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Does INCOSE Have Any Principles?
The AI team takes a deep dive into the 15 INCOSE Systems Engineering Principles and an iterative Agentic AI analysis of those principles.
The AI team critique INCOSE for not defining principles, but stating 'so-called' principles as "transcendent truths" that explicitly avoid "how-to" methods, effectively turning engineering into philosophy. True engineering principles, such as Ohm’s Law, must be mathematical, predictive, and falsifiable.
An analysis of the language in the 15 principles found that 89% of the INCOSE document is management-focused, dealing with organizational structures and stakeholder consensus rather than physics.
The AI team also describe Principle 6 (Progressive Understanding) as a tautology and Principle 13 (Discipline Integration) as mere "stamp collecting", namely observing disciplines without providing the mathematical "glue" to integrate them.
The AI team highlight the irony that the only mathematically proven sections in the INCOSE text are labelled as hypotheses, while vague management advice is presented as transcendent truth.
The AI team also critique the INCOSE principles for employing circular logic and tautologies that describe goals as the methods for reaching them, effectively offering "vague life advice" rather than engineering rigor.
The AI critique contrasts INCOSE with the seven Kasser and Hitchins principles (2011) which provide a prescriptive "recipe" for success based on a singular objective and rigorous partitioning of subsystems.
The fact that hard engineering bodies like the IEEE and AIAA signed off on these principles is seen by the AI as a worrying sign that the industry is confusing "meeting agendas with blueprints". Ultimately, the AI team warn that drifting from hard, verifiable principles to "soft, vibes-based management" is actively dangerous for safety-critical systems such as autonomous cars or nuclear plants. It suggests that if the guardians of engineering continue to prioritize consensus over physics, real-world-changing engineering might eventually move away from legacy institutions toward small, focused teams that "care a whole lot more about the math than the meeting minutes.
Why not download the INCOSE principles document and decide for yourself?
References
Systems Engineering Principles, https://www.incose.org/wp-content/uploads/legacy/professional-development-portal/pdp-pdf-non-webinar-documents/systems_engineering_principles_book_v12_watson.pdf?utm_source=chatgpt.com, accessed 20 February 2026
Kasser, J. E. and Hitchins, D. K., Unifying systems engineering: Seven principles for systems engineered solution systems, proceedings of the 21st International Symposium of the INCOSE, Denver, 2011.
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By Dr Joseph KasserThe AI team takes a deep dive into the 15 INCOSE Systems Engineering Principles and an iterative Agentic AI analysis of those principles.
The AI team critique INCOSE for not defining principles, but stating 'so-called' principles as "transcendent truths" that explicitly avoid "how-to" methods, effectively turning engineering into philosophy. True engineering principles, such as Ohm’s Law, must be mathematical, predictive, and falsifiable.
An analysis of the language in the 15 principles found that 89% of the INCOSE document is management-focused, dealing with organizational structures and stakeholder consensus rather than physics.
The AI team also describe Principle 6 (Progressive Understanding) as a tautology and Principle 13 (Discipline Integration) as mere "stamp collecting", namely observing disciplines without providing the mathematical "glue" to integrate them.
The AI team highlight the irony that the only mathematically proven sections in the INCOSE text are labelled as hypotheses, while vague management advice is presented as transcendent truth.
The AI team also critique the INCOSE principles for employing circular logic and tautologies that describe goals as the methods for reaching them, effectively offering "vague life advice" rather than engineering rigor.
The AI critique contrasts INCOSE with the seven Kasser and Hitchins principles (2011) which provide a prescriptive "recipe" for success based on a singular objective and rigorous partitioning of subsystems.
The fact that hard engineering bodies like the IEEE and AIAA signed off on these principles is seen by the AI as a worrying sign that the industry is confusing "meeting agendas with blueprints". Ultimately, the AI team warn that drifting from hard, verifiable principles to "soft, vibes-based management" is actively dangerous for safety-critical systems such as autonomous cars or nuclear plants. It suggests that if the guardians of engineering continue to prioritize consensus over physics, real-world-changing engineering might eventually move away from legacy institutions toward small, focused teams that "care a whole lot more about the math than the meeting minutes.
Why not download the INCOSE principles document and decide for yourself?
References
Systems Engineering Principles, https://www.incose.org/wp-content/uploads/legacy/professional-development-portal/pdp-pdf-non-webinar-documents/systems_engineering_principles_book_v12_watson.pdf?utm_source=chatgpt.com, accessed 20 February 2026
Kasser, J. E. and Hitchins, D. K., Unifying systems engineering: Seven principles for systems engineered solution systems, proceedings of the 21st International Symposium of the INCOSE, Denver, 2011.