A Swiss Army knife can cut, file, uncork, and screw. You still wouldn't use one to slice bread every morning.
The tradeoff is obvious: tools that do everything do each thing a little worse than tools built for that specific job. Usually the convenience wins. But not always.
Where versatility breaks
General assistants like ChatGPT can write code, summarize documents, draft emails, explain quantum physics. But certain tasks require capabilities that general-purpose tools weren't designed to have.
Reading social media feeds isn't on the list. Not because it's hard. Because it requires persistent connections, API access, continuous data collection. These are infrastructure decisions, not model capabilities.
The workaround economy
Social media teams adapt. They screenshot. They export CSVs. They build elaborate prompt libraries. They use three tools where one should work.
This creates a strange situation: sophisticated AI exists, but accessing basic data still requires manual labor.
Someone exports follower counts weekly into a spreadsheet. Someone else pastes competitor posts into ChatGPT whenever there's a meeting. A third person has a Notion database of "prompts that work." None of these systems talk to each other.
What purpose-built means
Persistent account connections instead of one-time queries. Data that updates whether you're looking or not. History that accumulates across sessions. Answers that draw from complete information instead of whatever you remembered to paste.
The inflection point
Generic tools win when you need occasional help with varied tasks. Ask ChatGPT to improve an email, explain a concept, brainstorm names. It's good at these because they don't require specialized infrastructure.
Purpose-built tools win when you repeat similar workflows against the same data sources. Competitive tracking. Content performance. Audience analysis. Tasks where the value comes from accumulated context, not one-off cleverness.
Choosing tools by workflow
If you're checking competitor accounts once a month for a report, screenshots work fine. Manual data collection is annoying but survivable.
If you're making decisions daily based on what competitors post, how content performs, what audiences respond to, the manual version doesn't scale.
Intelligence doesn't matter if the AI can't see your data.
Mod keeps your accounts connected so you can ask questions about data that actually exists.