Improving Data Management Maturity so AI and agents can be trusted with the data, metadata, and context they need.
I'm a product manager and software designer with 15+ years of experience leading data-driven solutions and AI products. At Salesforce, I lead AI Data Platform product strategy, focused on improving Data Management Maturity (DMM) so AI and agents have the trusted data, metadata, and context they need.
I pair product strategy with hands-on technical execution — using software engineering tools and LLMs to define requirements, explore ideas faster, and ship proof-of-concepts that validate customer needs directly. Along the way I founded a Data Visualization Center of Excellence, ran enterprise-wide DMM programs, and mentored 200+ data visualization engineers.
Outside of Salesforce, I hold an MS in Computer Science from CU Boulder (completed September 2026), write on data governance and technical leadership, and build AI/product tools in the open — from Claude Code plugins to deep learning coursework projects.
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2026 (ongoing) | Portfolio Site | tom-bohn.github.io | Active | Personal portfolio built with Next.js, React, and TypeScript — blog, projects, certifications, and an interactive V2MOM framework. |
| 2026 (ongoing) | Claude Code Plugins | claude-plugins | Active | Personal monorepo of Claude Code plugins for technical writing, solution architecture, and marketing workflows. |
| 2025 | AI/ML Analysis | SFDC-User-Permissions-AI | Active | Analyze Salesforce user permissions using AI/ML techniques — scraping, processing, and LLM-driven analysis pipelines. |
| 2025–2026 | Whitepapers | thomas-bohn-articles | Active | Whitepapers and frameworks on software engineering leadership, organizational transformation, and data governance, written using spec-driven development principles. |
MS Computer Science Coursework — CU Boulder, 2023–2026 (click to expand)
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2025 Sept | CycleGAN | deep-learing-gan-monet-painting | Completed | Generate Monet-style paintings from photographs using CycleGAN architecture. Replicates Monet's artistic style through color palette, brush strokes, and lighting techniques. |
| 2025 Aug | CNN | deep-learing-cnn-cancer-detection | Completed | Develop CNN for binary classification of histopathologic images to detect metastatic cancer using PatchCamelyon dataset. |
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2025 Oct | LLM Classification | deep-learning-llm-classification-finetuning | Completed | Fine-tune DeBERTa v3 model to predict human preferences in LLM responses using Chatbot Arena dataset with systematic optimization experiments. |
| 2025 Sept | LSTM | deep-learing-rnn-disaster-tweets | Completed | Build LSTM model to classify disaster-related tweets using 10,000 hand-labeled samples for emergency response monitoring. |
| 2024 Oct | Unsupervised NLP | unsupervised-nlp-sfdc-classification | Completed | Apply unsupervised learning to categorize 1,498 Salesforce documentation pages using NLP feature extraction and clustering. |
| 2024 Oct | Supervised NLP | supervised-nlp-auto-classification-for-sfdc-documentation | Completed | Develop NLP model to automate Salesforce documentation classification across Sales Cloud and Service Cloud features. |
| 2023 Sept | Unsupervised Learning | news-articles-categorization | Completed | Model BBC News article categorization using NLP, matrix factorization, and compare unsupervised vs supervised approaches. |
| 2023 Sept | Deep Learning | marketing_text_classification | Completed | Classify marketing text using k-train wrapper for TensorFlow, Keras, and Hugging Face Transformers with performance evaluation. |
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2023 Aug | Supervised Learning | customer-churn-prediction | Completed | Predict customer churn using Random Forest classifier on public dataset, emulating business context for attrition analysis. |
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2023 Oct | Network Analysis | marketing-network-analysis | Completed | Apply network analysis techniques to marketing analytics, modeling relationships and influence patterns between entities. |
| 2023 Sept | Topic Modeling | product-review-topic-modeling | Completed | Unsupervised text classification of product reviews using topic modeling for marketing analytics insights. |
| Date | Type | Repo | Status | Description |
|---|---|---|---|---|
| 2023 April | Data Visualization | consumer-price-index | Completed | Create comprehensive CPI visualizations to communicate inflation impact beyond top-level numbers for public understanding. |
| 2023 April | R Analysis | nypd-shooting | Completed | Analyze NYPD shooting incident data to identify contributing factors and trends in New York City shootings. |
| 2023 April | R Analysis | covid-19 | Completed | Conduct exploratory data analysis of global and US COVID-19 datasets to identify data interactions and connections. |
| Date | Title | Topic |
|---|---|---|
| 2026 Mar | The Pyramid Approach to Technical Writing | Technical Writing / AI Grounding |
| 2026 Feb | Measuring Value for Data Products | Product Strategy |
| 2026 Feb | My Background: Ten Years at the Intersection of Product, Architecture, and Engineering | Career |
| 2026 Feb | My Leadership Style: How I Approach Engineering Management | Technical Leadership |
| 2026 Jan | The Enabling Team Framework | Organizational Transformation |
See the full archive on Medium →
Lifelong Learner — completed an MS in Computer Science at CU Boulder (Sept 2026) while working full-time at Salesforce
Knowledge Sharing — published whitepapers and articles on data governance, technical leadership, and best practices
Growth Mindset — always exploring new technologies, methodologies, and AI-assisted ways of working
Builder — bridges academic research and practical business applications
Solving Complex Problems — using data to uncover insights that drive business value
Building Teams — creating environments where data professionals can thrive
Continuous Innovation — staying at the forefront of AI/ML and agentic development
Making Impact — shipping products that improve decision-making and outcomes