The Value Case for Writing
A Researcher's perspective on why writing is important
I’ve stared at this blank page more times than I’d like to admit over the past year. Every time, I’d have an idea, start writing, then save or delete everything and close the tab. On loop again. I wanted every piece to be good enough to put out there, deeply researched and I wanted the audience to engage with it. However I knew that I lacked the time to meet these standards consistently.
So I stopped writing for The Platform Space altogether.
But here’s the thing I’ve realised after I stopped contributing to this space here: I love writing - it’s continuous learning, it gave me a connection with this community, and the clarity that comes from putting thoughts into words.
This article is about rebuilding my case for writing, not as a content creator or thought leader (As a non-english native I actually really dislike this word), but as someone who learns by doing and thinks by writing. I want to start building platform products in the open again.
Past
When I paused The Platform Space, I thought I was being pragmatic. Between a full-time Lead IC role, ongoing PhD research, and becoming a mom, something had to give. Writing felt like the obvious choice - it was the add-on, not the core. But it was the thing I loved the most. For the past 5 years I wrote every day - either wiriting at work, writing for this newsletter or writing my thesis, it was something that become second nature almost.
In 2024 I stopped writing on here and it felt like I was given up part my job to some extent - I really didn’t needed the validation of subscriber counts or engagement metrics, but the actual process of:
Battling with half-formed ideas until they became coherent
Connecting dots between building platform products, my behavioural science academic research, and industry trends - AI became a thing
Getting feedback from readers that challenged my thinking
Having a public record of how my views evolved over time - this is still probably the best thing
Without writing, I was still learning, but I wasn’t synthesising. I wasn’t presenting back and I wasn’t able to critique some of my own work. As with research, writing made me better at building products.
Present
I’ve spent enough time thinking about product positioning to know that when something isn’t working, you need to revisit your value proposition. So I want to do that for my writing.
What I thought writing was for:
Building an audience
Establishing expertise
Creating comprehensive resources for others
What writing actually brings me:
Clarifies my thinking on complex topics
Creates accountability for continuous learning
Builds a network of people solving similar problems
Documents my evolution as a practitioner and researcher
Forces me to question my assumptions
Forces me to THINK
The shift here is subtle but important. The first list is focused on output and perception. These are your vanity metrics as a Substack contributor. The second is focused on process and growth. Both have value, but the second set is sustainable because it serves me regardless of external validation.
Future
One of the things that really stopped me writing in public was all the AI generated soup of content . The temptation to use AI to “do the writing for me” is really big but it can’t ever replace the process of putting down thoughts in a coherent way - and this is personal for me.
LLMs are brilliant for certain tasks. I use them regularly for:
Structuring initial frameworks
Research content
Reformatting content + checking grammar
Generating different angles on a problem
Generate different styles
But they have a fundamental limitation: they go in loops and they get stuck in the doom of context. They keep saying the same things in different ways. They can help you framework your thinking, but they can’t do the thinking for you. Not yet at least!
When I write, I discover what I actually believe about something - it gives me conviction. The act of trying to explain a concept forces me to face into what’s the best way to communicate something to both technical and non-technical audiences. For example, I might start writing about platform product metrics thinking I have a clear position, only to realise halfway through that my framework has a massive blind spot.
An LLM can’t do that. It can repackage what you already know (or what exists in its training data), but it can’t generate the insights that come from wrestling with your own experience and synthesising it in a way that’s impactful.
For Product Managers specifically, this matters even more. Our job is to develop good opinions about what to build and why. It’s about developing conviction on what’s the best problem to solve. If we outsource the writing to an LLM, we’re essentially outsourcing the core skill of our thinking: making sense of complexity and forming a point of view.
Write because it gives you clarity. Write because it helps you frame the problem. Write because it will make you a better communicator. Write because it helps you think!
That’s what my plan is now in re-launching The Platform Space. To go back to writing. So for those of you who’ve stuck around (thank you, genuinely) but also to those of you that are new, here’s what to expect.
Building Platform Products (incl. Infra for AI/ML)
Practical frameworks for discovery, delivery, and value measure
Deep dives on specific platform capabilities (documentation, deployment pipelines, observability, experimentation etc)
Interviews with other Platform PMs and Engineering Leaders
Case studies and patterns I’m seeing across organisations
Behavioural Science Meets Product:
How behavioural economics influences developer tool adoption
Research findings and their practical applications
Book reviews and academic paper breakdowns
The Messy Middle:
What I’m currently struggling with
Experiments in progress
Honest reflections on what’s working and what isn’t
Why This Matters (Beyond My Personal Journey)
Platform work is inherently complex and context-dependent. There are no universal solutions, no one size fits all and there’s at least 3 really big cloud providers who will tell you what’s the best way to build a platform product. I want to support you to navigate this complexity through shared learning and dialogue.
That’s what I hope The Platform Space can be - not a one-way broadcast of expertise, but a conversation about what we’re all figuring out together.
So here’s what I’m committing to:
Publishing at least once or twice a week
Engaging with comments and feedback - I think there’s a way to intro chat as well
Evolving my thinking based on conversations with this community
Documenting both successes and failures
In return, I hope you’ll:
Share your own experiences in the comments
Challenge my thinking when you disagree
Suggest topics you’d like to see covered
What’s Next
The next article will be about what I’ve learned in the past year as an AI/ML Platform PM - I’m diving into how to start from scratch and what the hype is all about.
After that, I’m planning a piece on the intersection of DORA metrics and behavioural nudges. How do we measure the right things without creating unwanted incentives?
One more thing: I’d love to hear from you. What are you currently working on? What challenges are you facing in platform work? What topics would you like to see covered? Feel free to reply or leave a comment - your input will directly shape what I write about.
One more thing
I initially titled this article “Why I’m Starting to Write Again,” but that felt too focused on me and too LLM’esque. The truth is, I’m writing again because I believe in the value of learning in public, building in the open, and growing through dialogue.
The Platform Space started about helping a small community of PMs working in this space - it was always about enabling others. Sometimes the best way to do that is by sharing not just what you know, but how you’re figuring things out.
Thanks for being here. I’m glad to be back.
See you next week!