Strategy. Architecture. Execution.

Turn AI opportunity into real-world results.

Mishkin Enterprises LLC provides AI-first software development, technology strategy, software modernization, and fractional CTO leadership. We design and deliver production-grade software around clear business outcomes, disciplined engineering, and operational reality.

◆ PRACTICAL AI SOLUTIONS

◆ ENGINEERING DISCIPLINE

◆ PRODUCTION FOCUS

Bryan Mishkin, Founder and CTO of Mishkin Enterprises LLC

Bryan Mishkin
Founder & CTO · Mishkin Enterprises LLC

Three ways to work together

Flexible engagement models, from focused technical guidance to hands-on delivery.

Strategic advisory represented by a compass and connected network nodes

Strategic advisory

Focused technology strategy and AI advisory for architecture, product delivery, engineering decisions, modernization, and technical risk.

AI-first software delivery represented by code brackets and a connected workflow

Delivery engagements

AI-first software development built around a defined outcome, explicit responsibilities, production-grade implementation, and validation against users and operations.

Ongoing CTO leadership represented by an organizational hierarchy and connected systems

Ongoing CTO leadership

Fractional CTO leadership for architecture, priorities, engineering teams, AI adoption, software delivery, modernization, and technical risk.

The Mishkin Method

A disciplined AI-first delivery loop.

AI is used throughout the lifecycle to accelerate iteration. Human judgment remains responsible for architecture, security, testing, operations, and the final decisions.

01 Define the Outcome

Start with the business outcome and operational reality.

02 Iterate the Specification

Refine requirements, rules, workflows and boundaries with AI.

03 Iterate Possible Solutions

Explore workflows, architectures and implementation options.

04 Implement at Production Grade

Build the selected solution with production engineering discipline.

05 Validate Against Reality

Test working software against users, specifications and operations.

06 Go Live and Continue

Use production learning to correct, improve and extend the system.

Production is the standard.

The meaningful test of AI-assisted engineering is not whether it can make a compelling prototype. It is whether the approach can deliver software that survives users, security requirements, integrations, changing requirements, and day-to-day operation.

Business outcome first

Start with the result the organization needs, not with a model, framework, or pile of generated code.

Engineering still matters

Architecture, testing, security, integrations, observability, and operational discipline remain part of production delivery.

Reality closes the loop

Working software is validated against users, specifications, and what the system actually reveals once it is operating.

Let’s build what’s next

Have a software initiative that needs to become real?

Tell me the outcome, where things stand today, and the constraints that matter. We can determine the right engagement from there.