Has the recent waves in the democratization of software development (nocode / vibe coding) got you thinking about the implications for strategy and entrepreneurship? Consider submitting your work to this upcoming special issue:

Software Without Developers: Implications of No-Code, Low-Code, and AI Coding for Entrepreneurship

The Journal of Business Venturing Design invites submissions for a special issue focusing on the implications for entrepreneurship of technologies that enable software creation without traditional developers or computer programming expertise.

The character of much entrepreneurship practice has been affected by several waves of technological development. These include the increasing availability of Application Programming Interfaces (APIs) and user-friendly visual interfaces to combine existing software tools, full-fledged no-code/low-code (NC/LC) software development tools, the ability of Large Language Models (LLMs) to generate and modify code, and the integration of no-code interfaces with generative AI capabilities - both within existing software and in new applications.

Together, these technological developments are reshaping the entrepreneurial landscape by dramatically reducing the technical hurdles involved in creating sophisticated software applications (Dushnitsky & Stroube, 2021; Hurlburt, 2021; Kostis et al., 2024; P. Simon, 2022). This democratization of software development allows entrepreneurs to significantly reduce barriers to entry by enabling faster building, testing, evaluating, and changing of business ideas (Carroll et al., 2024). The combinatorial possibilities afforded by these tools and interfaces, not only unlock business creativity but also helps simplify the process of establishing real businesses.

However, reliance on NC/LC and AI coding tools also introduces new types of platform risk (Jean et al., 2020) and technical debt (Kruchten et al., 2012). This highlights the need to better understand how to manage the short- and long-term trade-offs that come with reliance on these tools, especially relative to more traditional software and business design (Luo et al., 2021).

Given their transformative potential, growing popularity, and apparent influence on entrepreneurship, the Journal of Business Venturing Design invites manuscripts that explore this development through conceptual work, descriptive/explanatory studies, as well as more prescriptive design science research.

Guest editors:

Mohammad Keyhani, Haskayne School of Business, University of Calgary, Canada

Jonny Holmström, Swedish Center for Digital Innovation, Umeå University, Sweden

Yashar Mansoori, Chalmers University of Technology, Sweden

Henrik Berglund, Chalmers University of Technology, Sweden (Editor, Journal of Business Venturing Design)

Special issue information:

BACKGROUND

No-code/low-code and AI coding tools empower individuals and businesses to develop applications and digital solutions with little or no coding knowledge, enabling rapid prototyping and deployment. These developments have significant implications for entrepreneurship, as they have the potential to reduce the need for technical software expertise, lower entry barriers, and accelerate the innovation process (Heuschkel, 2023; Keyhani, 2022). The rise of such software without developers has the potential to democratize entrepreneurship, allowing non-technical founders and innovators to bring their ideas to life and compete with established players (Brühl et al., 2023). In the context of intrapreneurship and employee-driven innovators, these technologies are also fuelling the emergence of citizen developers who can develop and implement digital solutions without relying on central IT departments (Carroll et al., 2021; P. Simon, 2022).

Several technological advances have built the foundations for the recent surge in software democratization. First, the increasing availability of Application Programming Interfaces (APIs) for various software tools as well as platforms explicitly designed to help non-technical users connect such tools via APIs (e.g., Zapier.com and Make.com). This has given rise to a modular 'API economy' (Simon, 2021), where non-technical users can also design businesses by combining tools for product and service development, hosting, distribution, marketing, customer service, payments etc.

Second, a new wave of all-in-one platforms (e.g., Bubble.io and Adalo.com) that integrate design and UX, logic and functionality, and data layers into single integrated platforms, enables non-technical users develop and deploy fully functional web and mobile applications. Such platforms have made it simpler for entrepreneurs to launch businesses based on functional software by reducing the need for technical capabilities (ElBatanony & Succi, 2021a, 2021b).

Third, an increasing number of generative software platforms (Keyhani, 2025; Keyhani & Hastings, 2021; Zittrain, 2008) offer extensive functionalities through a blend of internal development and their the ecosystems of plugins and templates that are developed by external contributor communities (e.g., Notion.so, Coda.io, Airtable.com, Google Sheets, and Webflow.com). As a result, many types of software application can now be built using combinations of tools, plugins, and API linkages, further lowering the barriers to software and venture development.

Fourth, generative AI software development tools (e.g., Cursor, Vercel, Memex, Replit, and GitHub Copilot) have made it dramatically easier to generate and modify code without advanced programming knowledge. AI-assisted pair programming has been reported to increase the productivity of some software developers by more than 50% (Peng et al., 2023) and autonomous agent tools-such as Devin, Replit Agent or Lovable.dev (formerly GPT Engineer)-combine multiple generative AI agents to achieve unprecedented levels of automation in software development (cf., Wu et al., 2023). AI coding tools vary in their level of autonomy or "agentic" behavior and that presents different affordances and constraints (Händler, 2023; Lier & Muñoz-Gil, 2024). Such technological developments enable entrepreneurs in new ways and at a rapid pace (Giuggioli & Pellegrini, 2023). Furthermore, no-code development tools like WeWeb, Noodl and FlutterFlow integrate the capabilities of generative AI coding co-pilots with the visual programming tools of no-code development platforms. This follows another trend in no-code tools that allow non-technical users to create and deploy machine learning models (Sundberg & Holmström, 2023).

It should be noted that studies of professional software development with NC/LC and AI coding tools have identified various challenges and weaknesses across different stages of the development process (cf. Luo et al., 2021). However, from an entrepreneurial perspective, many of these drawbacks may be acceptable trade-offs in cases when speed of experimentation is important (Jamshidi et al., 2025; Keyhani & Jamshidi, 2025; Thomke, 1998). Depending on things such as stage of development and entrepreneurial goals, tool can be more or less suitable. Still, we lack systematic analyses of when and under what conditions risks related to platform lock-in, technical debt etc are worth taking for entrepreneurs. Many entrepreneurs also hesitate to adopt these rapidly developing technologies, fearing that a better tool may be just around the corner (Kennedy, 2006; Mollick, 2024).

As software without developers becomes more prevalent, it is important to understand its impact on entrepreneurial entry, practices, processes, outcomes, and the broader ecosystem. As the topics below illustrate, this emerging phenomenon clearly offers rich opportunities for research that is both theoretically interesting and practically valueable. These questions serve as illustrative examples rather than constraints on potential submissions, and we welcome a wide range of perspectives and approaches that contribute to advancing knowledge in this area.

ILLUSTRATIVE TOPICS

Democratization of Entrepreneurship

• How do NC/LC and AI coding tools reduce barriers to entrepreneurship, and to what extent do they foster greater diversity (of expertise) and inclusion (of perspectives) in software entrepreneurship?
• How do they alter the skill mix, size, and composition of entrepreneurial teams?
• How do these tools impact entrepreneurial initiatives undertaken by citizen developers and individual contributors in existing organizations?

Theories and Practices of Entrepreneurial Design

• How do NC/LC and AI coding tools affect processes of entrepreneurial experimentation and decision-making (cf. Thomke, 1998; Ries 2011, Camuffo et al. 2020, Coali et al. 2024, Paust et al. 2025) for example by enabling faster, cheaper, and more iterative prototyping?
• How do these tools impact processes of entrepreneurial transformation and co-creation (cf. Sarasvathy, 2001, 2021; Baker and Nelson, 2005; Bianchi and Verganti 2021) for example by enabling wider participation in software and business design?
• How do they influence various stages of the startup lifecycle-from ideation to scaling-including specific activities such as fundraising, prototype development, and pivoting?
• How do they influence different types of ventures-such as technology-based startups, pure software companies, or more traditional small businesses-and how might these effects vary based on organizational context and industry specifics?
• What are the implications of introducing AI with varying degrees of agentic autonomy into entrepreneurship and how might this affect venture development?

Team Composition and Organization

• How do NC/LC and AI coding tools change the marginal benefits of different entrepreneurial skills?
• How do these tools affect team composition (e.g., technical vs. non-technical founders)?
• How are organizational structures and workflows affected by these tools?
• How do they influence team dynamics, skill requirements, and founder-investor relationships?
• How do they impact the balance of power within entrepreneurial teams?

Entrepreneurial Strategy and Industry Evolution

• How do NC/LC and AI coding tools affect the competitive landscape for software startups?
• How do they impact barriers to entry in different industries and areas?
• Do they bring about the emergence of new business models, value chains, and ecosystems? May these differ from traditional software ventures?
• How do investors perceive startups that rely on NC/LC and AI coding platforms, and how does this affect their investment decisions?

Implementation and Best Practices

• What are the emerging best practices for using NC/LC and AI coding tools in entrepreneurship, and what are the trade-offs (e.g., cost, speed, flexibility, platform lock-in) relative to traditional software development?
• How do entrepreneurs view and adopt these tools in practice and how are risks and trade-offs assessed?
• How can design science researchers and educators develop robust entrepreneurial tools and frameworks despite rapid technological change?
• Given the short shelf-life of these tools, what are suitable formats and levels of abstraction for managerial theories and frameworks?

Entrepreneurial Education and Skills Development

• What skills and competencies will entrepreneurs need to benefit from NC/LC and/or AI coding, and what are effective learning or training practices for gaining these?
• Given the lowered technical skills needed, should NC/LC and AI coding be taught as a dedicated topic in entrepreneurship programs?
• How should business schools, incubators, and other educational entities adapt to these changes in digital entrepreneurship? What new skills and pedagogies are required?

Manuscript submission information:

Submissions should be prepared using the JBVD Guide for Authors:

https://www.elsevier.com/journals/journal-of-business-venturing-design/2667-2774/guide-for-authors

Papers will be reviewed according to the JBVD double-blind review process.

The deadline for full manuscript submission is October 1, 2025,  although we encourage earlier submissions.

We aim for a very speedy review process and accepted manuscripts will be published online on a rolling basis.

Manuscripts should be submitted through the JBVD online submission process: https://www.editorialmanager.com/jbvd/default2.aspx

Please select article type name VSI: Software Without Developers while making the submission.

Informal enquiries relating to the Special Issue, proposed topics, and potential fit with the Special Issue objectives are welcomed.

References:

Baker, T., & Nelson, R. E. (2005). Creating something from nothing:Resource construction through entrepreneurial bricolage. Administrative sciencequarterly, 50(3), 329-366.

Bianchi, M., & Verganti, R. (2021). Entrepreneurs as designers ofproblems worth solving. Journal of Business Venturing Design, 1(1-2), 100006.

Brühl, S.,Bernsteiner, R., Ploder, C., Dilger, T., & Spiess, T. (2023). The Use ofNo-Code Platforms in Startups. In L. Uden & I.-H. Ting (Eds.), KnowledgeManagement in Organisations (pp. 289–301). Springer NatureSwitzerland. https://doi.org/10.1007/978-3-031-34045-1_24

Camuffo, A.,Cordova, A., Gambardella, A., & Spina, C. (2020). A scientificapproach to entrepreneurial decision making: Evidence from a randomized controltrial. Management Science, 66(2), 564-586.

Carroll, N., Holmström, J., &Matook, S. (2024). Special Issue Editorial: Transforming Business with Low-Codeand No-Code. MIS Quarterly Executive, 23(3).https://aisel.aisnet.org/misqe/vol23/iss3/2

Carroll, N.,Móráin, L. Ó., Garrett, D., & Jamnadass, A. (2021). The importanceof citizen development for digital transformation. Cutter IT Journal, 34(3),5–9.

Dushnitsky, G., & Stroube, B. K.(2021). Low-code entrepreneurship: Shopify and the alternative path to growth. Journalof Business Venturing Insights, 16, e00251.https://doi.org/10.1016/j.jbvi.2021.e00251

ElBatanony, A., & Succi, G.(2021a). The pareto distribution of software features and no-code. Proceedingsof the 1st ACM SIGPLAN International Workshop on Beyond Code: No Code,18–22. https://doi.org/10.1145/3486949.3486964

ElBatanony, A., & Succi, G.(2021b). Towards the no-code era: A vision and plan for the future of softwaredevelopment. Proceedings of the 1st ACM SIGPLAN International Workshop onBeyond Code: No Code, 29–35. https://doi.org/10.1145/3486949.3486965

Giuggioli, G.,& Pellegrini, M. M. (2023). Artificial intelligence as an enabler forentrepreneurs: A systematic literature review and an agenda for futureresearch. International Journal of Entrepreneurial Behavior & Research,29(4), 816–837. https://doi.org/10.1108/IJEBR-05-2021-0426

Händler, T. (2023). BalancingAutonomy and Alignment: A Multi-Dimensional Taxonomy for Autonomous LLM-poweredMulti-Agent Architectures (arXiv:2310.03659). arXiv.https://doi.org/10.48550/arXiv.2310.03659

Heuschkel, S. (2023). The impactof no-code on digital product development (arXiv:2307.16717). arXiv.https://doi.org/10.48550/arXiv.2307.16717

Hurlburt, G. (2021). Low-Code,No-Code, What's Under the Hood? IT Professional, 23(6), 4–7. https://doi.org/10.1109/MITP.2021.3123415

Jamshidi, Z., Keyhani, M., &Choi, K. J. (2025). The Value of Random Experimentation.

Jean, R.-J."Bryan," Kim, D., & Cavusgil, E. (2020). Antecedents and outcomes of digitalplatform risk for international new ventures' internationalization. Journalof World Business, 55(1), 101021.https://doi.org/10.1016/j.jwb.2019.101021

Kennedy, A. N. (2006). InterstellarTravel: The Wait Calculation and the Incentive Trap of Growth. Journal ofthe British Interplanetary Society, 59(7), 239–246.

Keyhani, M. (2022). Startup Stacks:Understanding the New Landscape of Digital Entrepreneurship Technology. In M.Keyhani, T. Kollmann, Sorgner, Alina, A. Ashjari, & C. E. Hull (Eds.), Handbookof Digital Entrepreneurship (pp. 140–160). Edward Elgar.

Keyhani, M. (2025). TheGenerativity Advantage: Unpredicted Innovation at Scale. De Gruyter.

Keyhani, M., & Hastings, H.(2021). Implications of generativity for entrepreneurship and strategy. KeyhaniM and Hastings H (2021) Implications of Generativity for Entrepreneurship andStrategy. ERENET Profile, 16(1), 3–12.

Keyhani, M., & Jamshidi, Z.(2025). Outliers Emerge from Experimentation.

Kostis, A.,Lidström, J., Nair, S., & Holmström, J. (2024). Too Much AIHype, Too Little Emphasis on Learning? Entrepreneurs Designing Business ModelsThrough Learning-by-Conversing With Generative AI. IEEE Transactions onEngineering Management, 71, 15278–15291.https://doi.org/10.1109/TEM.2024.3484750

Kruchten, P., Nord, R. L., &Ozkaya, I. (2012). Technical Debt: From Metaphor to Theory and Practice. IEEESoftware, 29(6), 18–21. https://doi.org/10.1109/MS.2012.167

Leonardi, P. M. (2011). Whenflexible routines meet flexible technologies: Affordance, constraint, and theimbrication of human and material agencies. MIS Quarterly, 147–167.

Lier, M. van, & Muñoz-Gil, G.(2024). Artificial Agency and Large Language Models (arXiv:2407.16190).arXiv. https://doi.org/10.48550/arXiv.2407.16190

Luo, Y., Liang, P., Wang, C.,Shahin, M., & Zhan, J. (2021). Characteristics and Challenges of Low-CodeDevelopment: The Practitioners' Perspective. Proceedings of the 15th ACM /IEEE International Symposium on Empirical Software Engineering and Measurement(ESEM), 1–11. https://doi.org/10.1145/3475716.3475782

March, J. G. (1991). Exploration andExploitation in Organizational Learning. Organization Science, 2(1),71–87. https://doi.org/10.1287/orsc.2.1.71

Mollick, E. (2024). Co-Intelligence:Living and Working with AI. Portfolio.

Paust, S., Thrane, C., & Korsgaard, S. (2025). An integrativeliterature review of Prototyping in management research: definition andresearch agenda. Journal of Business Venturing Design, 100026.

Peng, S., Kalliamvakou, E., Cihon,P., & Demirer, M. (2023). The Impact of AI on Developer Productivity:Evidence from GitHub Copilot (arXiv:2302.06590). arXiv.https://doi.org/10.48550/arXiv.2302.06590

Ries, E. (2011). The leanstartup: How today's entrepreneurs use continuous innovation to createradically successful businesses (1st ed). Crown Business.

Sarasvathy, S. D. (2001). Causationand effectuation: Toward a theoretical shift from economic inevitability toentrepreneurial contingency. Academy of Management Review, 26(2),243–263.

Sarasvathy, S. D. (2021). Ask for it: A practice based theory ofventuring design. Journal of Business Venturing Design, 1(1-2), 100008.

Simon, J. P. (2021). APIs, the glueunder the hood. Looking for the "API economy." Digital Policy, Regulationand Governance, 23(5), 489–508.https://doi.org/10.1108/DPRG-10-2020-0147

Simon, P. (2022). Low-Code/No-Code:Citizen Developers and the Surprising Future of Business Applications.Racket Publishing.

Coali, A., Novelli, E., Sirigiri, A., & Spina, C. (2024). Ascientific approach to decision-making: Key tools and design principles.Journal of Business Venturing Design, 3, 100023.

Sundberg, L., & Holmström, J.(2023). Democratizing artificial intelligence: How no-code AI can leveragemachine learning operations. Business Horizons, 66(6), 777–788.https://doi.org/10.1016/j.bushor.2023.04.003

Thomke, S. H. (1998). ManagingExperimentation in the Design of New Products. Management Science, 44(6),743–762. https://doi.org/10.1287/mnsc.44.6.743

Wu, Q., Bansal, G., Zhang, J., Wu,Y., Li, B., Zhu, E., Jiang, L., Zhang, X., Zhang, S., Liu, J., Awadallah, A.H., White, R. W., Burger, D., & Wang, C. (2023). AutoGen: EnablingNext-Gen LLM Applications via Multi-Agent Conversation (arXiv:2308.08155).arXiv. https://doi.org/10.48550/arXiv.2308.08155

Zittrain, J. (2008). The futureof the internet: And how to stop it. Yale University Press.

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Mohammad Keyhani
Associate Professor
University of Calgary
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