information:
- Scattered Notes (Obsidian, meeting transcripts, handwritten thoughts)
- Endless Emails (buried action items in Gmail/Outlook)
- Disjointed Task Lists (manual tracking in GitHub Issues, Todoist, Notion)
- Unstructured Schedules (missed follow-ups, unclear priorities)
Instead of chasing hyper-productivity, we embrace Cal Newport’s slow productivity principles:
✅ Work at a natural pace—Automate routine tasks without adding friction.
✅ Prioritize meaningful work—AI helps extract what truly matters from information chaos.
✅ Reduce distractions—A fully offline, self-hosted workflow supports deep work.
The Solution: AI-Powered, Private Slow Productivity
This talk introduces a fully offline, open-source automation pipeline for structuring knowledge and task management:
- Hugging Face Transformers (Local NLP for Meaning-Making) – Extract insights from raw notes, emails, and transcripts.
- n8n (Self-Hosted Automation) – Connect data sources, enabling automation without third-party cloud services.
- Obsidian + GitHub Issues – Convert scattered knowledge into structured tasks without disrupting deep focus.
- Google Calendar / Teams (Self-Hosted Sync) – Automate scheduling while respecting slow productivity.
Data Science Leader with extensive experience in AI and MLOps, currently serving as the CTO at Infinitii AI. He has a strong background in team leadership, product innovation, and building scalable data-driven solutions. Piotr is passionate about using AI to solve real-world problems, particularly in time-series analysis. He is an advocate for Agile methodologies and MLOps practices, and has spoken at conferences about these topics.