Across higher education and industry, rapid advances in generative AI are reshaping writing-intensive work. Forecasts from the International Monetary Fund (Georgieva, 2024) and the World Economic Forum (WEF, 2025) suggest that a substantial share of knowledge-intensive and information-processing work will be affected through automation, augmentation, and task redesign. For technical and professional communication (TPC) programs, this raises a concrete program-level question: if AI can draft, revise, summarize, translate, and generate documentation at scale, where are our jobs, and what are we preparing students to do?

As a field, TPC has long aligned itself with emerging tools, workplace technologies, and evolving professional genres. Many TPC programs now feel pressure to move quickly, to integrate AI tools into courses, and to demonstrate curricular relevance. However, AI technologies are developing at such speed that tools considered cutting-edge a few months ago may quickly become obsolete. It is neither necessary nor practical for TPC programs to constantly redesign curricula around the newest AI tools or technologies, as rapid adoption of new technology alone never guarantees thorough preparation for our students’ long-term careers. This is nothing new for many of us – it’s why we spend so much time teaching theory in practical classes such as design and editing. Photoshop, for example, updates so regularly that teaching a specific tool’s use or location might be problematic; in 2025, Adobe updated Photoshop 13 times (Adobe Photoshop on Desktop Release Notes, 2026). To deal with an ever-changing world, students need to learn what to look for, what to question, what to revise, and how to adapt.

The more productive question, therefore, is not how our programs and curriculum can integrate AI, but what remains durable and valuable training in TPC programs when tools and technical ecosystems change so quickly, when we, individually, are suffering from “AI fatigue” (Dibia, 2025). What should endure in TPC education when technologies are unstable but professional responsibility is not? This proposed special issue, “Durable Skills for the AI-Altered Workplace: Rhetorical Agency, Human Judgment, and Ethical Care in TPC Programs,” centers that question.

The Contemporary Workplace

To ground this question in the contemporary workplace, we can look to emerging signals from the AI industry itself. Lazar Jovanovic, despite having no coding background, now works at the AI software company Lovable as a vibe coding engineer (Rachitsky, 2026). Rather than writing traditional code, he spends much of his time planning projects, defining goals, clarifying requirements for AI systems, and directing AI through carefully constructed prompts. In describing what enables success in the AI era, he emphasizes not technical syntax or traditional programming expertise, but clarity and planning, strong documentation practices, emotional intelligence and design judgment, communication skills, and evaluation. This emphasis on clarity, judgment, and structured intent is echoed across leading AI organizations. AI leaders such as Sam Altman (CEO, OpenAI, 2025), Andrej Karpathy (OpenAI cofounder, 2025), and Jensen Huang (CEO, NVIDIA, 2023) similarly stress that advantage shifts toward asking the right questions, maintaining a tight generation and verification loop with human oversight, and using natural-language direction to communicate intent and exercise judgment.

These are not novel AI skills. They are the very capacities that TPC programs have long emphasized and cultivated. As AI lowers the barriers to producing content, including writing, design, video, music, and even code, the source of value shifts toward human agency, evaluation, judgment, taste, and responsible ethical decision-making. This moment for us, therefore, is about re-centering and explicitly articulating the durable skills that TPC programs already cultivate, and asking how those skills should be taught, practiced, and assessed in different new AI-mediated scenarios.

Durable Skills

In this special issue, we use durability to refer to capacities that persist across technological shifts and remain valuable even as tools, platforms, and workflows evolve. It’s a much-used term as it relates to skillsets, particularly in educational marketing. The education-to-workforce focused non-profit America Succeeds, for example, identifies “durable skills” as “skills like critical thinking, communication, collaboration, and creativity – as well as character skills like fortitude, growth mindset, and leadership,” noting that such skills are “in demand for jobs across the workforce regardless of educational attainment level, industry, sector, or geography” (Bridging the Gap: A Case Study on Skillsline’s Innovative Approach for Developing Durable Skills in the Workforce, 2026). In the for-profit sector, the Winward Academy, a private online learning and test-preparation group focused on middle- and high-school students, cites America Succeeds as the basis for their focus on durable skills, and the Minerva Project, marketed as a data-driven alternative to traditional higher education, argues that durable skills are critical in today’s workforce, noting that they are often absent, or not clearly identified, in most curricula (Herget & El-Azar, 2023). In our own literature, Kirk St. Amant and S. Scott Graham guest edited an issue of Technical Communication Quarterly arguing the importance of durability and portability in our research (Molloy, 2019; Moriarty et al., 2019; St.Amant & Graham, 2019), and academics have not been shy in noting the value of what Kim et al. refer to as “durable competencies” across complex contexts (2025). Despite the prevalence of the idea of durability, and however we specifically define the durability of our skillsets, an increasing awareness of the value of transferable, multifunctional abilities is important. We need to be able to identify our durable skills.

Agency, Care, and Judgment

This special issue builds on these conversations by asking what durable skills look like in actual TPC programs in the AI era. We frame this issue around the following three anchor concepts that are both teachable and assessable across TPC curricula:

● Rhetorical agency: the ability to interpret context, recognize genres (Miller, 1984), identify stakeholders, analyze audiences (Ross, 2013), define purposes, make principled choices, and articulate those choices in ways that meet organizational, user, and community needs.

● Human-centeredness and ethical care: the ability to relate, empathize, and connect technological systems to the lived experiences of real users (Rose, 2016; Zachry & Spyridakis, 2016), as well as the willingness to question expedient automation and make decisions that protect accessibility, equity, trust, and human well-being (Katz, 1992; Walton et al., 2019), especially when institutional and workplace pressures reward speed.

● Human judgment: the ability to evaluate quality, verify claims, recognize risk, and make accountable decisions in AI-assisted workflows (Parasuraman & Riley, 1997), especially when AI outputs are plausible, fluent, and easily mistaken for sufficient (Reeves & Sylvia, 2024). This includes the capacity to determine what constitutes effective writing, responsible design, and appropriate communication in specific contexts, and to operationalize that judgment through human-in-the-loop practices (Getto et al., 2025), as part of a broader AI literacy that goes beyond tool use to critical evaluation and responsibility (Davis et al., 2026).

We welcome submissions from researchers, instructors, program administrators, and industry or internship partners whose work helps us understand how TPC programs are responding to AI-altered workplaces.

This special issue invites submissions that address questions such as:

● How are TPC programs defining durable capacities for AI-altered workplaces, and how are these capacities reflected across curricula and program design?

● How are TPC programs redefining career preparation in AI-altered workplaces, and how do programs communicate that value to support recruitment, retention, and student advising?

● What counts as evidence of learning in AI-altered writing-intensive work, and how might programs design assessment practices that foreground evaluation, verification, and accountability?

● How are TPC programs helping students construct ethical frameworks they will be able to apply in an ever-changing technological landscape?

● What program-level policies or governance practices are emerging around responsible AI use, and how might programs implement workable approaches across courses and instructors?

● What is the role of human-centered methods, including UX and accessibility, in sustaining ethical and effective communication in AI-mediated work?

● What is the role of industry partners and internship sites in shaping TPC program responses to AI-altered workplaces, and how might programs adapt experiential learning to these changing conditions?

● What new courses, course modules, or curricular pathways are TPC programs developing in response to AI-altered workplaces, and how do these designs align with program outcomes and student career preparation?

Full Manuscript Submissions

We invite full manuscript submissions including research articles, program showcases, curriculum showcases, and commentaries addressing durable skills in technical and professional communication via agency, care, and judgment.

Submissions should align with Programmatic Perspectives general guidelines: https://programmaticperspectives.cptsc.org/index.php/jpp/about/submissions.

Authors should submit full manuscripts directly through the Programmatic Perspectives submission system: https://programmaticperspectives.cptsc.org/index.php/jpp/information/authors. Authors must register with the journal before submitting or, if already registered, log in and begin the submission process.

Please clearly indicate at the top of your submission that this is a submission for the durable skills special issue.

If a submitted manuscript is deemed not appropriate for, or not sufficiently related to, the special issue, it may still be considered for the journal’s regular review process.

We welcome questions about the special issue. If you have questions about fit, topic, or submission, please contact Yingying Tang at yxt045.

Timeline

– Full manuscripts due: August 15

– Decisions to authors: Anticipated September

– Anticipated publication: Late December or early January

References

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AI means everyone can now be a programmer, Nvidia chief says. (2023, May 29). Reuters. https://www.reuters.com/technology/ai-means-everyone-can-now-be-programmer-nvidia-chief-says-2023-05-29/

Bridging the gap: A case study on Skillsline’s innovative approach for developing durable skills in the workforce. (2026). America Succeeds. http://www.durableskills.org

Davis, K., Tham, J., Stambler, D. M., Jiang, J., Campbell, J., Verhulsdonck, G., & Hocutt, D. (2026). What Do We Mean By “AI Literacy”? Tensions in Current Institutional Guidelines and Recommendations for a Slow, Reflective Future. Programmatic Perspectives, 1(1).

Dibia, V. (2025). AI fatigue: Reflections on the human side of AI’s rapid advancement. Communications of the ACM, 68(12), 35–36.

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Herget, A., & El-Azar, D. (2023). Teaching durable skills: How universities can intentionally build competencies. Minerva Project. https://humancapabilityinitiative.org/wp-content/uploads/2024/02/MInervaProject_TeachingDurableSkills-1.pdf

Katz, S. B. (1992). The ethic of expediency: Classical rhetoric, technology, and the Holocaust. College English, 54(3), 255–275.

Kim, A.-S., Jones, K., Lang, G., Raider, H. J., Sheikh, A., & Simione, K. (2025). Beyond Technical Skills: Uncovering Durable Competencies through Multi-Level Stakeholder Analysis. Information Systems Education Journal, 23(6), 4–18.

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Molloy, C. (2019). Durable, Portable Research through Partnerships with Interdisciplinary Advocacy Groups, Specific Research Topics, and Larger Data Sets. Technical Communication Quarterly, 28(2), 165–176. https://doi.org/10.1080/10572252.2019.1588375

Moriarty, D., Núñez De Villavicencio, P., Black, L. A., Bustos, M., Cai, H., Mehlenbacher, B., & Mehlenbacher, A. R. (2019). Durable Research, Portable Findings: Rhetorical Methods in Case Study Research. Technical Communication Quarterly, 28(2), 124–136. https://doi.org/10.1080/10572252.2019.1588376

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Reeves, C., & Sylvia, J. J. I. (2024). Generative AI in technical communication: A review of research from 2023 to 2024. Journal of Technical Writing and Communication, 54(4), 439–462.

Rose, E. J. (2016). Design as advocacy: Using a human-centered approach to investigate the needs of vulnerable populations. Journal of Technical Writing and Communication, 46(4), 427–445.

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Sam Altman on the future of AI and humanity. (2025). Apple Podcasts. https://podcasts.apple.com/us/podcast/sam-altman-on-the-future-of-ai-and-humanity/id1554567118?i=1000682967449

Singju, P. (2025, June 20). Andrej Karpathy: Software Is Changing (Again). The Singju Post. https://singjupost.com/andrej-karpathy-software-is-changing-again/

St.Amant, K., & Graham, S. S. (2019). Research that resonates: A perspective on durable and portable approaches to scholarship in technical communication and rhetoric of science. Technical Communication Quarterly, 28(2), 99–111. https://doi.org/10.1080/10572252.2019.1591118

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CFP_Special Issue on Durable Skills for the AI-Altered Workplace.pdf