Protocols and file formats
Implementations that have to follow a specification, match binary behavior, and talk to systems you do not control.
Specialized engineering
Protocol implementations and system ports are often postponed because getting the specification right and matching existing behavior used to take too long. That is less true than it was.
Where this applies
A protocol specification can run to hundreds of pages. A port has to match behavior that was never fully documented. You often cannot tell if it works until it talks to a real server. Teams buy a library or drop the requirement instead. AI can produce a first implementation much faster than before. That code still has to work against the real specification and the real systems, not against tests the same tools wrote.
Implementations that have to follow a specification, match binary behavior, and talk to systems you do not control.
A component you pay for or live with because writing it never seemed worth the engineering time.
Moving a working capability across languages, platforms, or runtimes without changing the behavior people already depend on.
Systems with weak documentation, unusual constraints, or failures that only show up against the real outside world.
Internal plumbing that is too specialized for the normal backlog and too important to treat as an experiment.
Work where the first useful result is a yes-or-no, not an optimistic estimate.
A concrete example
SMB3 is how Windows shares files. Most teams buy a library. This was not a generated demo. It was a protocol implementation that had to talk correctly to real Windows and NAS servers.
A complete client built from Microsoft protocol specifications, including real file operations, encryption, and server interoperability.
The authentication stack was ported to Kotlin in full and integrated with the SMB3 client.
The working client was then ported across language and platform boundaries to run natively on iOS.
How to begin
The first scope is shaped around the decision the business actually needs, not a promise to build the entire system.
Read the relevant system or specification and produce a defensible feasibility decision.
Demonstrate the uncertain behavior against the real dependency, protocol, or environment.
Ship the smallest useful component and use actual operation to inform the next scope.
Who you work with
The first call is with the people who will open the repo. No salesperson in the middle. Nothing sent overseas.
Thirty years building software. Twenty of them running this company in Las Vegas. The job is not to sell you the biggest project. Sometimes the honest answer is you do not need one.
See how the work is run →Usually the problem is not the number of features. It is the cost of understanding a spec, an unfamiliar system, a dependency, or existing behavior well enough to act. Internal teams often leave this work sitting because investigation loses to the roadmap.
No. AI is part of how we work, not the category of work we take. The project itself may be a protocol, a port, an integration, an internal component, or some other specialized software problem.
We pick the smallest deliverable that answers the important unknown: a written yes-or-no, a test against the real system, or the smallest piece that can actually run. Larger work is quoted from that, not from a guess on a sales call.
Yes. We normally work directly with the people who own the surrounding system. They know the business and how it runs; we make the technical decisions and the checks visible so the team can own the result after we leave.
Tell us what has been deferred, why it matters, and which uncertainty made it impractical. The first conversation is free.