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What to read?

Owner: Vadim Rudakov, lefthand67@gmail.com
Version: 0.3.1
Birth: 2025-10-01
Modified: 2025-12-18

Language Models

Building LMs

  1. Machine Learning Systems. Principles and Practices of Engineering Artificially Intelligent Systems - Harvard

  2. The Smol Training Playbook: The Secrets to Building World-Class LLMs [HuggingFace]

Small Language Models (SLMs)

  1. Small Language Models are the Future of Agentic AI [last revised 15 Sep 2025]

Tools

  1. CrewAI [github repo]

  2. DSPy: Declarative Self-Improving Language Programs

  3. MLflow + DVC docs

  4. AI pair programming in your terminal

Promt Engineering

General

  1. Prompt Engineering Guide [OpenAI]

  2. Prompt-Engineering-Guide

  3. DAIR.AI Courses [OpenAI NOT FREE]

  4. OpenAI Cookbook [OpenAI]

  5. claude-cookbooks [github repo]

  6. 15 AI Prompts To Improve Your Requirements Gathering Process

Methods

  1. Chain-of-Verification Reduces Hallucination in Large Language Models [arxiv 20 Sep 2023]

  2. Beyond Free-Form Text: How Constrained Decoding is Reshaping Structured Generation in LLMs [Sep 7, 2025]

  3. Structured model outputs

Requirements Engineering

  1. AI for Requirements Engineering: Industry Adoption and Practitioner Perspectives [Submitted on 05 Nov 2025]

  2. Large Language Models (LLMs) for Requirements Engineering (RE): A Systematic Literature Review [Submitted on 14 Sep 2025]

  3. Exploring the Use of LLMs for Requirements Specification in an IT Consulting Company [Submitted on 25 Jul 2025]

  4. Evaluating Large Language Models for the Automated Generation of Software Requirements [First Online: 12 July 2025]

  5. Towards Conversational Requirements Engineering: Detecting Defects in Requirements Using Large Language Models [First Online: 03 July 2025]

  6. LLMREI: Automating Requirements Elicitation Interviews with LLMs [Submitted on 3 Jul 2025]

  7. Using Large Language Models to Develop Requirements Elicitation Skills [09 Apr 2025]

  8. Research directions for using LLM in software requirement engineering: a systematic review [21 March 2025]

  9. Large Language Model for Requirements Engineering: A Systematic Literature Review [December 2024]

  10. Challenges in applying large language models to requirements engineering tasks [18 September 2024]

  11. The Return of Formal Requirements Engineering in the Era of Large Language Models [30 March 2024]

Business Analysis - Requirements Gathering

  1. 5 AI Tools for Business Analysts for Better Requirements Management [copilot4devops]

  2. The Coming AI Revolution In Requirements Gathering [forbes]

  3. 13 Best Prompt Engineering Tools to Boost Your AI Workflows [openxcell]

  4. Top 10 AI Tools for Requirements Gathering Success in 2025 [clickup]

Learning

  1. Using Large Language Models to Develop Requirements Elicitation Skills [09 Apr 2025]

Security

  1. OWASP Top-10 for LLMs (2025)

  2. Checkmarx — LLM Security Guide

  3. Confident AI — LLM Security Best Practices

  4. Prompt Injection Attacks [OWASP]

References
  1. Puchleitner, T., Lubos, S., Felfernig, A., & Garber, D. (2025). Evaluating Large Language Models for the Automated Generation of Software Requirements. In Advances and Trends in Artificial Intelligence. Theory and Applications (pp. 443–450). Springer Nature Singapore. 10.1007/978-981-96-8892-0_37
  2. Güttinger, J., Fenger, J.-N., Kirchmeier, T., & Legat, C. (2025). Towards Conversational Requirements Engineering: Detecting Defects in Requirements Using Large Language Models. In Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future (pp. 17–28). Springer Nature Switzerland. 10.1007/978-3-031-85316-6_2
  3. Hemmat, A., Sharbaf, M., Kolahdouz-Rahimi, S., Lano, K., & Tehrani, S. Y. (2025). Research directions for using LLM in software requirement engineering: a systematic review. Frontiers in Computer Science, 7. 10.3389/fcomp.2025.1519437
  4. Spoletini, P., & Ferrari, A. (2024). The Return of Formal Requirements Engineering in the Era of Large Language Models. In Requirements Engineering: Foundation for Software Quality (pp. 344–353). Springer Nature Switzerland. 10.1007/978-3-031-57327-9_22
AI Engineering Book from SovIAR
Release Notes
Intro
AI Systems Grounding in Computing Disciplines