Approach
Not vibe coders.
How we actually run engagements, what we use, and what we won't do. The trust page — read it before the first call.
Principles
01
Production from day one.
We don't build demos. Every engagement starts with the assumption that this will run in production with real users. Evals, observability, and cost telemetry are part of v1, not a nice-to-have in v2. If you can't measure it on day one, you're flying blind.
02
Senior-led, always.
Every engagement is run by engineers with 15+ years of experience building at scale. We don't have junior engineers learning on client projects. The person who owns your work is the person in the room — not a manager who reviews it.
03
Evals over vibes.
AI systems don't work because they feel right in a demo. They work because you have a repeatable way to measure quality, catch regressions, and know when something broke. We build the measurement layer before we celebrate the output.
04
We own the cost curve.
Every AI system has a unit economics problem waiting to happen. We design for it upfront: self-hosted inference where it makes sense, model routing, context compression, caching. The goal is a cost structure that doesn't blow up when you hit scale.
05
Honest over comfortable.
We'll tell you when the thing you want to build is the wrong thing to build. We'll tell you when the timeline isn't realistic. We'd rather have that conversation before we start than after we've shipped the wrong thing.
06
Documentation is code.
We write the runbook, the architecture doc, and the decision log. Not because it's on the checklist, but because the codebase you hand off is only as useful as the context it comes with.
How an engagement runs
01
Discovery
1–2 weeks
We spend time understanding the problem, not just the ask. What's the actual constraint? What's been tried? Who are the users and what do they actually do? We come out of discovery with a clear problem statement, a proposed architecture, and a rough scope.
02
Design
1–2 weeks
Architecture, data model, and interface design happen before implementation. We write the architecture document, get alignment on the technical approach, and define the acceptance criteria for each major piece of work.
03
Build
4–16 weeks
We ship in weekly or biweekly iterations. Each iteration ends with a working, deployed increment — not a demo. You have visibility into what's happening at all times. No surprises at the end of the sprint.
04
Operate
Ongoing
The work doesn't end at launch. We establish the monitoring, alerting, and on-call runbooks that let you operate the system confidently. Handoff is explicit and documented, not a zip file of code.
Our stack
What we actually use. Engineers will read this and self-qualify. We don't pretend to be tool-agnostic — we use what works for the problem.
AI / ML
Python
vLLM
LoRA
LangChain
LlamaIndex
OpenAI API
Anthropic API
RunPod
Backend
Node.js
TypeScript
FastAPI
PostgreSQL
Redis
Prisma
Frontend / Mobile
Next.js
React
React Native
Expo
TypeScript
Chakra UI
Infrastructure
AWS
Vercel
Render
Docker
Terraform
GitHub Actions
Observability
Datadog
Sentry
PostHog
Prometheus
Grafana
What we don't do
The list that filters
the wrong clients.
Pure consulting decks. We don't write strategy memos and hand them off. We build the thing.
Junior offshore teams. Your codebase is not a training ground.
Ship without evals. If we can't measure it, we don't call it done.
Scope creep as a revenue strategy. We price engagements honestly and say no when the scope is wrong.
Ghost after launch. Handoff is a real event with documentation and a runbook.
Vibe coding. Every architectural decision has a reason. If we can't explain it, we shouldn't be making it.