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arxiv: 2511.06428 · v2 · pith:KVMHJ3PSnew · submitted 2025-11-09 · 💻 cs.SE · cs.AI

Walking the Tightrope of LLMs for Software Development: A Practitioners' Perspective

Samuel Ferino , Rashina Hoda , John Grundy , Christoph Treude This is my paper

Pith reviewed 2026-05-22 12:41 UTC · model grok-4.3

classification 💻 cs.SE cs.AI
keywords LLMssoftware developmentpractitioner perspectivesbenefits and challengestrade-offsempirical study
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The pith

Software practitioners see LLMs as tools that sustain flow and sharpen mental models but can harm reputation across multiple levels.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines how large language models affect software development by interviewing 22 practitioners over three rounds. It finds benefits including maintained developer flow, better mental models, and increased entrepreneurship, set against challenges such as potential damage to developers' reputation. These are examined at the individual, team, organization, and society scales, along with practical steps to reduce the downsides. The results aim to help team leaders and managers judge when and how to adopt LLMs in their own settings.

Core claim

The study identifies both positive and negative effects of LLMs on software development as reported by practitioners. Benefits include maintaining flow, improving mental models, and fostering entrepreneurship, while challenges encompass risks to reputation. These impacts occur at individual, team, organizational, and societal levels, and the work provides guidance on how to mitigate the challenges through careful management of trade-offs.

What carries the argument

The socio-technical grounded theory analysis of practitioner interviews that uncovers benefits and challenges of LLM use organized by individual, team, organization, and society levels.

If this is right

  • Team leaders can evaluate LLM adoption by weighing flow improvements against reputation concerns in their specific setting.
  • Organizations may need policies to address societal-level effects of widespread LLM use in development.
  • Developers could apply mitigation strategies to preserve their professional standing while gaining productivity aids.
  • Entrepreneurship in software teams might increase if LLM tools are integrated thoughtfully.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Extending beyond the interviews, similar trade-offs between productivity tools and professional risks could arise in other creative or knowledge work domains.
  • The mitigation guidances could be piloted in real teams to see if they effectively reduce challenges like reputation damage.
  • Broader studies might explore how these findings vary with different LLM tools or developer experience levels.

Load-bearing premise

The self-reported experiences of these 22 practitioners are representative enough of the wider software development community to draw general conclusions about LLM impacts.

What would settle it

A large-scale survey of software developers finding that the balance of benefits and challenges differs markedly from what the interviews suggest would challenge the paper's conclusions.

Figures

Figures reproduced from arXiv: 2511.06428 by Christoph Treude, John Grundy, Rashina Hoda, Samuel Ferino.

Figure 1
Figure 1. Figure 1: Study methodology. related activities, which involves exploring the benefits, challenges, limitations, and recommendations shared by software practitioners involved in SE-related activities. Our analysis reveals the following main benefits: (B1) reduced effort due to LLMs as a foundation to boost code development and perceived saving time; (B2) flow experience when LLMs mitigate interruptions and automate … view at source ↗
Figure 2
Figure 2. Figure 2: Emergence of the category “Impact on using LLMs” from raw data → codes → concepts → subcategories → category through constant comparison. provide a snapshot of the LLM features with the intent of improving clarity of the context related to the data collection. We summarise the main features in the supplementary online package [26]. 2.4 Data Analysis One of the ways in which STGT distinguishes itself from t… view at source ↗
Figure 3
Figure 3. Figure 3: Main Benefits of using LLMs at the Individual (Software Practitioner) Level. [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Main Disadvantages of using LLMs at the Individual (Software Practitioner) Level. [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Comparison with related work focused on benefits and disadvantages. The colored bars represent the overlap with existing [PITH_FULL_IMAGE:figures/full_fig_p014_5.png] view at source ↗
read the original abstract

Background: Large Language Models emerged with the potential of provoking a revolution in software development (e.g., automating processes, workforce transformation). Although studies have started to investigate the perceived impact of LLMs for software development, there is a need for empirical studies to comprehend how to balance forward and backward effects of using LLMs. Objective: We investigated how LLMs impact software development and how to manage the impact from a software developer's perspective. Method: We conducted 22 interviews with software practitioners across 3 rounds of data collection and analysis, between October (2024) and September (2025). We employed Socio-Technical Grounded Theory for Data Analysis (STGT4DA) to rigorously analyse interview participants' responses. Results: We identified the benefits (e.g., maintain developer flow, improve developer mental models, and foster entrepreneurship) and challenges (e.g., damage to developers' reputation) of using LLMs at individual, team, organisation, and society levels; as well as actionable guidances into how mitigate these challenges. Conclusion: Critically, we present the trade-offs that software practitioners, teams, and organisations face in working with LLMs. Our findings are particularly useful for software team leaders and IT managers to assess the viability of LLMs within their specific context.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper reports results from a qualitative study of 22 interviews with software practitioners, collected in three iterative rounds between October 2024 and September 2025 and analyzed with Socio-Technical Grounded Theory for Data Analysis (STGT4DA). It claims to identify benefits (maintaining developer flow, improving mental models, fostering entrepreneurship) and challenges (e.g., damage to developers' reputation) of LLM use at individual, team, organizational, and societal levels, together with actionable mitigation guidance and an overall discussion of trade-offs useful to team leaders and IT managers.

Significance. If the methodological gaps are addressed, the work supplies new primary interview data on a timely topic and offers a multi-level framing of LLM impacts that could help practitioners weigh benefits against risks. The explicit attention to both positive and negative effects, plus the practitioner-oriented guidance, distinguishes it from purely technical LLM evaluations.

major comments (3)
  1. [Method] Method section: the sampling strategy, recruitment criteria, and participant demographics are not described in sufficient detail to assess whether the 22 practitioners capture adequate variation in roles, organization sizes, and LLM experience levels. Without this, the extension of themes to team-, organization-, and society-level claims rests on an unverified assumption of representativeness.
  2. [Method] Method section: the interview protocol (including question guides, how prompts evolved across the three rounds, and steps taken to reduce social-desirability or recall bias in self-reported LLM usage) is omitted. This information is load-bearing for evaluating the trustworthiness of the reported benefits, challenges, and mitigations.
  3. [Results] Results / Analysis description: explicit reporting of theoretical saturation criteria, member-checking procedures, or any form of triangulation (e.g., with artifacts or secondary data) is absent. This weakens confidence that the identified themes are not artifacts of the particular cohort or analysis process.
minor comments (2)
  1. [Abstract] Abstract: the date range 'October (2024) and September (2025)' should be clarified or corrected, as it extends into the future relative to typical submission dates.
  2. [Results] Ensure that each actionable guidance in the results is explicitly traced back to one or more interview-derived themes so readers can judge its empirical grounding.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed feedback on our manuscript. The comments highlight key areas where greater methodological transparency will strengthen the paper's contribution. We address each major comment below, indicating the revisions we will make to improve rigor and clarity without altering the core findings.

read point-by-point responses

  1. Referee: [Method] Method section: the sampling strategy, recruitment criteria, and participant demographics are not described in sufficient detail to assess whether the 22 practitioners capture adequate variation in roles, organization sizes, and LLM experience levels. Without this, the extension of themes to team-, organization-, and society-level claims rests on an unverified assumption of representativeness.

    Authors: We agree that additional detail on sampling and participant characteristics is necessary to support the multi-level claims. In the revised manuscript, we will expand the Participants subsection to explicitly describe the purposive sampling strategy, recruitment channels (professional networks and industry contacts), inclusion criteria focused on active LLM users in software roles, and a demographics table covering roles, organization sizes, years of experience, and self-reported LLM usage frequency. This will provide readers with the information needed to evaluate variation and the basis for extending themes across levels. revision: yes

  2. Referee: [Method] Method section: the interview protocol (including question guides, how prompts evolved across the three rounds, and steps taken to reduce social-desirability or recall bias in self-reported LLM usage) is omitted. This information is load-bearing for evaluating the trustworthiness of the reported benefits, challenges, and mitigations.

    Authors: We acknowledge that the interview protocol details were not sufficiently elaborated. The revised manuscript will include the core semi-structured interview guide, a description of how questions were iteratively refined across the three data collection rounds based on emerging themes from prior analysis, and explicit steps taken to reduce bias, such as assurances of anonymity, use of neutral and open-ended phrasing, requests for concrete recent examples to aid recall, and avoidance of leading questions. These additions will allow better assessment of data trustworthiness. revision: yes

  3. Referee: [Results] Results / Analysis description: explicit reporting of theoretical saturation criteria, member-checking procedures, or any form of triangulation (e.g., with artifacts or secondary data) is absent. This weakens confidence that the identified themes are not artifacts of the particular cohort or analysis process.

    Authors: We agree that explicit documentation of saturation assessment, member checking, and triangulation would enhance confidence in the analysis. In the revised version, we will add a dedicated subsection under Data Analysis that reports the criteria used to determine theoretical saturation (no new categories emerging after the third round), any member-checking steps performed with a subset of participants, and triangulation via independent coding by multiple researchers plus consistency checks against related literature. Where a procedure was not applied, we will note it transparently as a limitation. revision: yes

Circularity Check

0 steps flagged

No circularity: primary interview data analyzed via STGT4DA

full rationale

The paper derives its claims about benefits (e.g., maintaining developer flow), challenges (e.g., reputation damage), and mitigations at individual/team/org/society levels directly from thematic analysis of 22 new practitioner interviews collected in three iterative rounds using Socio-Technical Grounded Theory for Data Analysis (STGT4DA). No equations, fitted parameters renamed as predictions, self-definitional constructs, or load-bearing self-citations appear in the derivation chain. The central results are outputs of the empirical coding process applied to fresh primary data rather than reductions to prior inputs or ansatzes. This is a standard self-contained qualitative study whose validity rests on sampling and triangulation questions, not on any circular structure.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The work rests on standard assumptions of qualitative interview research and grounded theory rather than introducing new free parameters, axioms, or invented entities.

axioms (2)
  • domain assumption Self-reported experiences of interviewed practitioners accurately reflect real LLM impacts on software development.
    Invoked implicitly in the results and conclusion sections when generalizing from the 22 interviews.
  • standard math Socio-Technical Grounded Theory for Data Analysis (STGT4DA) is an appropriate and rigorous method for organizing the interview responses.
    Stated in the method section as the chosen analysis approach.

pith-pipeline@v0.9.0 · 5768 in / 1382 out tokens · 55071 ms · 2026-05-22T12:41:22.386301+00:00 · methodology

discussion (0)

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