Concept first and evidence next.
→ Concept → Evidence → Refine → Proof → Scale/Iterate
Speed is a science. Iteration without instrumentation is theater.
Even at concept stage, we define the telemetry: what to measure, where signal should appear, and when to kill or double down. Learning rate beats raw velocity.
Design for reversibility. Early choices set the slope.
We favor architectures – technical, legal, organizational – that keep doors open:
model-agnostic interfaces
modular compliance
and contracts that scale fairly
When we speak to AI, we’re not just instructing a system.
We’re shaping its worldview.
And when it speaks back, it shapes ours.
For me, developing a product or business model is never about thinking small — it’s about designing for the big picture. Implementation will follow in small or large steps, but always with the goal of turning the original vision into a market-shaping reality at the pace of scale.
Jake Revant – Founder & CEO
Incentives are the product.
Pricing, data rights, and risk sharing shape behavior more than features. We map who wins, who pays, who waits—and move friction where it’s cheapest.
Compliance as leverage.
Audit trails, residency, and incident playbooks aren’t paperwork; they’re distribution unlocks. When trust is a prerequisite, readiness becomes a growth channel.
Human-in-the-loop as a moat.
The durable edge isn’t “automation,” it’s service economics that elevate operators and deliver predictable uptime. People + systems > people vs. systems.
Narrative is an operating system.
Narrative is an operating system. A tight “why now / why this / why us” aligns hiring, roadmaps, partnerships, and capital. Clarity compounds.
Distribution seeks inevitability.
Wedges that solve one painful job, priced to win, expanding along existing workflows, beat cleverness. The best GTM feels like gravity.
Capital is a tool, not the storyline.
Milestones are evidence gates, not vibes: unit economics that survive scale, time-to-value measured in weeks, and a bias toward proof over polish.
Defaults do the heavy lifting.
Privacy-preserving data flow, kill-switches, safety cases, and observability ship in v0. Good defaults reduce regrets and increase the surface area for trust.
Taste sets the ceiling.
Products that feel inevitable escape commodity pricing. Taste isn’t decoration; it’s the synthesis of ergonomics, semantics, and timing.
We’re applying these principles now across a compact slate of concept-stage builds. Our bar: ship highest user-value, measurable safety, and distribution that grows because users feel smarter, not replaced by what they touch.
We’ll share build notes in public, including dead ends. The aim isn’t to predict the future; it’s to build it, and to shorten the distance between first principles and proof, and do it with enough rigor that momentum looks like luck.
💬 Do you believe in the same principles as we do and want to work on products that will shift our paradigm of human-machine interaction?
Let’s connect.
