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🧠⚡️💻🚀 ADHD & Software Development: Real Practices That Work w/ Paige Watson | Agile Mentors Podcast

🤖 AI Summary

  • 🧠 ADHD in software engineering often involves an inability to control focus rather than a lack of it. [06:01]
  • 🌊 Hyperfocus can lead to extreme productivity where developers lose track of basic physical needs like food or drink. [06:19]
  • 🧱 Starting large tasks is a primary point of failure where practitioners may freeze due to choice paralysis. [06:54]
  • 👥 Collaborative programming through mobbing or ensemble work provides essential guardrails to keep attention on current priorities. [07:53]
  • 🧪 Test Driven Development converts requirements into small, executable steps that provide immediate dopamine rewards upon completion. [08:08]
  • 💾 Externalizing memory is necessary because internal buffers flush easily when new, interesting stimuli appear. [10:32]
  • 🌲 Discovery Trees visualize work as a growing path, allowing teams to plan at the last responsible moment rather than upfront. [23:29]
  • 👤 Body doubling utilizes the presence of another person to anchor focus without requiring direct collaboration. [19:15]

🏆 Paige Watson’s ADHD & Software Development: The Cheat Sheet

🧠 Core Philosophy: ADHD as Focus Management

  • 🎯 Focus Control: ADHD is not a lack of focus, but an inability to control its direction. [06:01]
  • 🌊 Hyperfocus Risks: High-intensity flow can lead to cold coffee syndrome (neglecting physical needs like food/hydration). [06:19]
  • 🧊 The Freeze: Large, ambiguous tasks trigger overwhelm and executive function shutdown. [07:02]
  • 💾 Memory Buffer: Short-term memory flushes easily; important tasks often fail to write to the hard drive. [10:32]

🤝 Collaborative Programming & Guardrails

  • 👥 Mob/Ensemble Programming: Full-team collaboration provides external structure and prevents rabbit holes. [08:00]
  • ⌨️ Smart Input: While driving (typing), the ADHD brain can focus on implementation while the team navigates. [12:14]
  • 🚧 Verbal Guardrails: Teammates act as external checks to pull developers back from over-engineering or irrelevant refactors. [12:43]
  • 👯 Body Doubling: Working in the same physical or virtual space as another person to maintain task adherence. [19:15]

🧪 Technical Practices for Dopamine & Structure

  • 🧪 Test-Driven Development (TDD): Converts requirements into small, actionable code targets. [08:08]
  • 💊 Dopamine Loops: Frequent passing tests provide small, consistent rewards that maintain engagement. [08:29]
  • 📝 Code as Requirements: TDD ensures memory lapses don’t result in missing test cases or forgotten logic. [11:51]
  • ✂️ Tiny Chunks: Break work into the smallest possible units to prevent cognitive overload. [11:42]

🌳 Visualization via Discovery Trees

  • 🌲 Just-In-Time Design: Visual task breakdown performed at the last responsible moment rather than upfront. [23:37]
  • 📍 Visual Status: Use markers (ticks for in-progress, slashes for done) to see progress instantly. [24:52]
  • 🛤️ The Roadmap: Maintain a high-level direction but only detail the next 2-4 hours of work. [26:07]
  • 📢 Information Radiator: The tree serves as a transparent status update for management without needing meetings. [27:01]

🏢 Psychological Safety & Team Dynamics

  • 🔓 Self-Disclosure: Vulnerability about needs allows the team to accommodate energy fluctuations. [18:52]
  • 🔋 Recharge Breaks: Normalize quiet time or stepping away from the mob to manage sensory or social exhaustion. [20:41]
  • 🛠️ Experimentation: Treat workflows as code - test, iterate, and discard processes that don’t fit the human element. [30:23]

🤔 Evaluation

  • ⚖️ The speaker notes that computer science students on the autism spectrum enter the field at three times the rate of the general public. [03:38]
  • ⚖️ Supporting the claim of higher neurodivergent prevalence in tech, the research paper Science, Technology, Engineering, and Mathematics (STEM) Participation Among College Students with an Autism Spectrum Disorder by the National Institutes of Health confirms students with ASD are significantly more likely to gravitate toward STEM majors compared to the general population.
  • ⚖️ Regarding workplace performance, the report Neurodiversity in the Tech Sector by ChangeTheFace highlights that teams with neurodivergent professionals can be up to 30% more productive than those without them.
  • ⚖️ Topics for further exploration include the impact of remote work on body doubling and the long-term retention rates of neurodivergent developers in agile versus traditional environments.

❓ Frequently Asked Questions (FAQ)

🌲 Q: What are discovery trees in software development?

🌲 A: Discovery trees are visual maps used to break down complex features into smaller, manageable tasks just in time, helping teams avoid over-designing and reducing cognitive overwhelm.

👥 Q: How does mob programming help developers?

👥 A: Mob programming acts as a social and professional guardrail where teammates help maintain focus on the immediate task, preventing the individual from getting lost in refactoring rabbit holes.

🧪 Q: Why is Test Driven Development effective for neurodivergent brains?

🧪 A: Test Driven Development breaks work into tiny, binary success states that provide frequent feedback and dopamine hits, which helps manage the executive function challenges associated with long-term tasks.

📚 Book Recommendations

↔️ Similar

  • 📘 ADHD 2.0 by Edward M. Hallowell and John J. Ratey explores new science and strategies for thriving with a distracted brain.
  • 📘 Extra Focus by Jesse J. Anderson provides practical frameworks for managing the specific executive function challenges found in ADHD.

🆚 Contrasting

  • 🤿💼 Deep Work: Rules for Focused Success in a Distracted World by Cal Newport argues for isolated, distraction-free concentration which may conflict with the collaborative mobbing strategies suggested in the video.
  • 📘 The Myth of Multitasking by Dave Crenshaw challenges the idea that rapid task-switching is productive, focusing on the costs of attention residue.

🎨 Creatively Related

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