Marcus
Swift.

I’m building Clarify as a connected environment for business knowledge, communication and execution: keeping goals, context and follow-through together.

The design problem is continuity: keeping the purpose of a task, the relevant business context and its execution connected across tools and conversations.

Clarify is the broader business environment. Specialized agents and connected services contribute within it, while the business workflow gives the work its meaning. This is the direction of the product, rather than a claim that every workflow is autonomous.

FileMaker and SaaS modernization: understanding an existing application, preserving its business logic and moving its workflows toward a modern web stack.

The starting point is the system people already rely on: its data model, relationships, scripts and user journeys. DDR extraction and structured analysis make those dependencies inspectable.

The conversion work connects that understanding to web interfaces, APIs and modern data services. Preserving working business behavior matters as much as replacing the technology.

A system for moving software work from an idea into a defined change, implementation and verification, using coding agents within a repeatable development process.

The work includes task definition, execution context, agent orchestration and the evidence needed to judge a change. The challenge is maintaining ownership and intent as work crosses those boundaries.

It treats software delivery as a system that can be observed and improved, with a distinction between generating code and demonstrating that the requested behavior works.

A process agent drawing on OODA, improvement Kata and Kaizen to understand performance, investigate problems and guide continuing improvement.

OODA — Observe, Orient, Decide, Act — structures diagnosis and response. Improvement Kata turns a desired condition into experiments and learning. Kaizen supplies the continuing practice of improvement.

Erin connects intended processes to observed evidence and follows interventions through to their effects. The system doing the business work retains its own execution responsibilities.

Integrations between operational software, communication tools and data sources, built around the way a business works.

Common patterns include keeping customer records aligned, moving information from a conversation into a workflow, and connecting scheduling, service delivery and accounting.

The engineering starts with ownership of the data, the event that initiates the work, exception handling and how the result can be confirmed. An integration earns its place by reducing friction in the wider process.

Developing surveys, translating collected data into useful reporting, and exploring predictive models that support better decisions.

This work brings a psychology background into measurement: defining the question, designing the instrument, interpreting responses and communicating findings in terms a decision-maker can use.

Predictive modelling builds on the data collected. Its usefulness depends on data quality, appropriate validation and a clear distinction between an observed pattern and a forecast. Confidential research and customer datasets are not reproduced here.