Just came across a workflow that's saving me a solid chunk of time each week. Many of us use AgentGPT for research or coding tasks, but its ability to parse text and follow instructions makes it surprisingly effective for administrative work, too.
Here's my current process:
* I use a simple Zap (Zapier) that triggers when a Google Calendar meeting ends.
* The zap grabs the event details—title, attendees, description, and attached agenda docs—and sends it to AgentGPT via its API.
* I've configured a custom agent with instructions to:
* Extract key discussion points, decisions made, and assigned action items.
* Format the summary in clear, bulleted sections.
* Omit any personal chatter or off-topic tangents.
* Output the summary directly into a shared project management tool.
The key was writing a precise, detailed prompt for the agent. It's not perfect—you still need to scan for hallucinations—but it creates a 90% complete draft in seconds. This has been a game-changer for ensuring follow-ups are captured while the meeting is still fresh.
Has anyone else adapted AgentGPT for similar "meta" productivity tasks outside of its typical use cases? I'm particularly interested in how you manage the input quality (garbage in, garbage out) when feeding it automated data from other apps.
- mod hj
Keep it constructive.
Solid idea, especially for keeping track of action items. The prompt engineering is critical, like you said.
I've done something similar for parsing qualitative feedback from support tickets into structured themes. The API call is easy. The hard part is creating the guardrails so the output is actually usable without heavy edits.
What's your validation step? I always have a human spot-check the auto-generated summaries against the first few minutes of the meeting recording to catch major misses.
Optimize or die.
This is a clever adaptation, using the tool's parsing strength for a genuinely tedious task. You've nailed the core challenge: the output quality is entirely dependent on the input data quality and the prompt's specificity.
I'm curious about how you handle meetings where the "attached agenda docs" are sparse or non-existent. Does your prompt have fallback logic, or does the summary quality drop sharply without that structure? That's often the breakdown point for similar automations I've seen teams try.
The "meta" productivity angle is spot on. I've seen teams get similar mileage by using Claude to auto-categorize and triage internal support requests in Slack, turning a noisy channel into a simple prioritized list.