Most startup advice sounds good until you actually start building
One thing I’m realizing while building VIDI:
A lot of startup advice only makes sense under stable conditions.
Early-stage building usually isn’t stable at all.
You’re making decisions with:
incomplete information,
limited resources,
unclear demand,
and constantly changing assumptions.
Which means a lot of the game becomes:
observing behavior,
adjusting quickly,
and learning faster than your previous assumptions break.
What surprised me most over the last 11 weeks is how often user behavior changes the direction of the product more than the original idea itself.
Not because the original vision was “wrong.”
But because reality is usually more nuanced than the theory you start with.
Still early.
Still learning every week.
Curious how many other founders experienced a major shift between:
what they thought they were building
vs how people actually ended up using it.
The specific place this breaks down in data work: founders set up their analytics stack based on assumptions about what to measure, and those assumptions reflect the product they thought they were building — not the one user behavior keeps telling them to build.
So you end up with dashboards full of metrics chosen in month 1, measuring an old version of the product. And maintaining those metrics has a real cost: it anchors your thinking to the original thesis even when the data is quietly signaling something completely different.
What I've seen work better at early stage is 'minimum viable metrics' — track only what you're actively making a decision with this week. If you're not changing behavior based on a metric, you don't need it yet. Add complexity to your data model as you understand your product, not in anticipation of what you might someday want to know.
The 'user behavior changes the product more than the original idea' point is exactly right. It implies your product/data feedback loop needs to run faster than most early teams have it set up. The bottleneck is usually not what you're building — it's how quickly you can see and interpret what users are actually doing with it.
For early-stage founders starting to instrument their product and query that behavioral data without a full BI stack, my free SQL diagnostic scripts are a solid lightweight starting point: https://growthwithshehroz.gumroad.com/l/psmqnx
The gap between 'advice' and 'execution' is brutal. One pattern I've noticed: the friction isn't usually the product idea - it's the micro-tools that don't exist yet.
Example: I use voice dictation (Wispr Flow / Superwhisper) for most of my writing, and the biggest friction point isn't transcription quality - it's context-switching between different writing modes. Dictating a formal email sounds nothing like dictating technical docs.
Built custom AI prompts to handle this (different 'voice profiles' for each context) and it halved my cleanup time. Now I'm wondering if others have the same pain.
Curious: does anyone else use voice dictation for serious writing? Have you solved the context-switching problem, or is it something you just live with?
Haven’t checked in for a few weeks - a lot has changed already. Cool to see how fast everything is evolving.
Appreciate that - honestly the last few weeks have probably been the fastest learning period I’ve had so far while building this.
Very true — users usually shape the product more than the original idea does.
Yeah, honestly that’s probably been one of the biggest lessons for me so far while building this.
so
ok
If anyone’s curious what I’ve been building while going through this process:
https://vidicontract.tech/