Why Building in Public Creates Better Products and How to Maintian Your Competitive Edge
This is the first in a 4-part series where I'm pulling back the curtain on exactly how I'm building Sparkry Stack—not just what I'm building, but how I'm thinking about building it. Over the series, I'll walk you through the complete evolution: from the transparency strategy (today), to the technical architecture patterns I discovered, to the content automation system I built for myself, and finally to the AI agents I'm releasing for all of you. Each article builds on the last, and by the end, you'll have the high-level playbook for building AI-powered business systems, plus early access to the tools themselves.
TL;DR: Building Sparkry Stack publicly is turning 100 subscribers into my advisory board. The framework that works:
Pick A Project
Share Strategy
Ask Questions
Engage
Your biggest risk isn't competitors stealing ideas—it's building something nobody wants in private.
Here's the strategic framework that’s turning my isolated AI project into a 100-person advisory board—and why your biggest risk isn't competitors stealing ideas, it's building something nobody wants in private.
The Transparency Flywheel and What It Means for You
Building Sparkry Stack publicly isn't feel-good transparency theater. It's a strategic framework adapted from scaling systems at Amazon and Microsoft where we took our work to the community, so to speak. We would review it with our teams, our horizontal stakeholders (internal/external customers), and to our leadership stakeholders. This was essentially community feedback with a built in audience.
Here's the three-way value exchange that makes this work for any entrepreneurs wanting to grow their feedback channels:
You: For you as the builder, you get advisory team feedback without expensive consultants. Since going transparent with Sparkry Stack, subscribers have shaped every major decision. They told me exactly what I needed to hear: "People aren't sure where to start with AI. They've heard it can help but it's confusing and overwhelming." That single insight changed my entire product strategy. I am shifting my product to be much more approachable and easier to use.
Audience: Your audience gets real-time access to proven frameworks from someone who's got your skills. In my case someone who has scaled systems to millions of users. Not theory, not AI junk content, but battle-tested approaches from your real projects. For me, that was managing billions in lending decisions and building products that rarely failed but told us that they were failing before the user even knew.
Community: This creates a community and fuels the fly-wheel effect where everyone benefits from collective intelligence. When one person solves an architecture problem publicly, 100+ others learn from it. This also self-reinforces as You engage more, your Audience engages more, your Community thrives, and that leads to bigger audiences, a bigger community, and hopefully a bigger you (whether that is a better brand for you or a more successful business where you’ve hired an entire team that is also building in public).
This isn't wishful thinking. The results speak for themselves:
Webflow built in public and reached $2B unicorn status in 2020, crediting insights from public feedback and transparency
CopyAI's Paul Yacoubian used Twitter community building to create 'this flywheel effect' where launching side projects gained followers who became customers
Buffer has maintained radical transparency around salaries, diversity, and product roadmaps for years, building exceptional customer trust
The Transparency Implementation Framework
Here's how this works practically:
Pick A Project - Start with transparency about one project. Don't overshare everything. Pick one thing and go deep. I chose Sparkry Stack's six AI agents. Everything else stays private until proven.
Share Strategy - Share the thinking, not just results. My autism lets me "feel patterns first." I document those pattern recognitions as they happen, not after they're proven. Amazon taught me how to share my strategy, planning, and updates with stakeholders. I can use that to keep you all updated.
Ask Questions - Ask specific questions, get specific feedback. "What do you think?" gets generic responses. "What challenges have you had building AI agents?" gets much more detail. This approach turned subscribers into my technical review board.
Respond & Engage - Every response gets a thoughtful reply. This isn't social media broadcasting. You’re building an organization.
# TIP - Document Everything - Your struggle today is someone else's shortcut tomorrow. The LLM Engineer's Handbook recommendation from a subscriber pointed me to the “LLM Twin” concept. I had the basic concept in my brain but, leveraging someone else’s well considered and well documented solution would ultimately net a better result. Now instead of hundreds of one off workflows repeating the same patterns over and over, I’m building a general AI processor that can take different managed prompts and score them for my LLM Twin to give me insights. Game changer, as this will make my system incredibly stable, exponentially faster to build, and can scale.
The Amazon/Microsoft Transparency Playbook
Here are some examples of this playbook in action at Amazon and Microsoft:
Microsoft Engineering Service Pipeline: We managed 300 teams with zero shared visibility. Service reliability sat at an embarrassing sub-97% uptime for many services. The fix? Radical transparency. Monthly service reviews with senior leadership backed by clear data on each service and what they were planning to get to 99.99%. Service reliability jumped to 99.99%+ in one year across all services. Shared visibility brought shared learning and permanent improvement mechanisms.
Amazon A to Z app journey: When I joined the app was at 2.8 stars. Brutal. Instead of hiding the problems, we made them visible. Added metrics for crash reasons, organized negative ratings, turned customer service reports into ranked improvement lists. Result? Got up to 4.7 stars in 6 months and it never fell below 4.7 again. Transparency builds trust faster than any marketing campaign.
Amazon Lending's regulatory transparency: When you're making billions in credit decisions, every cent must be accounted for. Bank partners needed to see everything. Full transparency wasn't optional—it was survival. That discipline made us better builders as we evolved our credit decisioning system.
Transparency Shines Light On Problems - Transparency doesn't create problems. It reveals problems so you can fix them and teaches others how to do the same.
Overcoming the Fear Factor
Let's address what actually scares you about building publicly:
"Competitors will steal my ideas!"
My response: execution > ideas. Always. If someone can beat you just by reading your blog, you don't have a business—you have a blog post. At Amazon, we published our architecture patterns in whitepapers. AWS still won because execution matters more than ideas.
"What if I fail publicly?"
The Celebrate Failure principle: Failure in the open teaches more people than success in private. Your public failure becomes someone else's private wisdom. I've made multiple mistakes building Sparkry Stack that I’ve already shared. Sharing them prevented dozens of subscribers from making the same errors. I always tried to create a culture of highlighting failures. It wasn’t always painless, but it was healthy. A key mechanism we used was the Correction of Error process where we would analyze failures deeply with the 5 Whys? to determine the true root cause of the issue and permanently solve it. The whole team would review these. Generally, the only negative feedback came when people didn’t take the transparency seriously and tried to hand wave the problems away.
"What if I give away too much?"
The real risk is building something nobody wants in private. Community building benefits always outweigh oversharing risks if you're strategic about boundaries. Your closest community are likely going to be your most active users and your most honest. The community you build is a gold mine of rich information.
“My [insert your own neurodivergent trait here] causes me to not do this!”
Ya, this one is my kryptonite. Whether it is introversion, social anxiety, rejection sensitivity, executive dysfunction, perfectionism, procrastination, whatever it is, I feel them to some degree with every post. I see the logical and personal value in building the community. I can see the paths needed to build that community. I can see all the challenges I have navigating that minefield. I’m an engineer and I solve problems. So what can I do to solve each of those challenges? I prioritize them and tackle them one by one. I want my goals more than I want my fears. I will work around my problems just like someone finding the easiest path to cross a river. AI is often my companion in this journey as I’m able to offload a lot of cognitive load that I used to take on.
I want my goals more than I want my fears.
What This Actually Looks Like
Technical validation in real-time: Instead of hiring expensive consultants, subscribers spot issues. They see my architectural decisions and call out problems before they become expensive mistakes.
Product-market fit feedback: Real users telling you what they actually need. "I love the technical depth, but can you show me how to implement this without a computer science degree?" That question changed my entire content strategy from pure technical depth to accessible implementation.
Accountability mechanisms: Public commitments create pressure to deliver. Amazon's "Bias for Action" principle works better when 100 people are watching your progress.
Cross-pollination insights: My family's BlackLine MTB apparel brand consumes time but feeds system design thinking. Subscribers see how I apply the same frameworks to physical products. The crossover insights surprise everyone.
The Compound Effect, Creating Better Products
According to my analysis of elite content marketing performance patterns, 82% of top performers focus heavily on audience understanding versus just 48% of average performers, and 31% have integrated AI into daily workflows compared to only 12% of underperforming teams.
But the real compound effect? Your community becomes your research team, focus group, and launch team simultaneously.
Sparkry Stack isn't just AI tools for solopreneurs. It's proof that building transparently creates better products, stronger communities, and more sustainable businesses.
The scary part isn't failing in public. It's succeeding in private and wondering what you could have built with 100 advisors instead of zero.
Your Implementation Strategy
Start here:
Pick one project or major decision you're making
Document your thinking process, not just outcomes
Ask your audience one specific question about a real tradeoff you're facing
Respond thoughtfully to every piece of feedback
What's the one thing you're building that you're nervous to share publicly? Reply with just the project type—no details needed yet.
Want to join our community and learn more about my journey building AI and businesses in public? Subscribe today.
For deeper technical implementation, check out The AI-First Company for frameworks on building AI-native businesses with community at the center.
P.S. If you're getting value from this series, forward it to someone who's building something interesting. The best ideas spread through trusted networks, not algorithms.