001
We work inside your stack
Same repos, same data, same review process. No parallel universe that dies when we leave.
Embedded, not adjacent
STATIONEDEngineering studio
Scroll for more ↓Make the future [concrete].
Stationed imagines and engineers what new technology makes possible.
GTM & pipelineExperiments
Internal opsWorkflows
Vendor dataDirectories
HiringEvaluation
Agent infraPermissions
SupportRouting
··· >
Embed→Build→Land→Prove→Transfer
< ···[N.01/07]> Point of view
Intelligence is becoming a material.We build enough of it to step inside.
Book a call002
We build the boring layer
Enrichment, permissions, scheduling, evaluation: the parts that decide whether the interesting part works.
The layer that decides
003
We hand back the keys
Every system leaves owned, documented, and operated by your team. Transfer is part of the build.
Yours when we leave
5Stages, embed to transfer
1Workflow at a time
DaysTo a first working build
0Decks as the deliverable
Why pilots stall
- No owner after launch
- No path to the real data
- No place in the existing workflow
- Nobody's job to keep it alive
With Stationed
- One named owner, chosen before we build
- Built against production data paths
- Lands in the tools people already use
- Transferred with docs and a runbook
[N.03/07]> Capabilities
Different ways in.Same standard of work.
All capabilitiesEmbedded engineering
Put an engineer where the future is being decided.
Labs
Give an ambitious idea somewhere to become real.
Build days
The fastest way to understand a new medium is to make something with it.
[N.04/07]> The deployment loop
Get close enough to see what should exist.Then build it.
A loop, not a pipeline: what we prove in one deployment decides where the next one starts.
// 001
Embed
See the work from inside it.
// 002
Build
Make the new behavior real.
// 003
Land
Bring it into the world it has to survive.
// 004
Prove
Watch what changes.
// 005
Transfer
Leave capability, not dependency.
[N.05/07]> Deployments
Things we've made real.Systems in the world.
All deploymentsVENTURE STUDIO / FDE EMBED
A growth system that turns a hypothesis into an experiment.
Founders went from waiting on campaigns to running live tests the same week.
↗View detail
CONSUMER / SYSTEM BUILD
A company memory that didn't depend on remembering.
Vendor knowledge became searchable, structured, and kept current by the work itself.
↗View detail
INTERNAL / EVALUATION SYSTEM
A hiring system for a world where everyone can produce the code.
Evaluation moved from impression to evidence.
↗View detail
OPERATIONS / PLATFORM MIGRATION
The same system. This time they owned it.
The team kept every workflow running and gained the ability to change them.
↗View detail
[N.06/07]> Writing
Field notes.What the work teaches us.
All writingMETHOD↗ENGINEERING↗FIELD NOTES↗
The last mile is the whole job
Most AI projects we're called into aren't failing on model quality. They're failing in the ten feet between a working demo and the workflow it was supposed to change.
The boring layer is the product
Everyone wants to build the generation step. In every AI go-to-market system we've built, the value was sitting in the data layer underneath it.
We let candidates use AI in interviews. It made evaluation harder, not easier.
Banning AI in a technical interview measures a skill nobody on our team uses anymore. Allowing it broke most of what we used to look for — here's what we look at now.
[N.07/07]> FAQs
Straight answers.Before the first call.
001What does an engagement actually look like?
+
One or more engineers embed with your team, pick a workflow with an owner and an obvious right answer, and ship a working system into it. Then the loop repeats on the next workflow.
002How is this different from a consultancy or an agency?
+
The deliverable is a running system, not a recommendation or a deck. We work in your repos and review process, and the engagement is built around handing ownership back.
003Do we need an AI team already?
+
No. Most teams we work with know AI matters and have nobody whose job it is to own it. Part of the work is leaving that capability behind.
004What kinds of workflows do you take on?
+
High-frequency, painful, tractable work with a clear owner: GTM experiments, vendor and supplier data, hiring evaluation, internal ops, support routing, and the data pipelines underneath them.
005How fast do we see something working?
+
Days, not quarters. The first build is deliberately small so it can reach real users quickly and let what happens set the roadmap.