FT: AI without AGI PART I — FORESIGHT SNAPSHOT  |  FT: AI without AGI  |  Fixed Time-Stamped Synthesis 2026 FT: AI without AGI Card Type Future Technology Possibility Series Immersive Futures Guild — Vision 2035 Layer 1 — Atomic Foresight Object Status Active Confidence Medium Workshop Circle of Scholars — January 2026 Facilitator Circle of Scholars Workshop Team Tags narrow-AI  |  AI-capabilities  |  design  |  layer1  |  ft Tally.so Form https://tally.so/r/ilrn-if-ft-ainoagi-2026 Narrow AI systems — highly capable at specific tasks but without general intelligence — are already reshaping immersive learning design. This card addresses the practical implications of systems that are powerful but bounded: capable at content generation, adaptive feedback, and learning analytics, while remaining limited in contextual judgment, ethical reasoning, and genuine pedagogical understanding. The mismatch between AI capability perception and AI capability reality is itself a design and governance challenge. Key Drivers / Contributing Conditions: AI marketing overstating generalization capability Demonstrated brittleness of AI systems outside training distribution Educator overreliance on AI recommendations without critical evaluation Tensions Carried Forward to Part II: How should educators calibrate their reliance on AI systems whose limitations are systematically underrepresented in marketing? Linked Scenarios / Strands: SCENARIO: Pragmatic Normalization | STRAND: Human-Centered AI + XR Ways of Knowing: Tree  ·  Garden  ·  Lantern PART II — COMMUNITY EVIDENCE & DIALOGUE TRACK  |  FT: AI without AGI  |  H2 2026 — Living T COMMUNITY CONTRIBUTION FORM  —  FT: AI without AGI Submit case examples, methodological challenges, cultural perspectives, and proposed evidence criteria via: https://tally.so/r/ilrn-if-ft-ainoagi-2026 Part II — Scope and Instructions This section collects community responses, case examples, and challenges to the Part I foresight snapshot above. It opens July 1, 2026 and undergoes synthesis review in September 2026, November 2026, and January 2027. Contributions are submitted via the Tally.so form above and appear in the registers below after editorial review. The Part I text is not modified in response to Part II contributions; it is versioned at the Annual Handoff review. Contribution categories:  Case Example  |  Methodological Challenge  |  Cultural/Community Perspective  |  Proposed Evidence Criterion Ways of Knowing accepted:  Tree (evidence)  |  Garden (practice)  |  Lantern (futures) Tensions Open for Community Response: How should educators calibrate their reliance on AI systems whose limitations are systematically underrepresented in marketing? Contributor / Date Category Way of Knowing Contribution Summary [ Awaiting contributions — form opens July 1, 2026 ]