Code and Trust
Technology Expertise
Code and Trust engineers have shipped production systems across 8 core technology stacks. Every stack below links to a detailed expertise page covering what we build, how we use it, and the specific implementations we have delivered.
What technology stacks does Code and Trust specialize in?
Code and Trust specializes in 8 production technology stacks: Next.js, React, Python, TypeScript, PostgreSQL, n8n, OpenAI, and Anthropic Claude. Every stack has been used in shipped, production-grade projects — not experimental builds. AI implementation is a core practice across all stacks since 2022, not an add-on service.
8 production stacks — click any for depth
Each technology page below covers what Code and Trust builds with that stack, specific implementation patterns used in production, and the client contexts where we apply it. These are working references, not marketing overviews — every claim traces to a real delivered project.
Next.js
Server-rendered, SEO-optimized web platforms
App Router, React Server Components, ISR, edge middleware, and full TypeScript. 20+ projects in production.
View expertise →Python
AI/ML pipelines and backend API services
FastAPI, Django REST, LangChain, LlamaIndex, Pandas, Polars, Airflow — primary language for AI backend work.
View expertise →React
Component libraries and complex UI workflows
Design systems, Zustand/Jotai/React Query, performance optimization, WCAG 2.1 AA, React Native.
View expertise →PostgreSQL
Production database design and operations
Schema design, query optimization, zero-downtime migrations, PgBouncer, Neon, Supabase, AWS RDS.
View expertise →TypeScript
Strict typing from database to UI
Strict mode, Zod validation, type-safe ORMs, generated API client types — end-to-end type safety on every project.
View expertise →n8n
Enterprise workflow automation without Zapier pricing
Self-hosted deployments, version control, RBAC, production monitoring. CRM sync, document pipelines, webhook workflows.
View expertise →OpenAI
GPT-4o and o3 in production, not demos
Structured outputs, function calling, embeddings, vector search (pgvector, Pinecone), streaming, cost monitoring.
View expertise →Anthropic Claude
Extended context, prompt caching, computer use
Claude Sonnet/Opus, 200K context, citations, tool use — preferred model for document analysis and safety-critical AI features.
View expertise →How Code and Trust approaches technology selection
Code and Trust selects technology based on project requirements, not familiarity or trend. Each stack in our toolkit has a specific profile of strengths — we match tool to need, document the decision, and build with the expectation that your team will own and extend the result without us.
Senior-only team
Every engineer on client projects has 6+ years of production experience. We do not use client work as a training ground.
AI-native from day one
These are not bolt-on skills. We have shipped production AI systems across all 8 stacks since 2022 — before most agencies started marketing it.
Handoff-ready output
Every project ships with inline documentation, automated tests, and a knowledge transfer session. Your team can own and extend it independently.
Where these stacks get applied
Have a stack requirement in mind?
Tell us what you are building and which technologies are already in play. We will scope the work, resource it from the right stack, and give you a fixed-price quote.