AI for miscellaneous (non-coding) tasks

Finding some noise in an audio file with Claude Code

During a recent podcast recording that ran for over 1.5 hours, we had an incident where the automatic gain control on one of the participants’ systems ratcheted way up, amplifying some fan noise. As we pretty much record and post, I typically do not listen to the entire podcast – just spot check a few parts. I could not easily find the section with the noise to remove it, so at @khem 's suggestion, I asked Claude code to find it – it worked brilliantly:

> where in @049.mp3 is a loud fan noise?

... after some time:

● Perfect! I found sections with loud fan noise. The analysis shows sustained
  high-frequency content (characteristic of fan noise) at these locations:

  Loudest fan noise detected at:

  1. 1:27:00 (87 minutes) - Most prominent fan noise
  2. 1:01:30 (61 minutes 30 seconds)
  3. 0:59:30 (59 minutes 30 seconds)
  4. 0:41:00 (41 minutes)
  5. 1:15:30 (75 minutes 30 seconds)

It was right on!

I then asked Claude:

> can you summarize how you did this and the commands you ran?

● Here's a summary of my approach and the commands I used to detect the loud fan
   noise:

  Methodology

  1. Initial file inspection
  ls -lh 049.mp3
  ffmpeg -i 049.mp3 2>&1 | grep -E "Duration|Stream"
    - Confirmed the file exists (85MB, 91 minutes duration)
    - Verified audio format (48kHz stereo MP3)
  2. Overall audio statistics
  sox 049.mp3 -n stats 2>&1
    - Got baseline audio levels (RMS level: -22.02 dB)
  3. Segmented volume analysis
  # Analyzed every 30-second segment
  ffmpeg -ss {start} -t 30 -i 049.mp3 -af 'volumedetect' -f null - 2>&1 | grep
  'mean_volume'
    - Scanned through the entire 91-minute file in 30-second chunks
    - Identified segments with mean volume > -25 dB as "loud"
    - Found that most of the recording was consistently loud (indicating
  persistent background noise)
  4. High-frequency noise detection (the key step for fan noise)
  # Applied 1000Hz highpass filter to isolate high-frequency content
  ffmpeg -ss {start} -t 10 -i 049.mp3 -af 'highpass=f=1000,volumedetect' -f null
   - 2>&1 | grep 'mean_volume'
    - Fan noise is typically in higher frequencies
    - Applied a highpass filter (>1000Hz) to remove voice and music
    - Sections with loud volume after filtering indicate fan/mechanical noise
    - Threshold: high-frequency volume > -40 dB indicates likely fan noise

  Key Finding

  The combination of overall loudness + significant high-frequency content
  identified the fan noise locations. The loudest fan noise was at 87:00 (1 hour
   27 minutes) with high-frequency volume of -27.1 dB.
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Creating draw.io diagrams with Claude Code

I ran some experiments using Claude Code to create draw.io diagrams.

create a draw.io file “test.drawio” that has a venn diagram with three circles: Yoe, SimpleIoT, and BRun

The result:

can you adjust the circles so they overlap a little more?

Not, perfect, but it is doing what I ask it to do.

can you create a diagram for this post? 🚀 RDPD - Release Driven Product Development | Platform Thinking

The result:

This is impressive, and again illustrates why command-line tools, local files, and open file formats are the future.

I might just add a step to my newsletter workflow that creates a diagram with every post …

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A few more:

can you create a diagram for this post? 🧪 TDPD - Test Driven Product Development | Platform Thinking

can you create a diagram for this post?
📝 DDPD - Document Driven Product Development | Platform Thinking

How I use Claude Code to help publish my blog posts.

My workflow has expanded quite a bit past this, but this may be a useful reference.

Using AI for marketing

I built 19 website pages in a single day while my team was out for US thanksgiving. Not mockups. Not placeholders. Actual, shippable pages: a full partner ecosystem landing page plus individual pages for every major partner we’re building with right now. It felt surreal. Mostly because a year+ ago, there’s no universe in which I would’ve believed I could do that. And it definitely wouldn’t have happened without the engineers around me who’ve taught me how to think more like a builder—patiently walking me through GitHub (:unamused_face:), tools, workflows, and a way of working that used to feel miles outside my world.

I then asked how long it took before she stopped hating Git?

I mean it took about 5 pull requests before I finally managed to create one without an error :hot_face:… it’s been two weeks and I finally feel like the lightbulbs are going off and I’m understanding the flow (pulling things from main, branches, commits, PRs, basic commands I have on a sticky note lol, etc).

A few weeks later:

Three days. No browser tabs. No bouncing between tools.

Just Claude Code, Cursor, and Obsidian.

While our team was onsite with a customer last week, I ran a little experiment. I wanted to see if I could do meaningful work without the usual chaos.. 32 open tabs, research docs, half-remembered calls, notion notes, etc.

For context: I started using GitHub about a month ago. I’d never touched Cursor before this. I’ve only been playing with Claude Code for a couple of weeks. Obsidian just turned me into a .md girly.

So I fed in call transcripts from the last few months. Used Claude Code to actually study them… pulling direct quotes, surfacing real pain points, finding patterns across dozens of conversations.

Then I layered in outside research across three industries and started connecting dots.
What stood out wasn’t just the overlap, but the nuance. The subtle differences between what a robotics engineer worries about versus someone in computer vision. Same themes, different pressure points.

That work shaped new industry landing pages, informed another rev of our sales deck, and helped us finally build a resource center that makes sense: bridging early-stage content with deeper technical material, without dumping people straight into docs.

We’d already been iterating on our homepage for a while. But with this clarity in place, we finalized and shipped it in days.

It’s not 19 pages this time. :upside_down_face:

..But it’s a homepage, three industry landing pages, a refreshed sales deck, and a resource center with 23 pieces of content we’re proud of.

This isn’t about working longer hours or doing everything myself. It’s about how unbelievable these tools are becoming and what they unlock for small teams.

→ We can ground our messaging in actual customer language
→ We can synthesize research in hours instead of weeks
→ We can move with a kind of speed that just wasn’t realistic before

Honestly? I’m still pretty shook. If you’re curious, definitely go check out what we shipped.

I’ve recently started using Obsidian as well. Amazing tool when working with local files, Claude Code, and lots of *.md.

Hint: Even if you don’t use it for anything else, Obsidian is a decent Markdown editor … and it’s free!

Using AI for marketing continued

But here’s what I keep coming back to: this isn’t about becoming technical. It’s about staying curious.

I’m not an engineer. I’m a marketer who keeps raising her hand to try things that feel uncomfortable. The gap isn’t between technical and non-technical. It’s between those willing to feel like a beginner again… and those who aren’t.

if you see these posts and feel a mix of excitement and “I could never”, I am here to say you absolutely can.

now go deploy 48 agents to build the next super app. kidding. :yellow_heart: