Wispr Flow + Claude Transforms Content Creation
I kept hitting the same frustration every time I wanted to write about a technical project. I’d have this complex implementation in my head – all the edge cases, the gotchas, the lessons learned – but getting it from brain to readable article felt like translating between languages.
So I’d procrastinate, jot down a few bullet points, then let the idea sit for weeks.
The process was brutally slow – building content over weeks, adding bits here and there, tweaking and tailoring incrementally. It was subconscious-led rather than stream-of-thought-led.
Then I discovered Wispr Flow + Claude, and everything changed.
The Numbers Don’t Lie
Here’s the baseline math: Average typing speed is 40 words per minute. Average speaking speed is 125-150 words per minute. That’s a 3-4x speed increase just on raw output.
But the real multiplier is even higher because of the cognitive load difference. When you’re typing, you’re constantly self-editing and hesitating. When you’re speaking, you can just flow.
But this isn’t really about typing versus talking. It’s about completely changing how we approach technical content creation.
The Breakthrough Moment
My aha moment came when I was using Wispr Flow with Claude for coding. I found myself speaking to the terminal, getting functionality specs out of my head, talking through features and edge cases (I wrote about this here, if you are interested: Turning Claude Code into a Development Powerhouse).
I could think out loud and flow with ideas. It was far quicker to get information out of my head than typing ever was.
What this meant was I could build comprehensive functionality specs for code just by talking – before I even touched the keyboard. The only keys I touched were Ctrl+Windows (to trigger Wispr).
It hit me that this was a natural fit. Since I’m already living in Markdown files and writing mostly about development work – how I solved problems, why certain tools work well – the same approach should work for article creation.
This Isn’t Actually New (But It’s Better)
Photo from National Museum of American History
Let’s be honest here – people have been recording their thoughts since the 1860s with the Phonautograph. And then the Dictaphone came along. The only difference was other humans would then write up dictations. That cognitive load, that time taken to write things down, was just passed on to another human.
We got decent speech-to-text in the 1990s/2000s. But AI allows for far more increased speed and there’s less human requirement. I don’t need to hire someone to write down my ramblings. It can go straight to screen and then can use AI to tidy it up.
What has changed the game for me is the combination: immediate voice capture + intelligent clean-up and organization.
The Writing Problem
You know this pain: you understand a concept deeply, but getting it out of your head and into a shape that another human can follow can be tricky. The blank page problem is real. You know what you want to say but organizing it feels impossible.
This is where the voice-first approach shines. You can just start talking about the problem you’re trying to solve. Go around the houses a little bit. Mention edge cases as they occur to you. The AI will help sort it out later. A far smoother approach to AI copywriting.
My Current Workflow
Here’s exactly how I do this now:
1. Minimal mental prep: Just thinking “Is this a subject I want to cover? Can it be helpful?” I don’t fully plan out the article anymore.
2. Voice dump: I spit ball the idea to Claude (via Wispr Flow) and monologue about what I want to talk about. I go around the houses, mention tangents, explore different angles.
3. AI interview: Here’s the key – I ask Claude to interview me. “Here’s the initial thing we’re trying to discuss, can you help me dig in?” Claude returns 3-4 questions that I can see on screen and work through systematically.
4. Iterative exploration: I can direct the questions or say “I’ve had a thought, let’s talk about this angle.” We dig deep and go heavy, knowing we can pull it back once we’ve got all the context out.
5. Technical additions: Once I’ve got all the conversation down, I manually add any code examples, snippets, or links. I want to make sure the code is correct – you can’t just ask AI to generate technical examples and trust them blindly.
6. AI clean-up with oversight: I ask Claude to summarize, but then I take both the original context and the summary and run through a few iterations: “Is there anything we’ve missed? Is there anything that could enhance this direction?”
Human refinement: I come back days or weeks later with fresh eyes and tweak for flow, personality, and accuracy.
Why The Interview Format Works
Having Claude interview you breaks down content blocks that you might get, especially first thing in the morning when you need a prompt to get moving. You start with a generalized outline, then as questions come: “Oh, well what about this? Well, no that’s not what I want. What about this? Yeah, that’s the right direction.”
The ability to keep being poked along – “What are your thoughts on this? What about that?” – really maintains flow. You probably could get there solo, but it would take much more time.
In conversation, you can flip-flop back and forth, whereas when I write, it tends to be very structured, one trail of thought. Talking allows far more natural self-critique and counter-arguments in a fluid way. If there’s an additional thought tied to the last thought, you can briefly touch on it, then come back to the first thought. By getting it out of your brain and into Claude, you haven’t lost it.
The AI Clean-up Balance
Here’s the critical warning: if you use Claude too much, if you take all your context and meandering thoughts and ask Claude to just summarize everything, Claude can be very aggressive with how it reduces that information. You can end up with a very lobotomized article that could otherwise be far more human.
What I do is ask for summaries, but then cross-reference with the original context. “Is there anything we’ve missed? Is there anything that could enhance this direction?” But you need to drive it – if you let Claude drive completely, you lose your personality and style.
Everyone has their own way of telling stories, their own pauses, their own mannerisms. If you’re too Claude-ified, it will remove your personality, and readers can tell the difference between a good writer working with AI and a fully AI piece of content.
Content Type Considerations
This approach works brilliantly for technical documentation, development articles, and explanatory content. As long as you can get everything out of your head initially, it’s not necessarily limited by content type.
Where you need to hold back on AI involvement is when you start shaping that raw material into something specific. For creative writing like stories, this wouldn’t work well. But for technical documentation – especially dry documentation about processes – having an AI-driven clean-up process might actually be beneficial because you’re dealing with if-statements and cause-and-effect rather than emotions and emotional conversation.
Quality Control for Technical Content
When you’re explaining complex technical concepts, developers can’t afford inaccuracies in their documentation. Here’s my quality control process:
- Human verification: You still need to read everything back and tweak it. Mistakes happen even in human writing – your first draft needs editing regardless of how you created it.
- Manual code verification: Add code snippets and examples manually after the AI clean-up. If you’re explaining how to do something with code, you need to ensure what you’re sharing is 100% correct and verified by yourself.
- Responsible writing balance: There’s a clear line between what AI can do (organize thoughts, improve flow) and what you should do (verify technical accuracy, maintain authenticity).
Getting Started: The Minimum Viable Experiment
If you are sceptical about adding AI to your writing workflow, here’s a small experiment you can run:
- Install Wispr Flow (free plan available) – wisprflow.ai
- Open Claude (free plan available) – claude.ai
- Try this prompt: “I want to write a technical article about [TOPIC]. Can you interview me to help me explore all the angles and get my thoughts organized? Start with broad questions about the problem I’m solving, then dig into implementation details and lessons learned.”
- Just start talking into Wispr about your topic for 5-10 minutes
- Let Claude interview you based on what you said
- See what happens
You could even start by just typing your article title into Claude and asking for an interview. It’s a good jump-off point that requires zero additional tools.
The Meta-Validation
This entire article was created using exactly this process. I started with a rough idea about wanting to write about Wispr Flow + Claude. I talked through my thoughts, Claude interviewed me about different angles, and we built up layers through conversation.
You can see the process working in real-time: I discovered connections as I spoke (like connecting tangential speech to better self-critique), ideas got more sophisticated with each response, and we built enough raw material for a substantial article just through conversational exploration.
We literally demonstrated the “getting more context out upfront” principle while creating content about that exact principle. This is how to use AI for copywriting IMO.
The Real Game Changer
This isn’t just about speed, though the 3-4x output increase is significant. It’s about changing how you think about technical writing from a painful, time-consuming process to something that flows naturally from your existing knowledge.
Instead of staring at a blank page wondering how to structure complex ideas, you can just start talking about the problem you solved. The structure emerges from the conversation. The AI helps with organization and clean-up, but the insights, the personality, the technical accuracy – that’s still all you.
The cognitive load of writing is distributed across the right tools: your brain for insights and technical knowledge, your voice for natural expression, AI for organization, and your editing skills for final refinement and accuracy.
It’s not about replacing human creativity or expertise. It’s about removing friction from the process of sharing that expertise with others.
