Development in times of hype: How freelancers explore Generative AI?
Not on the map. Why?
Abstract (arXiv)
The rise of generative AI has led many companies to hire freelancers to harness its potential. However, this technology presents unique challenges to developers who have not previously engaged with it. Freelancers may find these challenges daunting due to the absence of organizational support and their reliance on positive client feedback. In a study involving 52 freelance developers, we identified multiple challenges associated with developing solutions based on generative AI. Freelancers often struggle with aspects they perceive as unique to generative AI such as unpredictability of its output, the occurrence of hallucinations, and the inconsistent effort required due to trial-and-error prompting cycles. Further, the limitations of specific frameworks, such as token limits and long response times, add to the complexity. Hype-related issues, such as inflated client expectations and a rapidly evolving technological ecosystem, further exacerbate the difficulties. To address these issues, we propose Software Engineering for Generative AI (SE4GenAI) and Hype-Induced Software Engineering (HypeSE) as areas where the software engineering community can provide effective guidance. This support is essential for freelancers working with generative AI and other emerging technologies.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jan 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 5.
8 papers.
- 2024Prompts Are Programs Too! Understanding How Developers Build Software Containing Promptscited by 19
- 2024Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Productscited by 11
- 2025Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypescited by 2
- 2026Investigating Writing Professionals' Relationships with Generative AI: How Combined Perceptions of Rivalry and Collaboration Shape Work Practices and Outcomescited by 2
- 2026PrefPO: Pairwise Preference Prompt Optimizationcited by 1
- 2026"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Workcited by 0
- 2026What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBookcited by 0
- 2026Focused on the User, Overlooking the Risks: Security and Privacy Understandings, Practices and Challenges of Independent Chinese AI Agent Developerscited by 0
- 2026Focused on the User, Overlooking the Risks: Security and Privacy Understandings, Practices and Challenges of Independent Chinese AI Agent Developers2 Jun 2026
- 2026What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook8 May 2026
- 2026PrefPO: Pairwise Preference Prompt Optimization13 Mar 2026
- 2026"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Work8 Mar 2026
- 2026Investigating Writing Professionals' Relationships with Generative AI: How Combined Perceptions of Rivalry and Collaboration Shape Work Practices and Outcomes9 Feb 2026
- 2025Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypes6 Oct 2025
- 2024Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products15 Oct 2024
- 2024Prompts Are Programs Too! Understanding How Developers Build Software Containing Prompts19 Sep 2024