Steven Skoczen is an AI consultant and full-stack software leader with 25+ years of hands-on development and 15 years of professional experience building scalable web and AI systems. He has founded products and companies, led engineering teams from startups to government contexts, and shipped production LLM-powered reasoning engines and five internal products solo in 16 months at Nisos. Equally comfortable in UX, backend architecture, and DevOps, he builds humane, privacy-respecting tools—like the Mindful Browsing Chrome extension and an encrypted course platform—and contributes to open-source projects such as django-analytical and the Will chatbot. His work focuses on AI that augments human intelligence with explainability and high-confidence "I don't knows," reducing bias and hallucinations in decision systems. A global nomad based in Boulder, he pairs creative writing and coaching with technical practice to help mission-driven organizations adopt practical AI capability. He is driven by a conviction to redistribute generational technology toward social good rather than centralized control.
15 years of coding experience
22 years of employment as a software developer
BS, Environmental Engineering, BS, Environmental Engineering at Cornell University
Will is a simple, beautiful-to-code bot for slack, hipchat, and a whole lot more.
Role in this project:
Back-end Developer & DevOps Engineer
Contributions:820 commits, 122 PRs, 403 pushes in 4 years 7 months
Contributions summary:Steven appears to be responsible for the core architecture, deployment, and maintenance of the Will project. The commits demonstrate work on the project's main application, including the setup of threads, integration with web frameworks like Bottle, and the creation of a system for handling incoming events. They also show contributions to setting up the project's build process.
Contributions summary:Steven contributed to the `django-analytical` project, which focuses on analytics services for Django projects. Their work primarily involved enhancing existing features and adding support for new analytics platforms such as Gaug.es and Intercom. The user also addressed bugs related to user identification and implemented custom variable support, demonstrating a focus on improving the integration and functionality of the analytics services within the Django framework. These changes improved the tracking capabilities of the analytical tools.
analyticspythondjango-frameworkdjangotemplates
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Steven Skoczen - AI Consultant - Strategy And Implementation