Jalál, 16 ‘Ilm (Knowledge), 183 B.E.
Quotes for Reflection
“The purpose of learning should be the promotion of the welfare of the people…. True learning is that which is conducive to the well-being of the world, not to pride and self-conceit, or to tyranny, violence and pillage.” — Bahá’u’lláh [1]
Question for Consideration
Develop the comparison of action-reflection-revision loops in AI agents and Bahá’í consultation. [2] [3]
Perplexity Computer Response: Compare Action-Reflection-Revision Loops in AI Agents and Bahá’í Consultation
The action-reflection-revision thread [4] is now developed and preserved in the project. Here’s what emerged.
Three Distinct AI Loops
The literature conflates three things that must be kept separate. Revision within one attempt fails without external feedback: intrinsic self-correction degrades accuracy because the verification signal depends on the same process being verified [5] though models can be trained — just not prompted — into genuine self-correction. [6] Environment-grounded adaptation (Reflexion) works precisely because reflection is anchored in consequences the agent cannot talk its way past. [7] And learning across attempts — the closest analog to community learning — is now real: ExpeL distills insights from trajectories, [8] and LessonL’s solicitation–banking–selection mechanism lets a team of small models share lessons and outperform a much larger one. [9]
Be the Voice of…
Therefore, all souls should consider it incumbent upon them to investigate reality. Reality is one; and when found, it will unify all mankind. Reality is the love of God. Reality is the knowledge of God. Reality is justice. Reality is the oneness or solidarity of mankind. Reality is international peace. Reality is the knowledge of verities. Reality unifies humanity. — ‘Abdu’l-Bahá. [10]
Footnotes
[1] Bahá’u’lláh, ‘Abdu’l-Bahá. BAHÁ’Í SACRED WRITINGS. Bahá’í Reference Library. https://www.bahai.org/r/104138778
[2] Perplexity Computer. “Compare action-reflection-revision loops in AI agents and Bahá’í consultation.” Edited by Steve Bosserman. October 30, 2026. https://www.perplexity.ai/computer/tasks/fb20eb81-eae0-4dd5-b96e-7686b3a92ca9
[3] Transformative Leadership Education Staff. “Unite, Decide, Thrive: Using Consultation to Improve Decisions” (Free Online Course). Transformative Leadership Education. https://tinyurl.com/courseconsultation
[4] Universal House of Justice. “24 July 2013 – The National Spiritual Assembly of the Bahá’ís of Canada.” Bahá’í Reference Library. https://www.bahai.org/r/940508814
[5] Huang, Jie, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou. “Large Language Models Cannot Self-Correct Reasoning Yet.” arXiv, 3 Oct 2023 (v1), last revised 14 Mar 2024 (v2). https://arxiv.org/abs/2310.01798
[6] Kumar, Aviral, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal Behbahani, Aleksandra Faust. “Training Language Models to Self-Correct via Reinforcement Learning.” arXiv, 20 Mar 2023 (v1), last revised 10 Oct 2023 (v4). https://arxiv.org/abs/2409.12917
[7] Shinn, Noah, Federico Cassano, Edward Berman, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao. “Reflexion: Language Agents with Verbal Reinforcement Learning.” arXiv, 19 Sep 2024 (v1), last revised 4 Oct 2024 (v2). https://arxiv.org/abs/2303.11366
[8] Zhao, Andrew, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, Gao Huang. “ExpeL: LLM Agents Are Experiential Learners.” arXiv, 20 Aug 2023 (v1), last revised 20 Dec 2024 (v3). https://arxiv.org/abs/2308.10144
[9] Liu, Yuanzhe, Ryan Deng, Tim Kaler, Xuhao Chen, Charles E. Leiserson, Yao Ma, Jie Chen. “Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve.” arXiv, 29 May 2025 (v1), last revised 23 Oct 2025 (v2). https://arxiv.org/abs/2505.23946
[10] ‘Abdu’l-Bahá. THE PROMULGATION OF UNIVERSAL PEACE. Bahá’í Reference Library. https://www.bahai.org/r/628985716
