Library
News, white papers, articles, and resources from our team on federal technology, AI, data security, and delivering for our clients.
Designing the Governed Cloud: Architecture, Integration, and Accountability
Cloud migration commits budget, staff time, and operating risk before a workload runs in its new location. When dependencies, ownership, and recovery are left unsettled, the move carries old problems into new infrastructure. Leaders should judge migration readiness by the decisions and evidence behind a workload rather than by whether it can be moved. This paper proposes a minimum decision record, four evidence gates, and a decision-rights allocation for making that judgment, and it closes with a 60-day pilot that tests the approach on one workload.
Journey Through Alchemy SDLC™ (Part 6): When the Rhythm Meets Reality
Finding your rhythm is one thing. Learning to navigate the unexpected while keeping that rhythm is another.
From Raw Data to Reliable Service
A team can define the right decision and build a sound analytical method but still lose confidence in the result because the data arrive late or change meaning along the way. Sometimes, no one can reconstruct what happened between the source and the report. The processing environment needs an operating agreement that covers those failures and gives someone authority to act when they occur.
Beyond the Pilot: Closing the Gap Between Demonstration and Deployment
Artificial intelligence (AI), automation, and modern software engineering have made it faster than ever to demonstrate new capabilities. Turning a demonstration into a capability that works every day is still slow, and that is where many modernization efforts stall. This paper introduces a seven-stage modernization lifecycle, identifies the handoffs where operational knowledge is most often lost, and poses five questions leaders should answer before committing to deployment. It argues that organizations must evaluate the delivery model that will carry a technology into operation with the same rigor they apply to the technology itself.
Tech Note 4: Integrating Requirements with Microsoft Power Platform Apps Using AI
Alchemist AI Pro™ output, expanded by a Python “architect” into one JSON manifest and pushed to Dataverse by a Java deployer, gives Power Apps Copilot and Power Automate Copilot what they need to finish a Microsoft Power Platform application. This note includes the prototype code.
Five Questions Every AO Needs to Answer
In September 2025, the Department of War (DoW) announced the Cybersecurity Risk Management Construct (CSRMC), which calls for automated, continuous risk management across a system’s life as the replacement for point-in-time cyber assessments (DoW Chief Information Officer [CIO], 2025). That fundamentally changes the authorizing official’s (AO’s) job. An AO used to judge a package once and then approve it. Under CSRMC, the AO has to continuously assess whether a system’s risk is acceptable for as long as that system is used.
Tech Note 3: ServiceNow, From Use Cases to a Running Application
Alchemist AI Pro™ use cases, parsed by a Python or Java extractor and posted to a ServiceNow® Scripted REST API, give Now Assist and Otto what they need to build a running ServiceNow® application. This note includes the prototype code and payloads.
Portability Before the Bill
All three hyperscalers waived data egress fees for departing customers in 2024, and the EU Data Act bars switching charges outright from January 12, 2027. That turns the price of leaving a cloud provider into a number a program office can finally put on paper, and it exposes where the real migration cost has always been: the engineering rework, the compliance boundary, and the provider-specific services nobody inventoried.
Managing Data Science as an Operational Capability
Data science begins with evidence rather than an assumed application, and without a named decision it can consume staff capacity while producing analyses no owner can use. This paper sets out a decision-centered management model covering ownership, data readiness, fitness for purpose, monitoring, and the evidence a manager needs to authorize, accept, and sustain an analytical capability.
What Building Real Software Taught Me
A logistics and operations leader with no development background took two applications from operational idea through requirements, AI-assisted development, testing, the Final Mile, and acceptance. Producing code turned out to be the fast part. Knowing what to build, proving it worked in the real world, and owning the decision to accept it did not get easier.
Journey Through Alchemy SDLC™ (Part 5): From the Other Side of the Console
The same journey, reported from the other side of the console. The XO describes what an assignment, a missing constraint, a correction, a template, or a green test actually changes — and what it needs from a Captain to keep fast execution pointed at the objective.
Tech Note 2: Appian, Undoing Platform Lock-In
Appian keeps an application's definitions inside a web-based designer rather than as files on disk. This note walks through Alchemist AI Pro™ reading a complete Appian application straight from that interface and rendering it as use cases, tests, personas, and rules.