Every engineer runs AI-assisted by default
LLM pair programming and agentic scaffolding are part of the default workflow, not an optional tool or demo.
Human Ownership. AI Velocity.
AI-Augmented Software Engineering Talent
Build and ship dramatically faster with senior software engineers who use generative AI, coding agents, and agentic workflows as their primary engineering tools, while keeping architecture, judgment, and accountability human.
US-based and timezone-aligned engineers across 100+ technologies.
10x Shipping Velocity
Without quality tradeoffs.
Wisby combines senior engineering judgment with AI-powered implementation, testing, review, and delivery.
The AI writes fast. The engineer decides what's worth keeping.
The goal is not to generate more code. The goal is to produce useful, reliable, production-quality software dramatically faster.
AI-native engineering
AI-native isn't the pitch. It's the construction.
Anyone can say they use AI. Here's what it actually changes about how we build software, day to day.
Review is built for AI output specifically
Engineers review architecture, edge cases, security, performance, maintainability, and operational impact.
We maintain our own AI engineering workflows
Project context, retrieval, MCP connectors, agentic harnesses, evaluations, and automated verification replace generic prompts.
Velocity is measured against quality
The objective isn't simply to produce code faster. The objective is to ship better software faster.
The team shape matters
Not the usual dev shop.
Most of what makes a project go sideways isn't the tech. It's the shape of the team building it.
A rotating cast of offshore contractors you need to re-explain the codebase to every quarter.
One small senior team that owns the engagement from start to finish.
A black box where AI-generated code reaches production because nobody's job is to catch it.
Every line is reviewed by a named engineer before it ships.
Layers of account managers and status decks between you and the people writing the code.
You talk directly to the engineer doing the work. No translation layer. No decks.
AI engineering workflow
Architect. Build with AI. Verify. Review. Ship. Own.
AI accelerates the work. Deterministic checks and senior engineers decide when it is ready.
- 01
Discover
We learn the domain, constraints, users, existing architecture, and what actually matters before writing code.
- 02
Architect
A senior engineer defines the architecture, data model, boundaries, failure modes, and technical approach.
- 03
Build with AI
Generative AI and coding agents accelerate implementation, refactoring, testing, and documentation.
- 04
Verify
Builds, tests, linters, E2E flows, and security checks validate the implementation.
- 05
Human Review
A senior engineer decides whether the output is correct and appropriate for production.
- 06
Ship & Own
We deploy with production-grade practices and remain accountable after launch.
Services
Engineering across the product lifecycle.
Senior specialists, AI-augmented by default and accountable for the production outcome.
Service
Frontend Engineering
Interfaces built for the people who use them, not the demo.
Service
Backend Engineering
Systems that hold up under load, audit, and time.
Service
Mobile Engineering
Native-quality mobile experiences shipped at modern velocity.
Service
Cloud & DevOps
Infrastructure someone can actually reason about.
Service
Data & AI Engineering
The engineering discipline behind the model, not just the demo.
Service
Quality & Test Engineering
The discipline that keeps velocity from becoming risk.
Engagement models
Choose how much you want us to own.
Add one senior engineer, assemble a dedicated team, or hand us the project end to end.
Start a conversation
Put senior engineers behind your roadmap.
Tell us what you need to ship. We'll tell you honestly whether we're the right fit.