Most people approach AI tools the way they approach a Swiss Army knife. Pick one. Use it for everything.
That’s not a workflow. That’s a habit.
The people getting the most out of AI right now aren’t using one tool better. They’re using the right tools for the right jobs — and chaining them together in a sequence.
Here’s a workflow I use after almost every important meeting.
The Post-Meeting Thinking Problem
You just finished a call. Something important happened — a conversation that shifted your perspective, revealed a problem, confirmed a direction, or opened a new possibility.
What do you do with it?
Most people write a quick note. Some people rely on their AI notetaker summary. And then… nothing. The insight sits in a transcript file and slowly becomes invisible.
The problem isn’t capturing the meeting. It’s processing it. Understanding what it means. Connecting it to everything else you know and are working on.
That’s where I use ChatGPT — not as a note-taker, but as a thinking partner.
Step 1: Think With ChatGPT
After a significant meeting, I paste the transcript into ChatGPT. Then I give it a prompt like this:
“Here’s a conversation I just had. Here’s the context for my current strategy. Help me understand what this meeting means for where I’m headed. Ask me questions if you need to.”
ChatGPT doesn’t summarize. It engages. It connects dots. It asks follow-up questions that push me to articulate what I actually think about what happened.
This is what ChatGPT is genuinely good at: open-ended exploration and reasoning. It excels when the task is “help me think this through” rather than “do this specific thing.”
After a few exchanges, I have clarity. I know what I think about the meeting and what, if anything, needs to change in my plans.
Then I say: “Now generate a memo that I would give to my automation tool to update my master strategy document.”
ChatGPT writes the memo. Structured, specific, ready to act on.
Step 2: Act With Lindy
I give that memo to Lindy.
Lindy’s job is different. It’s not a thinking partner — it’s an executor. It’s built to take a specific instruction and carry it out with integrations to external tools. Google Docs, email, calendar, CRM.
Lindy opens my master strategy document in Google Drive and writes the updates from the memo.
That’s it. The thinking happened in ChatGPT. The execution happened in Lindy.
Why Two Tools Instead of One
When I explain this to people, the first question is usually: “Why not just use ChatGPT for everything? It can write to Google Docs too with plugins.”
It can. But the experience is different.
ChatGPT is built for conversation. It’s great when the process is exploratory — when you don’t fully know what you need yet and you want to discover it through dialogue.
Lindy is built for execution. It’s great when the instruction is specific — when you know what you want done and you need it to happen reliably across integrations.
Trying to use ChatGPT as an executor often produces inconsistent results, because it’s optimized to respond helpfully in conversation, not to run deterministic workflows. And trying to use Lindy as a thinking partner doesn’t work, because it’s built to act on clear instructions, not explore open-ended questions.
They’re not competing tools. They’re complementary. They do different jobs.
The AI Fluency Shift
There’s a level of AI fluency that goes beyond learning which prompts work.
It’s understanding that AI tools are not interchangeable. Each one has a design philosophy, a set of strengths, and a context where it performs best. Matching the tool to the phase of work — thinking, deciding, acting, communicating — is what separates people who get inconsistent results from people who have actual systems.
I’ve seen this pattern in people who are genuinely good at AI:
- They use different tools for different phases of work (thinking vs. doing)
- They’ve thought about what each tool is actually optimized for
- They chain tools in sequence rather than trying to do everything in one prompt
The conversation tool and the automation tool work better together than either does alone. That’s not a product insight — it’s a workflow design principle.
How to Try This
If you want to test this workflow, start simple:
- After your next important meeting, open ChatGPT and paste the transcript (or a summary of it)
- Tell it what you’re working on and ask it to help you understand what the meeting means for your priorities
- Have a short dialogue. Ask it to push back, identify contradictions, ask you questions.
- At the end, ask it to summarize the key updates in a memo format
- Use that memo as input for whatever automation tool you use (Lindy, Zapier, Make, even manual updates)
The goal isn’t to automate everything. It’s to stop losing the insights from important conversations.
Most of what you learn in a meeting is gone by tomorrow. This workflow is how I keep it.
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