Knowledge workers solve problems, make decisions, and learn continuously—yet much of the "knowledge" they produce in the form of personal notes and sense-making artifacts largely remains invisible to the public, as it is usually kept personal. Notes are taken, files are stored, and insights accumulated, but it often remains unclear how work done in the past translates into competences in future that others can understand, trust, or meaningfully evaluate. This session shows how Tools for Thought—in this case [Obsidian.md](http://obsidian.md/)—can help bridge this gap. Rather than focusing on tools or workflows for their own sake, we address what knowledge workers actually need: ways to capture work-related outcomes, connect them coherently over time, and present them in forms that make competences visible and credible. We demonstrate how connected note environments can support four practical moves: - Capturing key decisions, insights, and work artifacts as they occur - Reflectively connecting these materials so patterns of practice and capability emerge over time - Validating skill claims with concrete examples instead of vague self-descriptions - Presenting knowledge, skills and experience in ways that others can follow and assess Using personal examples from research, teaching, and project-based work, we show how Tools for Thought can function as a personal competence record: a living resource that supports reflection, collaboration, and professional communication—without turning knowledge work into bureaucratic reporting. Format: Talk with short examples and discussion **References (Selection)** - Dilger, B. & Strate, M. (2025). Brückenbau zwischen individuellen Kompetenzen, Weiterbildungsangeboten und Anforderungen auf dem Arbeitsmarkt durch KI-gestützte Kompetenzportfolios in der beruflichen Weiterbildung. bwp@ Berufs- und Wirtschaftspädagogik – online, 48, 1–19. https://www.bwpat.de/ausgabe48/dilger_strate_bwpat48.pdf - Hartig, J., Klieme, E. (2006). Kompetenz und Kompetenzdiagnostik. In: Schweizer, K. (eds) Leistung und Leistungsdiagnostik. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33020-8_9 - Siegel, S. T., & Lohner, D. (2024). Wissensmanagement von Lehrenden mit „Digital Tools for Thought“: Potenziale, Grenzen und Einsatzmöglichkeiten. Neues Handbuch Hochschullehre (NHHL), 114, 1–20. - Siegel, S. T., Lohner, D., & Arnold, M. (2025). Reimagining Teaching Portfolios Through Personal Knowledge Management with Digital Tools for Thought. Zeitschrift für Hochschulentwicklung, 20(3). https://doi.org/10.21240/zfhe/20-3/11

Can changes in political context shift the weight individuals place on non-pecuniary versus pecuniary motives in financial decision-making? We examine this question using pre-registered surveys and incentivized investment decisions surrounding the 2024 U.S. presidential election. Following Trump’s victory, investors reduced average green investments due to worse financial expectations. However, investors who strongly disapproved of his climate policies increased their green allocations, emphasizing climate considerations over financial ones. These “contrarian” investors appear motivated to offset perceived policy shortcomings. Real-world ETF flows corroborate this pattern. The findings have implications for understanding and modeling values-based investment behavior.

This article examines the growing number of Russian students pursuing higher education in China. It highlights how China’s open-door policies, global ambitions, and modern academic environment attract talented students dissatisfied with Russia’s outdated educational system and rigid corporate culture. While this inflow of talent benefits China, Russia faces the challenge of an emerging academic brain drain. Russia must reflect on what is driving this problem and take decisive action to mitigate its effects.

Purpose While artificial intelligence (AI) is a hot topic in public debate and academic discourse, most research is still conceptual with only a few insights into how AI is used in entrepreneurship practice. This study explores empirically how and with what effect early-stage IT startups utilize AI tools, with the general aim of getting a better understanding of how a new technology is adopted in the entrepreneurial process. Design/methodology/approach Conceptually, our study builds on the External Enabler Framework to structure the analysis. Following a mixed-method approach, we first analyze qualitative data on how AI tools are used in early-stage startups and identify the mechanisms that are facilitated. In a quantitative study, we test the effect of two identified efficiency mechanisms. Specifically, using Crunchbase data, we compare startups before and after the introduction of ChatGPT-3, focusing on (1) the number of employees and (2) the time to achieve seed funding. Findings Our qualitative study indicates that startups use AI mainly in the form of GenAI tools to streamline the process of venture creation, saving time and resources, and less frequently for directly shaping the offered product or the venture itself, presumably resulting from the distinct demands of different applications. While AI is considered important, it has so far not replaced human agency. Building on these results, the quantitative study confirms that startups with access to GenAI tools require fewer employees and achieve critical milestones faster, specifically securing seed funding. Research limitations/implications Our qualitative study is based on interviews with early-stage IT startups applying AI tools. In the quantitative study, it is challenging to distinguish between AI-infused efficiency effects and investor-related supply-side effects, resulting from the hype surrounding AI. Future research is needed to explore AI's broader influence on entrepreneurial processes. Originality/value Our study is one of the first to uncover the use of AI tools in early-stage startups, allowing entrepreneurs to compare with others and enabling policymakers to identify changes in the startup process, with implications for policy design. For academics, our study contributes to the discussion around AI and agency in the entrepreneurial process and provides insights into the applicability of the External Enabler framework.

If trade diplomats thought they knew one thing, it was how to cut industrial tariffs. Yet the Doha deadlock rests squarely on the inability to compromise on industrial tariff cuts. This column says that the arguments made for higher levels of ambition don't stand up to much scrutiny and should not be allowed to provide a basis for a continuing impasse.