The D.I.S.T. Framework is a four-phase methodology — Dissolve, Isolate, Synthesize, Titrate — enabling professionals to break their job descriptions into discrete tasks, separate AI-suitable work from uniquely human work, and build hybrid workflows accordingly. Developed by Michael Janzen after a 26-year Fortune-50 career in workflow and process design, it is released under an MIT License at github.com/michaelsjanzen/dist.
The Problem the Framework Addresses
Artificial intelligence is shifting the boundaries of many knowledge-work job descriptions, changing what some roles require and what individuals contribute. Existing consulting solutions for this disruption are typically proprietary and expensive, designed to serve enterprise competitiveness rather than individual adaptability.
The Four Phases
- Dissolve: Auditing work to break a rigid job description into its elemental tasks.
- Isolate: Sorting those tasks into two categories — Silicon (AI-ready) tasks and Carbon (uniquely human) tasks — to identify augmentation opportunities.
- Synthesize: Architecting symbiotic workflows where AI handles routine execution and the professional provides judgment.
- Titrate: Validating new workflows through careful testing to avoid the “productivity placebo” effect — where plausible-sounding AI outputs substitute for reliable results.
Why Open Source
The framework is distributed via GitHub using version control and collaboration tooling, not because it is software, but to allow community input to expand and refine it over time. The MIT License explicitly permits coaches, consultants, and organizational leaders to adapt, modify, and build commercial or personal practices on top of it.
Relationship to the Book
The framework serves as the operational protocol for Agile Symbiosis, a book that covers the economic context and philosophy behind career adaptability in an AI-influenced labor market. The toolkit — including prompts and templates for a structured career review — is available independently of the book at github.com/michaelsjanzen/dist.