STATIONED DESIGN SYSTEM
The complete design system extracted from the Stationed homepage. Fonts, colors, spacing, motion, and every component — documented and ready to import.
black#131313warm#c9c9c5darkGrey#414140white#ffffffaccent#4F8CFFbgDark#0A1015bgSurface#111920bgElevated#182028bgCard#151d26bgLight#f5f6f8bgWarm#c9c9c5textWhite#fffffftextPrimaryrgba(255,255,255,0.92)textMutedrgba(255,255,255,0.6)textSecondaryrgba(255,255,255,0.45)textDark#0f1419textDarkMuted#3b4656textDarkSecondary#718096The accent blue (#4F8CFF) at various opacities — used for hero glows, card gradients, borders, and interactive highlights across all dark-bg pages.
accent#4F8CFFaccentHover#3a7aefaccentGlow08rgba(79,140,255,0.08)accentGlow06rgba(79,140,255,0.06)accentGlow04rgba(79,140,255,0.04)accentBorder15rgba(79,140,255,0.15)accentBorder20rgba(79,140,255,0.2)accentBorder50rgba(79,140,255,0.5)accentBg10rgba(79,140,255,0.1)accentBg12rgba(79,140,255,0.12)positivergba(100,220,150,0.8)negativergba(255,100,100,0.6)accentGradientLineaccentGradientCardaccentGradientTopaccentGradientHeroaccentRadialGlowImage-backed content slots with documented empty states for supplied photography.
The Stationed mark is an offset-square system traced from the brand lockup. The wordmark remains live Space Grotesk text.
displayThe quick brown fox jumps over the lazy dog
monoThe quick brown fox jumps over the lazy dog
bodyThe quick brown fox jumps over the lazy dog
14px28px312px416px520px624px832px1040px1248px1664px2080px24100px28120px32140px40160pxsmmdlgglowbtnHovercardHoverDark elevated surface with blur backdrop.
Semi-transparent warm border.
For service card grids.
display-large// BUILD
display-mediumWHAT MATTERS
display-small// DISCOVERY
accent-large1
accent-medium// SERVICE ARCHITECTURE
On Light Background
On Dark Background
hero (dark-on-light)about (light-on-dark)module (dark-on-light)First card in the grid spans 2 columns for the bento effect.
Standard single column.
Standard single column.
Standard single column.
Standard single column.
Sections with clipTop create the diagonal clip-path transition between sections.
Deep-dive into your team's existing workflows. We identify the highest-leverage automation opportunities and build an execution plan.
Subtle film-grain noise texture applied via CSS pseudo-element.
Used on /labs, /careers, /fellowship — the blue-glow dark theme
The dark-page hero is built from layered elements: an SVG background (HeroBg — /hero-bg.svg), a radial blue glow (HeroGlow), a dot-grid overlay (DotGrid), and a torn-paper edge (TornEdge). The HeroCanvas component composes all layers into one wrapper.
Wraps HeroBg + DotGrid + HeroGlow + TornEdge into one component. Used on the fellowship page.
Four hero variants: centered (homepage), split (for-teams), dev (careers), fellowship. All include a radial blue glow and optional SVG background.
Hands-on programs that turn your existing people into AI-native operators. Not lectures. Live work sessions.
We place senior builders inside your company to own an outcome end-to-end. Not staff aug. Operators accountable to results.
When the problem is ambitious enough to need a full team and focused enough to ship in six weeks, we run a Lab.
Minimum engagement is six weeks. Most teams extend once they see results.
We embed on-site when possible. Remote is fine for teams that already work asynchronously.
Healthcare, finance, logistics, real estate, and any team ambitious enough to ship.
Used on the careers page for job listings. Hover slides the row right with arrow animation.
Light-bg cards with icon areas and body text. Used on homepage and service pages.
Structured case-study card for the Work page.
A team with a workflow that needed an owner.
The process lived across too many tabs and too much memory.
A system in the team's existing environment.
The workflow became repeatable and visible.
The handoff matters as much as the build.
Uniform index card for the dense Work grid.
VENTURE STUDIO / FDE EMBED
The unit of work moved from campaign to experiment.
Founders had channel ideas but no way to run enough experiments to find out which ones worked.
Read the deploymentWeek-by-week timeline with blue marker dots. Used inside the Labs card on the homepage.
Infinite scrolling logo marquee with fade edges. Used on homepage and fellowship pages.
// AI DEPLOYMENT FIRM
// WHERE OUR SYSTEMS LAND
The gap is rarely model quality. It is ownership, data paths, and whether the system has a place in the work people already do.
VENTURE STUDIO / FDE EMBED
Agent-run go-to-market experiments
CONSUMER / SYSTEM BUILD
Searchable vendor-sourcing system
INTERNAL / EVALUATION SYSTEM
Roles-and-applications pipeline
OPERATIONS / PLATFORM MIGRATION
Migration onto owned infrastructure
Deployment, not advice, is the unit of work: systems only matter when they survive contact with the work.
Same repos, same data, same review process.
Enrichment, permissions, scheduling, evaluation; the parts that decide whether the interesting part works.
The system is owned, documented, and operated by your team when we leave.
AI doesn't fail because the models are bad. It fails because it never reaches the work.
// STATIONED / POINT OF VIEW
A focused build against one workflow, with a working system in the environment where the work happens.
View detailAgentic systems with the permissions, review steps, and failure behavior required for real operations.
View detailThe structured data layer that makes useful automation possible and keeps it current.
View detailEvidence-based evaluation for judgment-heavy processes where a demo is not a result.
View detailBuild days and training where your team ships against its own workflows and stack.
View detailMove working automations onto infrastructure your team controls and can extend.
View detailThe work has a shape because the handoff is part of the build. Five stages keep the team close to the workflow and make ownership visible from the first week.
// DEPLOYMENTS / SYSTEMS IN THE WORK
VENTURE STUDIO / FDE EMBED
Problem: Founders had channel ideas but no way to run enough experiments to find out which ones worked, and no shared infrastructure between companies.
What we built: A GTM system that handled the mechanical parts of an experiment end to end — audience definition, data collection, enrichment, scoring, message generation, and tracking — so a founder could go from a hypothesis to a live test the same week.
WHAT CHANGED
The unit of work moved from campaign to experiment: a founder could take a hypothesis to a live test in the same week, and what survived became shared infrastructure instead of one person's process.
WHAT WE LEARNED
Most of the value wasn't the generation step everyone expects. It was the enrichment and scoring underneath it — the boring part decided whether the interesting part worked.
CONSUMER / SYSTEM BUILD
Problem: The knowledge existed but wasn't queryable, so the same research happened repeatedly and new team members couldn't self-serve.
What we built: A structured directory with the sourcing and enrichment pipeline behind it, in the place the team already worked, so adding a vendor was a side effect of normal work rather than an extra chore.
WHAT CHANGED
Vendor questions became a lookup instead of a research project.
WHAT WE LEARNED
When a workflow depends on one person's memory, the deployment risk isn't the model — it's whether the system captures knowledge as a byproduct of work people already do.
INTERNAL / EVALUATION SYSTEM
Problem: Resumes are a weak signal for this, and "AI-heavy" resumes are now trivially easy to generate.
What we built: A roles-and-applications pipeline wired to our own operating stack, plus a structured evaluation approach that scores real work instead of claims — including interviews where candidates are expected to use AI.
WHAT CHANGED
Evaluation moved from impression to evidence, and the same infrastructure now supports client hiring conversations.
WHAT WE LEARNED
Every internal system we build is a rehearsal for a client deployment. This one became a reusable pattern for evaluating any judgment-heavy process.
OPERATIONS / PLATFORM MIGRATION
Problem: The workflows worked but were locked in — no ownership of the data, no way to test changes safely, no path to extend them.
What we built: A full inventory of what the platform was doing, an exporter that preserved fidelity, and a migration onto infrastructure the team owns, with the same workflows running.
WHAT CHANGED
The team kept its automations and gained the ability to change them.
WHAT WE LEARNED
"Owning your data" sounds like a strategy slide until an outage or a pricing change makes it an operational one.
Sit with the people doing the job and find the workflow worth attacking first.
Read the full method// NEXT DEPLOYMENT