# Letters from Future Self: Augmenting the Letter-Exchange Exercise with LLM-based Agents to Enhance Young Adults' Career Exploration

arXiv: https://arxiv.org/abs/2502.18881 · HTML: https://mlsanity.com/paper/2502.18881/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2025.

## Built on by (most cited first, 8 of 8)

- [When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being](https://mlsanity.com/paper/2512.08937/) (2025)
- [AI-exhibited Personality Traits Can Shape Human Self-concept through Conversations](https://mlsanity.com/paper/2601.12727/) (2026)
- [Future You: Designing and Evaluating Multimodal AI-generated Digital Twins for Strengthening Future Self-Continuity](https://mlsanity.com/paper/2512.06106/) (2025)
- [CareerPooler: AI-Powered Metaphorical Pool Simulation Improves Experience and Outcomes in Career Exploration](https://mlsanity.com/paper/2509.11461/) (2025)
- [Simulating Life Paths with Digital Twins: AI-Generated Future Selves Influence Decision-Making and Expand Human Choice](https://mlsanity.com/paper/2512.05397/) (2025)
- [Words to Describe What I'm Feeling: Exploring the Potential of AI Agents for High Subjectivity Decisions in Advance Care Planning](https://mlsanity.com/paper/2512.11276/) (2025)
- [InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection](https://mlsanity.com/paper/2603.27563/) (2026)
- [AI-Mediated Self: How HCI Defines and Relates to the Self](https://mlsanity.com/paper/2610.10770/) (2026)

## Abstract (arXiv)

Young adults often encounter challenges in career exploration. Self-guided interventions, such as the letter-exchange exercise, where participants envision and adopt the perspective of their future selves by exchanging letters with their envisioned future selves, can support career development. However, the broader adoption of such interventions may be limited without structured guidance. To address this, we integrated Large Language Model (LLM)-based agents that simulate participants' future selves into the letter-exchange exercise and evaluated their effectiveness. A one-week experiment (N=36) compared three conditions: (1) participants manually writing replies to themselves from the perspective of their future selves (baseline), (2) future-self agents generating letters to participants, and (3) future-self agents engaging in chat conversations with participants. Results indicated that exchanging letters with future-self agents enhanced participants' engagement during the exercise, while overall benefits of the intervention on future orientation, career self-concept, and psychological support remained comparable across conditions. We discuss design implications for AI-augmented interventions for supporting young adults' career exploration.