I have built plenty of amazing products, some of which are public on my GitHub (https://github.com/afrotechboss). But I always find it difficult to scale from there. I enjoy the building process, sometimes I even onboard a couple of first users, they love it, but after a while it dies off. I feel like I have a lot to learn. Any advice?
Started sharing weekly updates for my app and it was fun at first but soon i realized i was tweaking features just to make them look cool on social media.
Spent hours making things flashy for a quick post instead of building stuff users actually needed.
Once i stopped posting so much, development went way faster and stress dropped.
Anyone else feel like sharing updates daily turns into a huge distraction after a while?
We ran a checkout optimization test over 5 weeks with 11,200 sessions. The original form had 9 fields. We hypothesized that fewer fields would mean less friction.
Control (9 fields): 68.4% completion Variant (5 fields): 59.1% completion
We lost 9 points by removing fields. The removed fields were: company size, role, use case, and referral source. When we interviewed abandoners, the pattern was clear. Those four fields had been doing qualification work. Users who filled them felt the product was being configured for them. Without them, the checkout felt generic, and the commitment felt arbitrary.
We restored all four, moved them to a second step with a progress indicator, and completion rose to 74.2% higher than either version.
Anytime we want to see technological advancements, we either keep an eye on Product Hunt, Techcrunch or the military. And that's today's case.
In the morning, I read this announcement:
Meta is partnering with defense tech company Anduril to develop AR/VR headsets for the U.S. military, starting with a new device called EagleEye. The new headset will include night vision, thermal sensing, and augmented reality features. The partnership has raised eyebrows due to Meta s role in data and AI, and the ethical implications of a social media giant entering the military tech space.
Both big AI labs quietly switched on watermarking this month Anthropic marks every text Claude touches, OpenAI marks GPT-Live voice audio (EU AI Act, Article 50).
The catch: a detected mark means the model processed the text, not that it wrote it. Fixing grammar leaves the same mark as full generation. And no mark proves nothing either edits, translation or transcription wash it out.
When I started I had a pretty clear idea of what I wanted to build and what I didn t want to compromise on. Then customers deadlines revenue and random problems started piling up. Some of the things I said I d never do slowly became things I had to consider just to keep moving. At what point is changing your priorities a sign of growth and when does it mean you re drifting too far from what you originally wanted to build?
We tracked feature adoption across 6 months. The fastest-growing "feature" was a keyboard shortcut that was not in our docs, not in our onboarding, and not in our release notes. It had been added by an engineer as a personal convenience and shipped without announcement.
Weekly users after 6 months: 3,100. Our documented shortcut with the highest adoption: 900.
Users had found it through a forum post, a tweet, and word of mouth. When we interviewed them, they said they assumed it was intentional because it worked so well. We had been documenting the shortcuts we wanted people to use, and the one they wanted was invisible.
We added it to the docs and the in-product shortcut panel. Adoption rose to 5,400 weekly, and it became the second-most-used shortcut in the product.
We recently fell into the trap of prioritizing features simply because they were easy to measure. Our charts were showing great engagement so we thought we nailed the solution.
It was eye-opening to jump on user calls and realize we hadn't solved their primary issue at all. Data tells you where people click but it completely misses the friction they feel right before that.
