About
I kept noticing that the conversations that mattered most rarely looked urgent.
That became Sidekick Log.
I’m Hien Nguyen. Before I started Screate Labs, I ran a community-led growth agency working with clients in Vietnam, Australia, and the US. Most of my work moved through people: clients, collaborators, creators, introductions, communities, and conversations that might become something later.
That taught me something I still believe: a lot of important work does not begin as a task. It begins as a relationship.
Someone says, “I’ll connect you.” A prospect asks one good question. A collaborator goes quiet for a week. A person you met months ago suddenly becomes relevant again. None of these arrive neatly labelled important. Most of the time, you only understand what a conversation meant after the moment has passed.
Meanwhile, the inbox keeps moving. Something newer takes its place.
I eventually left agency work because I wanted to find out whether I could build products instead of spending my life helping other people build theirs. Sidekick Log started as one of those experiments.
The first small bet
Before there was much of a product, someone paid me for Sidekick Log while I was sitting in a café.
That was not product-market fit. It was just enough evidence to make me think: wait, maybe this problem exists outside my own head.
The first version was almost stupidly small. A read-only Chrome extension looked through recent Gmail conversations for signals that might deserve attention: pricing questions, urgency, meeting requests, buying intent, decision-makers, things that suggested a conversation could turn into something.
Click a signal, go back to Gmail, act.
No CRM to maintain. No new inbox. No autonomous sending. Just one bet:
Could software notice that a conversation mattered before I remembered to check it?
That was narrow enough to build. It was also wrong in useful ways.
Reality kept correcting the product
The obvious use case was follow-up: someone is waiting, you forgot, Sidekick Log catches it. But people testing normal inboxes sometimes had very few explicit commitments. What surprised them instead were old introductions, invitations, buying signals, and conversations they had forgotten were sitting there. That widened the question from “what do I owe?” to “what am I overlooking?”
Reply/no-reply turned out to be too shallow. A thread can be active and still go nowhere. “Let me check and get back to you” is a reply, but nothing actually moved. So I started modelling whose move it is, what changed, what was promised, what is still waiting, and whether the underlying decision progressed.
The harder problem became obvious: AI can generate more summaries, drafts, and recommendations than any human can consume. The scarce thing is not intelligence. It is judgment. What deserves attention? What is merely interesting? When should software interrupt you? When should it stay completely silent? That is the layer I’m trying to get unusually good at.
The bigger idea kept getting easier to describe than the smaller product was to prove. So I kept cutting back.
I removed things that made Sidekick Log look smarter without making it more useful. I worked through boring failures too: stuck scans, storage pressure, noisy classifications, account isolation, misleading empty states, privacy language, and all the little places where software can quietly lose your trust.
The test kept coming back to the same thing:
Did Sidekick Log show you something useful you would otherwise have missed?
The belief underneath it
AI is making intelligence abundant.
We can generate another draft. Another summary. Another analysis. Another plan. Another list of possibilities.
My attention does not expand at the same rate. Neither does yours.
So I’m increasingly interested in the layer between machine intelligence and human attention: the part that decides what is consequential enough to reach you at all.
That is why Sidekick Log now explores three levels of the same problem: a forgotten obligation, a latent opportunity worth resurfacing, and eventually a pattern across weak signals that you did not know to ask about.
I do not think privacy, semantic search, or “AI for email” is enough to win that problem. The longer bet is that a system can learn from what you actually act on, what moves forward, what produces an outcome, and what repeatedly turns out to matter.
The other side of the same question
Screate Labs also runs Friends of Screate Labs, with Curious Walking Club as its first ritual. That work starts from the opposite direction: create reasons for interesting people to meet, then observe what relationships, opportunities, and new nodes appear.
Sidekick Log lives on the other side of that relationship.
One brings people into the room. The other asks what deserves attention after the room is gone.
I do not know yet whether those experiments eventually converge into the same product. I am not forcing them to. But they come from the same obsession: how do we help good things between people actually happen instead of disappearing under noise?
Where it is now
Sidekick Log is still early. It is a real Chrome extension, but the thesis is not proven and the product has changed a lot. I keep the changelog public because I think the corrections are part of the work.
Right now I’m testing whether Sidekick Log can repeatedly notice something consequential in a real work inbox before the person would have noticed it themselves.
If it does, I want to know what happened next.
If it gets the judgment wrong, I want to know that even faster.
Come mess with it
If you’re curious, install it on an inbox you actually care about. Use it. Break it. Tell me what it surfaced, what it missed, and what felt completely stupid.
I share the messy version of the journey in real time on @hienverse and @screate.co.
You can also email me at hien@screate.co. I read every email. Or DM me on Instagram.
— Hien
Selected press
- ReworkedAI across communication, coordination, and execution.
- VC MagazineWhere work gets lost between email and task tools.
Through Screate Labs: Claude Startups Program ↗ · Build Club — Women in AI Accelerator 2026 ↗ · ElevenLabs Startup Grants ↗ · OpenAI for Startups Community ↗.