Custom software for Lincoln — built the AI-native way.
We pair senior engineers with an AI-accelerated delivery model to design, build, and ship custom software far faster than a traditional shop — without the fragile, unreviewed code that gives AI a bad name.
AI changed the economics of custom software. We rebuilt our process around it.
Lincoln anchors a strong insurance, agriculture, and higher-education market — home to a deep insurance employer base, the University of Nebraska-Lincoln and its research-software ecosystem, and a growing B2B SaaS scene. Senior hires are six figures, months out, and picked over by insurance employers, UNL, and the smaller venture-backed bench. AI changes the math, but only when senior people own the parts AI gets wrong.
AI is genuinely good at the repetitive 70% of software work: scaffolding, boilerplate, CRUD, first-draft UI, test stubs, glue code. It is dangerously unreliable at the other 30%: architecture, security, edge cases, and knowing when its own output is wrong. Teams that ship raw AI code learn this in production.
We build for Lincoln operators — insurance and claims platforms, ag-economy and food-systems tools, edtech and student-facing platforms, B2B SaaS shipping into regional and ag-economy buyers, and modernization of decades-old enterprise stacks. Our model: AI handles scaffolding and the repetitive 70%; a senior engineer owns architecture, security review, and signs off on every change.
AI writes the first draft. A senior engineer signs off.
Every change runs through review for security, tests, and architecture before it ships — that review is the product.
const draft = await ai.generate(spec) // minutes, not daysreview(draft, { security: true, tests: true, architecture: true })// ✗ rejected: claims-processing handler double-processes on retry → idempotency key + replay test// ✓ merged: FERPA-safe role check on student-record endpoint, ordered-event reconstruction for late insurance webhooksOn a Lincoln insurance, edtech, or ag-economy build, the failure modes are non-idempotent claims handlers, FERPA-vs-HIPAA confusion, and late-arriving webhook drift. Senior review catches them before a month-end run, audit, or IRB does.
What we build for Lincoln companies.
Insurance & claims platforms
Underwriting tools, claims automation, and broker portals for carriers and InsurTechs.
EdTech & learning platforms
Student-facing apps, LMS extensions, and institutional tools that work for districts and universities.
SaaS platforms
Multi-tenant products with auth, billing, and dashboards — MVP to scale.
Modernization
Move legacy systems onto a modern, maintainable stack — incrementally, no big-bang.
AI applications
Copilots, RAG, search, and agents grounded in your data, with guardrails and evals.
Internal tools & copilots
Operations tooling that replaces the spreadsheet-and-tribal-knowledge workflow.
A senior team that moves at AI speed.
You work with senior engineers who own architecture and quality — not a junior pool with raw AI output bolted on. We communicate in Central Time and integrate with your tools and cadence.
Lincoln's senior engineering pool is concentrated around insurance employers, UNL, and a smaller venture-backed bench — three-to-six months to hire and quietly poached by Omaha and remote coastal roles. An AI-native team gets you shipping this week, flexes monthly, and doesn't add to your local hiring backlog.
Talk to an engineerTraditional Lincoln dev shop vs. AI-native.
| Traditional Agency | DEV.co (AI-native) | |
|---|---|---|
| Time to working software | Months | Days to weeks |
| Cost | Full senior rates, all hours | Lower — AI removes the rote work |
| Code quality | Good (if senior) | Same bar — every change reviewed |
| AI risk | — | Contained by senior review + tests |
| You own the code | Usually | Always — full repo on day one |
| Scales with you | Slow to staff up | Flex up or down monthly |
Common questions from Lincoln teams.
Do you work with Lincoln companies?
Do you work with insurance core systems and FERPA-scoped student data?
Is AI-built software production-ready?
Will we own the code?
How fast can we start?
Can you work with our existing team?
Let's build it — Lincoln.
Tell us what you're trying to ship. We'll give you an honest recommendation, a timeline, and a fixed quote — and tell you if AI-native is the right fit or not.