From Newsletter Chaos to Thematic Clarity
My N8N Experiment
The Problem: Drowning in Smart People’s Thoughts
I have a newsletter problem. Not the “I need to unsubscribe” kind, but the opposite: I’m subscribed to brilliant people sharing valuable insights, and I can’t keep up.
The emails pile up. Dharmesh Shah sending updates about his agentic AI experiments at HubSpot. Industry leaders dropping wisdom bombs about product strategy, market trends, and technical deep-dives. Each one valuable. Each one sitting unread in my inbox, mocking me.
The issue isn’t just volume, it’s the cognitive load. Reading these newsletters one-by-one means constant context switching. I’m jumping from AI agents to SaaS pricing to developer tools to marketing strategy.
My brain feels like a browser with 47 tabs open, each demanding attention.
I tried the obvious solution: summarize each email. But that still doesn’t solve the context switching problem, and more importantly, I was missing something bigger. When Dharmesh sends a couple of emails per week about his AI journey, I don’t just want bite-sized summaries. I want to step back and understand: What is he really thinking about? What themes is he exploring? Where is his attention focused?
That’s when I realized: I don’t need to see individual trees. I need to see the forest.
The Vision: NotebookLM as My Second Brain
Enter NotebookLM. If you haven’t played with it, it’s Google’s AI-powered research assistant that lets you upload documents and have deep, contextual conversations about them. I’ve fallen in love with it for exactly this use case: throw in related content, and it helps me synthesize themes and insights that span multiple sources.
The ideal workflow became crystal clear in my head:
Extract all emails from a specific sender (say, Dharmesh)
Consolidate them into a single document
Feed that into NotebookLM
Ask: “What are the recurring themes? What’s the evolution of thinking here?”
Simple, right? Except there’s no integration between Gmail and NotebookLM. Which seems like an obvious oversight, but here we are.
Why N8N? (Spoiler: I Have Jenkins PTSD)
I’ve been in DevOps for 15 years. Jenkins, CI/CD pipelines, automation workflows—it’s been my lifeline. When I see a repetitive manual process, something in my brain just screams “AUTOMATE THIS.”
Recently, I’ve been exploring the agentic AI tools landscape, and N8N kept coming up. YouTube tutorials, blog posts, Twitter threads—everyone seemed to be building with it. The pitch was compelling: a visual workflow builder with integrations to everything. Gmail, Google Docs, Sheets, Slack, you name it.
I thought: “N8N is a workflow processor with plug-and-play integrations. Building this pipeline should be very easy.”
So I dove in.
The Honeymoon Phase: First Impressions
I’ll give N8N credit: the first impression was genuinely impressive.
I’m using N8N Cloud, and the low-code visual editor felt intuitive. Dragging nodes, connecting them with lines, searching for integrations—as long as you have the data model in your head, it’s straightforward. Certainly less work than configuring Jenkins pipelines or wrestling with YAML files.
The node library is extensive. Gmail? Check. Google Docs? Check. Data transformations? Check. It felt like Lego blocks for workflows. Snap pieces together, configure a few settings, hit execute, and watch the magic happen.
Unfortunately, that initial impression was the peak. It was a gradual downhill from there.
The Build: Two Iterations and Many Lessons
Let me walk you through what I actually built.
Iteration 1: The HTML Export Dream
My first workflow looked like this:
Form submission trigger → Get many messages → Edit Fields → Get a message → Edit Fields → Convert to File
The idea: trigger the workflow with an email address, fetch all their emails, extract the content, convert it to HTML, and dump it somewhere I could grab for NotebookLM.
Here’s where I hit my first gotcha: “Get many messages” is a misnomer. It doesn’t actually get you many messages with full content. It gives you a table of message metadata—IDs, snippets, basic info—but not the actual email bodies. This is presumably to prevent you from downloading gigabytes of data accidentally, but the naming is misleading.
So I had to add another node: “Get a message.” This takes each message ID from the first step and fetches the full content. The good news? N8N is smart enough to automatically iterate over the table, so I didn’t need to explicitly create a loop. That was actually slick.
Then came the “Edit Fields” nodes. Why two of them? Because the Gmail API returns everything: headers, labels, thread IDs, metadata soup. I had to explicitly extract just what I wanted: subject, date, and the actual email text.
I tried converting this to HTML and using Postbin (which N8N recommends for testing) to dump the output. Then I’d copy-paste into NotebookLM. It worked... but felt clunky.
Iteration 2: The Google Docs Integration
The second iteration was cleaner:
Form submission trigger → Create a document → Get many messages → Get a message → Edit Fields → Update a document
Instead of exporting files, I’d create a Google Doc on the fly and append each email to it. Then I could just share the Google Docs link directly with NotebookLM as a source. Much more elegant.
This worked! Sort of. The output was a chronological dump of emails—no fancy formatting, no headers, just raw content. I’d tried to use Markdown in an earlier attempt, but it didn’t work as expected for reasons I’ve honestly forgotten.
But the core loop was functional: fetch emails, filter out noise, write to Google Doc, link to NotebookLM.
The Frustrations: Death by a Thousand Paper Cuts
Here’s where we need to talk about the things that drove me slowly insane.
The Auto-Save Betrayal
The most frustrating moment—and there were many—was discovering that my entire Day 1 workflow had disappeared because N8N doesn’t auto-save by default.
I could see the execution history. The logs showed my workflow had run successfully. I could see the outputs, the data transformations, everything. But the workflow itself? Gone. Because I’d closed the tab without manually hitting the save button.
This happened. Multiple times. My bad!
For someone coming from modern dev tools where auto-save is table stakes, this felt like using software from 2005. And yes, you can argue “user error,” but when the platform shows you execution history proving your workflow existed and worked, not saving it feels like a betrayal.
The 75% Problem
This became my mental model for N8N: it gets you 75% of the way there, then leaves you stranded.
Example: I wanted to use Google Sheets instead of Google Docs initially. N8N has a Google Sheets integration. Great! You can create a sheet, write data to it, update cells—all the things you’d expect.
But here’s the gotcha: to dynamically update columns in Google Sheets, N8N requires you to explicitly define headers. Makes sense. Except when you dynamically create the sheet through the workflow, there’s no easy way to add those headers. You’re stuck in a catch-22: can’t update without headers, can’t create headers programmatically.
I also wanted to move the created sheet into a specific folder. That had its own set of gotchas. What should have been a simple “create → organize → populate” flow turned into an afternoon of wrestling with the API.
Variables, If-Then-Else, and Pro Plans
I wanted to store some values across nodes—basic variable management. Turns out N8N does have variables, but they’re global. Coming from a programming background, this was shocking. Global state is generally considered an anti-pattern, yet here it was as the default (and on the free tier, it is not an available) option.
Want proper variable scoping? That’s a pro plan feature.
I also wanted basic if-then-else logic. N8N has conditional nodes, but they felt clunkier than they should be. For someone who thinks in code, I kept wanting to just write:
javascript
if (emailCount > 10) {
// do this
} else {
// do that
}Instead, I’m dragging nodes and configuring dropdown menus.
The Documentation Dance
The documentation is extensive, but I found myself constantly Googling for examples because the official docs would explain the what but bare minimum.
The Verdict: Is N8N Worth It?
After nearly two days of work spread across a couple of sessions, I have a working workflow. And I need to be fair: it does work.
I can trigger it, give it an email address, and out comes a Google Doc with all their messages consolidated. I link that to NotebookLM, and suddenly I can ask those high-level thematic questions. “What are Dharmesh’s main focus areas this quarter?” “How has his thinking on AI agents evolved?” It delivers exactly the forest-level view I was looking for.
But would I recommend N8N? The jury is still out.
Who It’s Good For
I think N8N optimizes for a specific user: someone who wants to prototype workflows quickly, who doesn’t have a programming background, and who needs to connect common SaaS tools without writing code. For that person, the visual interface and extensive integration library are genuinely valuable. I don’t quite know what happens when they run into the issues that I outlined.
It’s excellent for mocking up ideas. “Let me see if this flow makes sense” can happen in minutes. That’s powerful.
Who Should Look Elsewhere
If you’re a programmer who thinks in code, loops, and proper variable scope? N8N might frustrate you. The visual editor that’s supposed to make things “easier” actually adds friction. You’re constantly translating your mental model (”I just need a for loop and a conditional”) into drag-and-drop nodes.
If you need production-grade reliability and you’re planning to hand off your workflow to someone else? I’m not convinced N8N is there yet and to be fair, I haven’t tried the enterprise plan. The auto-save issues, the “last mile” gaps in integrations, and the need for workarounds make me hesitant to treat it as mission-critical infrastructure.
My Next Steps
I’m giving N8N a fair shake. I’ll try one or two more workflows before making a final judgment. But I’m also exploring other agentic workflow tools to see if there’s something that offers more programmatic access—essentially, a tool that doesn’t hide the code but rather enhances it.
If I were starting this project over today? I’d probably reach for a tool with a code-first approach rather than a visual editor. Sometimes writing Python or JavaScript is the faster path, especially when you already think in those patterns.
The Bigger Picture: Information Needs Better Tools
Here’s what I keep coming back to: the newsletter problem is real, and it needs solving.
We’re inundated with information. Smart people are sharing valuable insights across dozens of platforms and formats. But our tools for sense-making haven’t kept up. We’re still treating emails as individual items rather than as threads in a larger narrative.
The workflow I built—as janky as parts of it are—actually addresses a genuine need. Being able to go from “trees” (individual emails) to “forest” (thematic understanding) is valuable. NotebookLM as the final piece is what makes it sing, turning raw text into conversational insights.
This experiment taught me that the gaps between our tools are often where the most interesting opportunities live. Gmail doesn’t talk to NotebookLM. NotebookLM doesn’t have email integration. So we build bridges.
Closing Thoughts
Would I use N8N again? Maybe. Would I recommend it to a friend? Depends on the friend.
But here’s what I would say: if you’re drowning in newsletters from people whose thinking you value, consider building some kind of consolidation workflow. Whether it’s N8N, Zapier, a Python script, or even a manual process of copy-pasting into a doc once a month—find a way to step back and see the patterns.
The insights are there. You just need to zoom out far enough to see them.
What do you think? Have you built something similar? Are you also drowning in newsletters? Drop a comment or reach out—I’d love to hear about your approaches to this problem.
And if you want the technical deep-dive on the actual workflow structure and data models, let me know. That might be a separate post for the nerds (affectionate) who want to build something similar.