Building @headfavourhq | Digital Product Design | Brand Designer | Grateful | here to help...
Joined October 2017
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HeadFavour retweeted
This week marks 5 years since we created the FlutterBytes Community. 🎉
What started as a small, closed mentorship group has grown into one of Africa’s largest Flutter communities.
Here’s what makes me most proud. 🧵
HeadFavour retweeted
Quick update. We're rebranding and unifying our products into one brand. This is HeadFavourHQ. These are the products under the parent brand for now.
So get ready to see more of posts across the various products on this one place🚀✨
Thank you for being here as we start out.
HeadFavour retweeted
A curated reference of small design decisions that shape better interfaces.
Link : detail.design
HeadFavour retweeted
How do VCs actually underwrite seed investments? Let me explain:
At the seed stage, investors aren’t modeling cash flows, they’re modeling outcomes.
Every check is underwritten using exit math to answer one question:
Can this investment return the fund?
Here’s how the math works.
1. Start with a target outcome
VCs begin by imagining a huge exit (often a $500M to $1B outcome).
They’re not expecting every company to get there, but they need to know it’s possible.
2. Target ownership
Investors back into initial ownership based on what ownership they want at exit (taking into account dilution from future rounds).
If a fund owns 10% of a company that sells for $500M, that stake is worth $50M.
On a $100M fund, that one investment could return half the fund.
If the company hits $1B, it could return the entire fund.
3. Dilution assumptions
Ownership doesn’t stay constant.
By Series C, early investors may be diluted 30-50%.
That 10% seed stake might shrink to 5-7% at exit. The exit has to be big enough to compensate for that.
4. Portfolio construction
Most funds assume only 1-2 companies will drive total fund returns.
Every seed bet must have the potential to return the fund on its own, even if most never will.
The takeaway:
VCs use exit math to decide whether a company could be one of the few that move the needle.
That’s the underwriting lens behind every seed check.
HeadFavour retweeted
Lagos, we're coming! 🚀
FlutterBytes Conference 2026 lands at Zone Tech Park, Gbagada on Nov 6–7.
Mark your calendars, this is the one conference you don't want to miss.
Register: flutterbytesconf.com
HeadFavour retweeted
The brand identity creation process I use to replicate success:
🟠 Context first
🟠 Clarity
🟠 Field research
🟠 Visual storytelling
🟠 Design system
How I know it works:
92.9% of my 2026 brand identity projects were approved within one iteration.
HeadFavour retweeted
We have an announcement 📢
FlutterBytes Conference 2026 is happening on 6th & 7th November at Zone Tech Park, Gbagada, Lagos.
Tickets are live, grab yours now: flutterbytesconf.com
See you there! 🥳
HeadFavour retweeted
As of today, Pewbeam has been downloaded in 99 countries and used in 87. We now have paying, recurring customers in 29 countries.
In two weeks we will enter another level of growth, and I’m mind-blown by the work the team is doing.
HeadFavour retweeted
If you are a Mac user, check this
recordly.dev
Damn.
HeadFavour retweeted
With Fable 5.1 out today, we've also reset 5-hour and weekly limits for all users.
HeadFavour retweeted
YC built software that all our founders have used to send SAFEs for the last few years. Today, we're opening it up to everyone and giving it away for free.
In 2013, @cjoneslevy created the SAFE at YC. It's since been used by YC founders to raise $15B+ and has become the standard way startups raise money.
So we're launching Send a SAFE: a free tool to generate, sign, & send one in ~2 minutes, built to be used by founders (and their AI agents).
HeadFavour retweeted
Only if education could be this interactive ❤️🔥
I've had a looong wish to build something genuinely useful through vibe coding, and I finally did it.
A 3D human anatomy application built with @threejs using GPT 5.6 Sol.
It all started with a single design image that I created using GPT Image 2.0. I then used it to generate every 3D organ image, one by one.
Next, I converted each of those images into 3D models using @tripoai (and no, they didn't sponsor this 😄).
After that, I opened Codex, wrote a master prompt based on the design, and gave it the prompt, the design image, and all the 3D models.
Codex built the first version beautifully, but there was one big problem.
Every single 3D model was nearly 120-150 MB. That obviously wasn't practical for the web and was giving a performance of 16fps.
After a few iterations, Codex optimized each model down to roughly 2–5.5 MB while preserving the visual quality, reducing the total asset size from ~900 MB to just 28.6 MB. And each model loads on demand.
Along the way, Codex also generated those anatomical illustrations showing where each organ sits in the human body, and even created the interactive hotspot markers that explain different parts of every organ. It handled all of that.
The process wasn't exactly one shot, but it also wasn't difficult. You just have to do it step by step.
It genuinely felt like building something that could make learning anatomy much more engaging.
The inspiration came from @DilumSanjaya's 3D animal plant cell project. I remember seeing it and thinking, "I want to build something like this one day."
And I did it :D
Live: anatomy-livid.vercel.app/
Code: github.com/thebuggeddev/anat…
