OpenClaw workflow automates meeting follow-ups, replaces Granola for user

Meeting automation workflow using OpenClaw
A user has documented their transition from Granola to OpenClaw for meeting management. While Granola provided meeting notes for $14/month, the user found it insufficient for handling post-meeting tasks.
The core issue was managing what happens after meetings: following up with the right people, sending recaps, tracking commitments, and monitoring next steps across multiple clients. These tasks were consistently falling through the cracks.
OpenClaw workflow specifics
The user configured an OpenClaw workflow with these capabilities:
- Listens to meetings via speech-to-text (STT)
- Transcribes meeting content
- Generates a clean summary on WhatsApp by the time the call ends
- Breaks out action items clearly
- Creates a draft follow-up email ready for sending
The key difference noted is that OpenClaw doesn't just record what happened—it acts on the information. While Granola provides notes, OpenClaw provides notes plus automated next steps.
The user reports this approach is particularly valuable for those juggling multiple clients or back-to-back calls, as it changes how their day runs. They cancelled their Granola subscription the same week they implemented the OpenClaw workflow.
📖 Read the full source: r/openclaw
👀 See Also

Building a Voice Assistant with OpenClaw, Alexa, and Local LLM
A developer built a voice-first assistant using OpenClaw as the AI agent backbone, Alexa for voice input, and a local LLM (Ollama with Qwen 2.5 3B) to handle general knowledge queries with sub-second response times and reduced API costs.

Operational Memory Over Automation: Why Small Business Agents Need to Remember
The real value for small business AI agents isn't automation — it's operational memory. A white paper from McPhersonAI argues agents should behave like disciplined operators: remember standards, notice drift, preserve context, and surface what matters.

Designer builds native Mac photo tagging app with Claude Code and local vision model
A designer with no Xcode experience used Claude Code to build Loupe, a SwiftUI Mac app that analyzes photos with a local vision model (minicpm-v via Ollama) and writes IPTC/XMP metadata. The app includes parallel processing, hardware auto-detection, and a learning system that adapts to tagging style.

OpenClaw News Assistant: $100 Burned on Sports + Tech Dedupe & Hallucination Fixes
A developer spent ~$100 building a personal news assistant with OpenClaw for sports and tech/AI news. Key issues: hallucination (rumors treated as fact, merged incorrect stories), deduplication across 10+ sources, freshness vs resurfacing old stories, and token cost. Stricter prompts, caching, dedupe, ranking, verification, and diff logic improved results but cost became prohibitive.