diff --git a/README.md b/README.md
index a7156f4..cfbda54 100644
--- a/README.md
+++ b/README.md
@@ -63,12 +63,12 @@ To Contribute, checkout our [`CONTRIBUTING.md`](./CONTRIBUTING.md).
   * [Environmental Impact](#environmental-impact)
   * [Labor](#labor)
   * [Poor Code Quality](#poor-code-quality)
+    * [Deskilling](#deskilling)
     * [Infosec risks](#infosec-risks)
   * [Healthy and Safety](#healthy-and-safety)
     * [Maintainer Fatigue](#maintainer-fatigue)
     * [Ties to the War Industrial Complex](#ties-to-the-war-industrial-complex)
     * [Effects on Policing](#effects-on-policing)
-  * [Deskilling](#deskilling)
   * [Effect on Hardware Prices](#effect-on-hardware-prices)
 * [License](#license)
 
@@ -514,6 +514,16 @@ Vibe coding / agentic workflows result in poorer code quality, and relaxed overs
 * [Amazon calls engineers for a “deep dive” internal meeting to discuss “GenAI”-related outages](https://ghostarchive.org/archive/3TfgF)
 * GitClear has released reports in [2024](https://www.gitclear.com/coding_on_copilot_data_shows_ais_downward_pressure_on_code_quality) and [2025](https://www.gitclear.com/ai_assistant_code_quality_2025_research) indicating a worsening of key code quality metrics correlating with increased LLM adoption.
 
+### Deskilling
+
+There is increasing evidence to show that LLMs negatively impact developers' coding abilities:
+
+* [Brains show less activity when completing tasks with LLMs](https://arxiv.org/abs/2506.08872) compared to completing tasks with search or completing tasks without digital help.
+* [Developers who use early-2025 LLMs reported higher subjective performance](https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/), but were measured to have lower objective performance. This gap between subjective and objective performance was considered notable.
+* [In an Anthropic study](https://www.anthropic.com/research/AI-assistance-coding-skills), learners using LLMs demonstrated lower learning rates on average compared to learners not using LLMs.
+* [A recent study uses the term "cognitive surrender"](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646) to describe the way humans tend to offload key critical thinking skills onto LLMs, even when the output is wrong.
+* There are [anecdotal reports of LLM users forgetting how to code](https://www.theverge.com/ai-artificial-intelligence/767973/vibe-coding-ai-future-end-evolution).
+
 ### Infosec risks
 
 This also often results in massive security holes.
@@ -583,16 +593,6 @@ Having to deal with the onslaught of many LLM written pull requests and issues,
 * [Godot maintainers struggle with 'draining and demoralizing' AI slop submissions](https://www.theregister.com/2026/02/18/godot_maintainers_struggle_with_draining/)
 * [An AI Agent Published a Hit Piece on Me (matplotlib)](http://archive.today/2026.02.19-045842/https://theshamblog.com/an-ai-agent-published-a-hit-piece-on-me/)
 
-## Deskilling
-
-There is increasing evidence to show that LLMs negatively impact developers' coding abilities:
-
-* [Brains show less activity when completing tasks with LLMs](https://arxiv.org/abs/2506.08872) compared to completing tasks with search or completing tasks without digital help.
-* [Developers who use early-2025 LLMs reported higher subjective performance](https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/), but were measured to have lower objective performance. This gap between subjective and objective performance was considered notable.
-* [In an Anthropic study](https://www.anthropic.com/research/AI-assistance-coding-skills), learners using LLMs demonstrated lower learning rates on average compared to learners not using LLMs.
-* [A recent study uses the term "cognitive surrender"](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646) to describe the way humans tend to offload key critical thinking skills onto LLMs, even when the output is wrong.
-* There are [anecdotal reports of LLM users forgetting how to code](https://www.theverge.com/ai-artificial-intelligence/767973/vibe-coding-ai-future-end-evolution).
-
 ## Effect on Hardware Prices
 
 The demand for construction and outfitting of new data-centers to host AI/LLM compute capacity has overwhelmed global supply and production of multiple hardware components. Memory, Storage, and GPUs have seen massive increases in price for both consumer and enterprise models upward of 400% in some cases.