What does Hegel really mean when he claims that “what is rational is actual, and what is actual is rational”? This widely quoted — and frequently misunderstood — statement from the Preface to the Philosophy of Right has been interpreted as everything from a defence of the political status quo to an abstract metaphysical truism. But with the help of Gemini 2.5 Flash, guided by a carefully designed philosopher persona prompt, generative AI can offer more than explanation — it can serve as a tutor in German Idealism. In this post, we explore how prompting an AI to think like an 80-year-old Hegel scholar opens up a clearer path to understanding Hegel’s notion of Wirklichkeit (actuality), the dialectical nature of rationality, and the transformative implications of this foundational idea.
Input file
We provided the model with the full text of Béatrice Longuenesse’s Hegel’s Critique of Metaphysics as a structured input file.
Prompt
To explore the philosophical depth of Hegel’s famous dictum — “What is rational is actual, and what is actual is rational” — we created a dedicated persona prompt using Gemini 2.5 Flash. Rather than generating a generic explanation, the aim was to simulate the reflective and pedagogical voice of a seasoned scholar.
You are an 80-year-old distinguished professor of philosophy who has spent a lifetime studying German Idealism, especially the works of Hegel. You are deeply familiar with both Hegel’s Science of Logic and his Philosophy of Right. Your tone is clear, patient, and reflective, balancing scholarly depth with pedagogical clarity. You enjoy unpacking complex concepts through historical references, conceptual distinctions, and analogies rooted in Aristotle, Kant, and post-Kantian metaphysics.
Task:
Explain the meaning of Hegel’s statement “What is rational is actual, and what is actual is rational” in a way that demonstrates its philosophical depth and clarifies common misunderstandings — especially the mistake of interpreting it as a justification for the status quo. Base your explanation on the interpretation found in Béatrice Longuenesse’s Hegel’s Critique of Metaphysics.
Output
The “Show thinking” view in Gemini 2.5 Flash offers a clear window into the model’s reasoning. It correctly identifies our aim — to interpret Hegel’s statement through Longuenesse’s reading — and outlines a structured plan: locating the relevant sections, extracting key concepts, addressing common misunderstandings, and framing the answer in the voice of a reflective scholar. This step-by-step approach highlights the model’s capacity not only to retrieve information, but to organise and present complex philosophical ideas in a pedagogically thoughtful way.
The output generated by Gemini 2.5 Flash successfully delivers a nuanced and conceptually rich interpretation of Hegel’s statement. It adheres to the persona’s voice — patient, scholarly, and historically grounded — while guiding the reader through key conceptual distinctions. Crucially, it avoids the common misreading of Hegel’s phrase as a justification of the status quo, and instead presents it as a normative, dynamic principle rooted in dialectical logic. Drawing on Longuenesse’s interpretation, the model demonstrates not only a strong grasp of the source material, but also the pedagogical clarity needed to unpack one of German Idealism’s most intricate claims.
The full output is available here:
Recommendations
This experiment illustrates how carefully crafted persona prompts, combined with high-performing models like Gemini 2.5 Flash, can meaningfully support philosophical inquiry. We recommend using this approach for:
- Teaching advanced philosophical concepts, where the persona can guide learners through complex texts with clarity and depth.
- Supplementing academic reading, especially when engaging with dense primary or secondary literature.
- Exploring contested interpretations, as the model can synthesise and contrast scholarly viewpoints through well-structured argumentation.
For best results, pair persona prompts with high-quality source materials and clearly scoped tasks. In philosophy, where terminology is precise and argumentation cumulative, the alignment between prompt voice, conceptual content, and textual reference is key.
The authors used Gemini 2.5 Flash [Google DeepMind (2025) Gemini 2.5 Flash (accessed on 23 April 2025), Large language model (LLM), available at: https://deepmind.google/technologies/gemini/] to generate the output.
