Architectural Tech Stack

Extending and customizing Microsoft 365 Copilot to create bespoke AI experiences that are deeply integrated into the flow of work within Teams, Outlook, and more.

Building enterprise-grade conversational agents and custom copilots that leverage Generative AI plugins and agentic actions, grounded in Microsoft Graph and enterprise data.

Production-grade access to GPT-4 / GPT-5 class models with enterprise governance, private networking, and compliance posture suited to regulated workloads.

Designing, evaluating, and deploying agentic RAG solutions with built-in safety, content filters, and observability for enterprise rollout.

An AI pair programmer that accelerates development by suggesting code and entire functions in real-time, directly within the code editor.

Building pro-code agents with the M365 Agents SDK to orchestrate multi-turn reasoning, tool use, and channel delivery across Microsoft 365 surfaces, including Teams and Copilot.

Designing autonomous system loops that allow AI models to reason, plan, and execute tool-based actions to solve multi-stage business problems.

Implementing advanced Retrieval-Augmented Generation workflows using vector databases and semantic search to ground AI outputs in proprietary corporate knowledge.

I benchmark non-Microsoft model APIs (Google Gemini, Anthropic Claude, OpenAI direct, local Ollama) against Azure OpenAI for prototypes and capability comparisons. Production deployments target the Microsoft stack for governance, identity, and compliance.

The complete suite of low-code tools I use to build end-to-end business solutions, including apps, automations, bots, and analytics, all connected to your data.

Used to build enterprise-grade conversational AI assistants and custom copilots that leverage Generative AI plugins to perform complex actions and streamline user interactions.

Integrating pre-built AI models directly into Power Apps and Power Automate for tasks like document processing, prediction, and object detection without requiring data science expertise.

Orchestrating complex workflows across applications and services to automate repetitive business processes.

For creating custom, low-code applications that serve as intuitive, user-friendly interfaces for sophisticated automated workflows and data management.

For creating scalable and secure data models that provide a robust foundation for enterprise-grade Power Platform solutions, ensuring data integrity and governance.

Using the low-code, Excel-like language to build logic and behavior within Power Apps, enabling rapid development of complex functionality.

The central collaboration hub where conversational AI agents and automations are deployed to integrate seamlessly into the user's daily workflow.

Shipping custom Teams apps, message extensions, and AI-powered bots using the Teams Toolkit and Teams AI SDK, with full support for SSO, adaptive cards, and Copilot extensibility.

Using SharePoint for document management, intranet portals, and as a data source for Power Platform solutions.

Building and deploying custom RAG solutions and enterprise-grade AI agents with a focus on evaluation, safety, and content filtering.

Implementing secure, AI-powered search over enterprise data, enabling advanced information retrieval for Retrieval-Augmented Generation applications.

Deploying GPT-4 / GPT-5 class models with private networking, customer-managed keys, and the Microsoft compliance posture required for regulated workloads.

Hands-on exposure to Vertex AI as a benchmark reference; production deployments are anchored on the Microsoft cloud.

Establishing guardrails for AI safety, bias mitigation, and transparency to ensure automated systems remain ethical and compliant.

Applying architectural principles to the data lifecycle to ensure high-quality ingestion and consistent grounding for AI models.

The primary stack for building performant, type-safe user interfaces for AI applications and strategic dashboards.

Utilizing Python to architect RAG pipelines, data transformations, and custom AI logic that extends the capabilities of standard platforms.

Leveraging high-performance systems programming to build efficient web-based tools and secure client-side AI components.

Essential for collaboration, version control, and managing the source code of complex architectural deployments.

Jira

Running agile delivery for AI and Power Platform engagements with epics, sprints, and backlogs that keep multi-team builds shipping on cadence.

Confluence

Centralizing architecture decisions, runbooks, and solution documentation so enterprise knowledge stays discoverable and version-aware across teams.

Designing and testing RESTful interfaces (Postman) to ensure seamless communication between AI agents and external business systems.