Raghav Agrawal @impactology@mastodon.social
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impactology.bsky.social
Raghav Agrawal @impactology@mastodon.social
@impactology.bsky.social
2.1K followers 3.4K following 5.8K posts
Former Diamond Dealer | Independently explored research in design, education, and cognitive science; now bringing those ideas to life via UX

https://twitter.com/impactology
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impactology.bsky.social
UI Design worksheet

Inspired by Five Design Sheets
fds-design.github.io
IxD process steps by Jonathan Korman
A comprehensive one-page design worksheet template laid out in A4 format with a dark header reading 'DESIGN WORKSHEET'. The top contains fields for PROJECT, DATE, and SHEET number. The worksheet is organized into 9 main sections arranged in a structured grid: Top row (3 columns): - Section 1 'BRAINSTORM' (left): Contains fields for 'Generate Ideas', 'Filter Categorize', and 'Combine Refine' with horizontal lines for writing - Section 3 'INTERFACE SKETCH' (center): Large dashed-border box for sketching rough layout with placeholder text 'Rough layout sketch (What it looks like)' - Section 5 'FOCUS OPERATIONS' (right): Fields for 'Central Idea/Novel Method', 'Key Operations', and 'Controls Needed' Second row continues sections: - Section 2 'SYSTEM MAP' (left column): Fields for 'Main objects (nouns)', 'Actions (verbs)', 'Flow: object → action → result' with a dashed sketch area, plus 'Goal of screen' and 'Key user actions' - Section 4 'INTERACTION' (center column): Detailed fields for Element, Trigger, Rule/validation, Data used, Action/goal connection, Feedback, Loop, and Mode - Section 6 'VISUAL LOGIC' (right column, upper): Instructions to use spacing/size/typography only, with dashed sketch area for grayscale study - Section 7 'DESIGN REASONING' (right column, lower): Three prompts - Problem (what was unclear?), Principle (what rule/idea fixed it?), Choice (what did you decide and why?)
October 17, 2025 at 12:05 PM
impactology.bsky.social
This means designing tools that unbundle the university’s service of bounded scope, giving self-taught learners the compression, context, and collaborative rhythm of formal education without the hierarchy or exclusion.
Unbundling of a university's service of disciplined scoped learning with rigorous but playful experimentation with other people into three chunked products 1. Contours, a custom search engine client that inverts the paradigm of unlimited scrolling and instead helps in chunking people's explorations Does this by helping identify core transformative ideas, concepts, questions of a domain to help know what to focus & to see the boundaries of where understanding something ends. 2. CALT (Curiosity aligned learning topologies) A platform that creates and curates hard problems to solve for you based on your existing knowledge, skills, interests Basically it creates contextualized problems for you to solve 3. CoLearn A platform that matches mentors & mentees based on shared interests, goals, thinking styles, values to co-create lesson plans A clean, minimalist table titled 2. How Each Tool Produces One Dimension of This State.” It lists three learning tools — Contours, CALT, and CoLearn — across four columns: Tool, Function, Micro-Cognitive Effect, and Macro-Cognitive Outcome. Contours: Function — builds epistemic boundaries to show what’s relevant versus noise. Micro-effect — gives a learner the sense of finitude (“I can see the map. I can stop exploring now.”). Macro-outcome — moves from overwhelm to Clarity. CALT: Function — translates curiosity into deliberate challenges suited to capability. Micro-effect — converts passive knowing into procedural flow (“I can try this now.”). Macro-outcome — moves from paralysis to Momentum. CoLearn: Function — creates reciprocal learning loops by matching mentors and peers. Micro-effect — makes learning socially mirrored (“My curiosity connects to others.”). Macro-outcome — moves from isolation to Belonging.
October 13, 2025 at 3:28 PM
impactology.bsky.social
What a UI design course or book should be like

Purely skill-focused, execution-oriented handbook for building useful, usable, and emotionally intelligent interfaces from sketch to production.
The Full-Stack Design Engineer’s Field Manual A skill-based, execution-oriented handbook for building useful, usable, and emotionally intelligent interfaces — from sketch to production. I · Model the System • Build clarity before pixels. • Map the conceptual model — what objects exist, what they can do, and how they relate. • Compare system, designer, and user models to catch mismatched assumptions. • Define interface language — verbs, nouns, and visible states — that reflect the model. • Draw one diagram that links data, interaction, and feedback. • Prototype system logic in a quick interactive scaffold (spreadsheet, flow builder, or sandbox). • Output → a single-page system model that can guide every design choice. II · Structure the Interaction • Shape flows and states that match system logic. • Use Five Design Sheets to explore multiple structural solutions, not just visual variants. • Define interaction units (tasks) and their entry, transformation, and exit states. • Diagram the behavior logic: triggers, rules, feedback, and loops. • Combine related flows into a state map that exposes dependencies and reuse. • Output → a tested interaction backbone: every possible state accounted for. IV · Express the Logic Visually • Turn invisible behavior into visible structure. • Build a visual grammar (type, color, space, iconography) tied to functional roles. • Represent state change through clear visual transitions, not arbitrary motion. • Balance procedural, participatory, spatial, and encyclopedic affordances (Murray). • Design for hierarchy of attention: one dominant action per view. • Output → a motion-ready interface where visuals communicate system reasoning. V · Encode the Interface • Translate design intelligence into reusable components. • Name components after conceptual roles, not visual appearance. • Bind each component to state rules defined in the model. • Tokenize spacing, color, and timing so they can be coded exactly once. • Pair with developers to validate constraints, breakpoints, and animation curves. • Output → a working component library whose naming mirrors system logic. VI · Test the Experience Mechanically • Evaluate performance, coherence, and cognitive load. • Run latency and feedback audits on real devices. • Time every key interaction; identify drags beyond 300 ms. • Check consistency between concept, copy, and behavior. • Use heuristic testing focused on precision: clarity, latency, reversibility, and tone. • Output → an audit log that treats UX quality as measurable mechanical feedback. VII · Communicate for Implementation • Make reasoning visible to collaborators. • For every major decision, write a 3-line rationale: problem → principle → choice. • Present interaction diagrams and timing tables in developer-ready form. • Conduct critique sessions that target coherence and responsiveness, not aesthetics. • Maintain a decision ledger that captures the evolution of the model. • Output → shared understanding that keeps logic intact through production. VIII · Maintain Conceptual Integrity • Keep growth from breaking the model. • Schedule monthly model audits — does the interface still match core concepts? • Trace every new feature to a node on the original diagram. • Refactor inconsistencies before they propagate. • Archive motion and logic tests as regression references. • Output → a continuously evolving but internally consistent interface system. IX · Ship and Reflect • Close the loop like an engineer. • Compare the shipped build against conceptual and interaction specs. • Record deltas: motion offsets, color drift, timing variance. • Fix or document trade-offs and feed learnings back into tokens or models. • Write a one-page post-flight report per release — what worked, what broke, what’s next.
October 9, 2025 at 1:20 PM
impactology.bsky.social
India – Affiliated College Model vs Western – University Model
Comparison Table: India – Affiliated College Model vs. Western – University Model Aspect: Who teaches? India – Affiliated College Model: Teaching is done in small, semi-autonomous affiliated colleges (often underfunded, with limited faculty autonomy). Western – University Model: Professors are part of the same university that grants degrees. Faculty belong to departments with research + teaching roles. Aspect: Who grants degrees? India – Affiliated College Model: Central university or state university office (not the college itself). Colleges only forward students for exams. Western – University Model: The same university where you study grants the degree. Colleges/departments are internal, not external. Aspect: Curriculum India – Affiliated College Model: Uniform syllabus set by the affiliating university, same across hundreds of colleges. Minimal room for innovation. Western – University Model: Designed by faculty within the university. Can change rapidly to match new research or industry needs. Aspect: Exams & Evaluation India – Affiliated College Model: Centralized question papers and grading, focused on rote memorization. Colleges often train students just to pass. Western – University Model: Evaluation is decentralized: professors design their own assignments, projects, open-book exams, etc. Aspect: Research culture India – Affiliated College Model: Weak to absent. Affiliated colleges are teaching-only, with almost no labs, funding, or publications. Western – University Model: Research and teaching are deeply linked. Universities run labs, journals, conferences, and often drive national innovation. Aspect: Student experience India – Affiliated College Model: Coaching-class vibe: high enrollment, overcrowded, "syllabus-finishing" orientation. Minimal critical thinking. Western – University Model: Campus-based: strong culture of seminars, projects, labs, student-faculty interaction, independent inquiry.
October 3, 2025 at 8:30 AM
impactology.bsky.social
Most honest person I've met recently was a tech VP who told me: "I manage a team of twelve people who create documents for other teams who create documents for senior leadership who don't read documents"

The hidden economy of nonsense by Alex McCann
thestillwandering.substack.com/p/the-death-...
The anthropologist David Graeber called these "bullshit jobs", roles that even the people doing them suspect are pointless. But I think it's evolved beyond that. We've built entire ecosystems of mutual nonsense. Consider the average corporate decision. It starts with someone identifying a "opportunity" (usually a non-problem). This triggers a cascade: analysts analyse, consultants consult, middle managers manage the consultation of the analysis. Workshops are held. Stakeholders are engaged. Decks are created. Months later, something might happen. Usually, it's a minor adjustment that could have been made in an afternoon by anyone with common sense. Everyone involved knows this. The analyst knows their model is largely guesswork. The consultant knows their framework is just common sense in a matrix. The manager knows the workshop is theatre. But they all need each other to maintain the illusion. It's like a corporate version of the emperor's new clothes, everyone can see the emperor is naked, everyone knows everyone can see it, but we've all agreed to keep complimenting his outfit because our mortgages depend on it.
September 25, 2025 at 9:32 AM
impactology.bsky.social
Movement Matters: How Embodied Cognition Informs Teaching and Learning by Edited by Sheila L. Macrine, Jennifer M.B. Fugate direct.mit.edu/books/oa-edi...
Experts translate the latest findings on embodied cognition from neuroscience, psychology, and cognitive science to inform teaching and learning pedagogy. Embodied cognition represents a radical shift in conceptualizing cognitive processes, in which cognition develops through mind-body environmental interaction. If this supposition is correct, then the conventional style of instruction—in which students sit at desks, passively receiving information—needs rethinking. Movement Matters considers the educational implications of an embodied account of cognition, describing the latest research applications from neuroscience, psychology, and cognitive science and demonstrating their relevance for teaching and learning pedagogy. The contributors cover a range of content areas, explaining how the principles of embodied cognition can be applied in classroom settings. After a discussion of the philosophical and theoretical underpinnings of embodied cognition, contributors describe its applications in language, including the areas of handwriting, vocabulary, language development, and reading comprehension; STEM areas, emphasizing finger counting and the importance of hand and body gestures in understanding physical forces; and digital learning technologies, including games and augmented reality. Finally, they explore embodied learning in the social-emotional realm, including how emotional granularity, empathy, and mindfulness benefit classroom learning. Movement Matters introduces a new model, translational learning sciences research, for interpreting and disseminating the latest empirical findings in the burgeoning field of embodied cognition. The book provides an up-to-date, inclusive, and essential resource for those involved in educational planning, design, and pedagogical approaches.
September 14, 2025 at 3:24 PM
impactology.bsky.social
Junior to Senior: Career Advice for the Ambitious Programmer by David Glassanos

www.holloway.com/b/junior-to-...

"A practical guide to self-confidence, personal growth, teamwork, learning, communication, and delivering results—the soft skills that every programmer needs to succeed in their job"
Junior to Senior : Career Advice for the Ambitious Programmer by David Glassanos As a programmer, you’ve spent plenty of time learning technical and programming skills. Junior engineers—and even some who have been in it a long time—must constantly focus on improving their “hard” technical skills. But writing code is only part of our job as software developers. It’s equally essential for developers to cultivate the soft skills critical for adding value for their team, their company, their customers, and their career—and it’s often neglected. Junior to Senior is one of only a few books that gives practical advice on the soft skills needed to thrive as an engineer: Dealing with lack of confidence Learning from others and by reading unfamiliar code Managing your time Working effectively with your manager Communicating clearly with business stakeholders and writing clear documentation Understanding different ways to add value for a company and its customers Managing risks and recovering from mistakes Dealing with conflict Balancing the demands of work and personal life … and much more. Improvements in these areas are important milestones on the journey from junior to senior software developer. Junior to Senior is filled with insights, from one engineer to another, to guide you along that path.
September 12, 2025 at 1:46 PM
impactology.bsky.social
Ask Me This Instead: Flip the Interview to Land Your Dream Job by Kendra Haberkorn
www.holloway.com/b/ask-me-thi...

Why should only hiring managers and recruiters decide your job destiny? No matter where you are in your career journey, it’s time you were in control.
Flip the Interview to Land Your Dream Job by Kendra Haberkorn Written by a veteran recruiter for job-seekers who want to find their dream job—not just the next job. Why should only hiring managers and recruiters be in control of your job destiny? This book will empower you at every step of the hiring process, guiding you to understand your own skills and priorities, how to find the company that can give you what you want, and how to “flip the interview” to get real answers to your most important questions. No matter what field you’re in, whether you’re looking for your first gig or exploring options later in your career—it’s time you were in control. Ask Me This Instead will teach candidates: How to figure out what you really want out of a job How to research companies to narrow your list of prospects To craft a standout resume that’ll help you find fit in your next role What you need to know about who is involved in the hiring process How to use the interview to uncover the truth about the role, team, and company Interview preparation tools and strategies The book also offers: Worksheets to help you uncover your priorities, craft a better resume, create an interview plan, and more! A database of questions candidates can ask different interviewers that can be tailored to your priorities.
September 12, 2025 at 1:39 PM
impactology.bsky.social
Gentle introduction to sheaves on graphs by Jakob Hansen
www.jakobhansen.org/publications...
"Just knowing that two things are connected is not enough. We
need to know something about the relationship implied by connection. Sheaves offer a mathematically rigorous for approaching problems like this"
A gentle introduction to sheaves on graphs Jakob Hansen Abstract This document is an introduction to the language and theory of cellular sheaves on graphs with an eye toward engineering and other applications. No familiarity with topology or commutative algebra is assumed. However, a basic familiarity with graphs, particularly spectral graph theory, and a working knowledge of linear algebra from an abstract perspective (e.g. abstract vector spaces, quotients, direct sums and tensor products, inner products) are necessary. 1 Motivation: connections and relationships Networks are everywhere. The patterns of connectivity between different entities (e.g., people, computers, ideas, neurons) have important consequences for the properties of systems constructed of these entities. This is the foundational insight behind network science and its allied fields, and it has proven immensely useful. But sometimes, just knowing that two things are connected is not enough. We need to know something about the relationship implied by the connection. Sheaves offer a mathematically rigorous for approaching problems like this. They describe the local relationships associated to data on a network, and prescribe how those local relationships combine to give global structure to the data. Sheaves have a sophisticated and deep algebraic theory, as well as a nascent spectral theory, both of which offer powerful tools for understanding networks and systems.
September 11, 2025 at 1:05 PM
impactology.bsky.social
Category Theory for the Sciences by David I. Spivak mitpress.mit.edu/978026202813...

Written in an engaging and straightforward style, and assuming little background in mathematics, the book is rigorous but accessible to non-mathematicians.
An introduction to category theory as a rigorous, flexible, and coherent modeling language that can be used across the sciences. Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences. Information is inherently dynamic; the same ideas can be organized and reorganized in countless ways, and the ability to translate between such organizational structures is becoming increasingly important in the sciences. Category theory offers a unifying framework for information modeling that can facilitate the translation of knowledge between disciplines. Written in an engaging and straightforward style, and assuming little background in mathematics, the book is rigorous but accessible to non-mathematicians.
September 10, 2025 at 2:25 PM
impactology.bsky.social
Poems That Solve Puzzles : The History and Science of Algorithms Chris Bleakley

global.oup.com/academic/pro...

"It is the first book for the general reader on the history and science of algorithms. Uniquely, the algorithms are explained in a clear manner suitable for a non-specialist"
Poems That Solve Puzzles The History and Science of Algorithms by Chris Bleakley It is the first book for the general reader on the history and science of algorithms Uniquely, the algorithms are explained in a clear manner suitable for a non-specialist. The explanations are augmented with easy-to-understand examples and illustrations This title is a narrative history. The tale is driven by the stories of the people and events that gave rise to the invention of algorithms Description Algorithms are the hidden methods that computers apply to process information and make decisions. Nowadays, our lives are run by algorithms. They determine what news we see. They influence which products we buy. They suggest our dating partners. They may even be determining the outcome of national elections. They are creating, and destroying, entire industries. Despite mounting concerns, few know what algorithms are, how they work, or who created them. Poems that Solve Puzzles tells the story of algorithms from their ancient origins to the present day and beyond. The book introduces readers to the inventors and inspirational events behind the genesis of the world's most important algorithms. Professor Chris Bleakley recounts tales of ancient lost inscriptions, Victorian steam-driven contraptions, top secret military projects, penniless academics, hippy dreamers, tech billionaires, superhuman artificial intelligences, cryptocurrencies, and quantum computing. Along the way, the book explains, with the aid of clear examples and illustrations, how the most influential algorithms work. Compelling and impactful, Poems that Solve Puzzles tells the story of how algorithms came to revolutionise our world. Table of Contents 0:Introduction 1:Ancient Algorithms 2:Ever Expanding Circles 3:Computer Dreams 4:Weather Forecasts 5:Artificial Intelligence Emerges 6:Needles in Haystacks 7:The Internet 8:Googling the Web 9:Facebook and Friends 10:America's Favourite Quiz Show 11:Mimicking the Brain 12:Superhuman Intelligence 13:Next Steps
September 2, 2025 at 7:10 PM
impactology.bsky.social
Markwhen is an interactive text-to-timeline tool. Write markdown-ish text and it gets converted into a nice looking cascading timeline.

markwhen.com
github.com/mark-when/ma...
This screenshot shows the Markwhen web application interface, which is a text-to-timeline tool. The interface is divided into two main sections: Left Panel (Text Editor): - Contains a text editor with the title "My 4 day week life" - Shows markdown-like syntax for creating timeline entries: - A work week entry dated 2023-01-09/2023-01-12 with a green #Work tag - A weekend section titled "The new weekend" spanning 3 days with a party emoji and blue #FreeTime tag - Three checkbox items listed under the weekend: "Get shit done" (checked), "other shit" (unchecked), and "A third checkbox" (unchecked) - The left sidebar shows various icons for different tools and views Right Panel (Timeline Visualization): - Displays a calendar-style timeline view for Friday, January 13, 2023 - Shows a visual representation of the work week as a green bar spanning from 2023-01-09 to 2023-01-12 - The weekend period is represented with a blue section showing "3 days" and "1/3" with the party emoji and "The new weekend" label - Contains interactive elements like edit and menu buttons Browser Interface: - Standard browser window with tabs, showing "markwhen.com" in the address bar - User appears to be logged in as "Guest" - The page title shows "My 4 day week life - Markwhen" The interface demonstrates how Markwhen converts simple text markup into an interactive, visual timeline representation.
September 1, 2025 at 2:20 PM
impactology.bsky.social
TIL about The Slide Rule, basically an analog calculator that apollo astronauts carried to space

en.wikipedia.org/wiki/Slide_r...
This image shows a vintage slide rule, a mechanical analog computer used for mathematical calculations before electronic calculators became widespread. The slide rule appears to be a linear model with multiple logarithmic scales printed on white or cream-colored material, housed in a metal frame with sliding mechanisms at both ends. It's photographed against a red textured background that appears to be leather or a similar material. The slide rule has various numerical scales and markings typical of these precision instruments, which were essential tools for engineers, scientists, and mathematicians from the 17th century through the 1970s. The metal hardware and overall construction suggest this is a quality instrument, likely from the mid-20th century when slide rules were at their peak of sophistication and widespread use. These devices worked by aligning different logarithmic scales to perform multiplication, division, roots, logarithms, and trigonometric functions through the physical manipulation of the sliding components.
August 30, 2025 at 6:34 PM
impactology.bsky.social
Augmentability Audit Template

Use this worksheet during design reviews. Unlike usability testing, an augmentability audit checks if your system expands what users can think, learn, and do.
A table with two columns labeled "Heuristic" and "Audit Question". The Heuristic column lists: Expansion of Repertoire, Composability, Malleability, Learnability Through Doing, Collaborative Amplification, Expressive Richness, Scaffolding of Complexity, Feedback as Insight, Generativity, and Long-Term Empowerment. The Audit Question column contains corresponding questions: "Does this app let users achieve something they couldn't before?", "Can users combine parts into larger workflows or structures?", "Can users adapt or reshape the tool to their own needs?", "Does using the app inherently teach new skills or literacies?", "Does the app expand the capacity of groups to work together?", "Does it provide multiple modes of expression (text, visuals, simulations)?", "Can beginners start simple, then progress without hitting a ceiling?", "Does feedback reveal deeper patterns or structures, not just status/errors?", "Does the system invite extension, remix, or new creations?", and "After extended use, are users permanently more capable or literate?"
August 30, 2025 at 11:13 AM
impactology.bsky.social
Augmentability Heuristics Manifesto

A guide for designing systems that expand human capacity

The measure of a system is not how easy it is to use, but how much more capable it leaves its users.
Expansion of Repertoire The system should enable users to think, represent, or act in ways previously impossible. Composability Elements should combine into larger wholes. Users must be able to construct complexity from simplicity. Malleability The medium itself must be open to shaping. Tools should be adaptable and reconfigurable by end users. Learnability Through Doing Interacting with the system should inherently teach the user — new literacies, new habits of mind, new powers. Collaborative Amplification The system should increase the capacity of groups to coordinate, deliberate, and solve together. Expressive Richness Provide multiple modes of expression — text, diagrams, models, simulations — so users can externalize thought fully. Scaffolding of Complexity Design pathways from beginner to expert. Systems should grow with the user, never ceiling them out. Feedback as Insight Feedback should reveal structure, relationships, and possibilities — not just system status. Scaffolding of Complexity Design pathways from beginner to expert. Systems should grow with the user, never ceiling them out. Feedback as Insight Feedback should reveal structure, relationships, and possibilities — not just system status. Generativity The system should invite extension, remix, and new creations. It should be a platform, not a product. Long-Term Empowerment
August 30, 2025 at 5:55 AM
impactology.bsky.social
Lead to job posts like the former displacing the latter

Usability Engineer became ancestor of today’s UX researcher/designer

The Augmentability Designer could have become ancestor of a profession that looks more like Bret Victor, Ink & Switch, Andy Matuschak or “tools for thought” community today.
Two job postings displayed vertically with clear separation. The first posting has a light gray header with a folder icon and reads "Actual Timeline — Usability Engineer (1985)". Below are sections for Company (IBM Human Factors Group), Position (Usability Engineer), and Description explaining the role involves evaluating user interaction with business software using cognitive psychology principles. The Responsibilities section lists four bullet points about conducting studies, applying modeling techniques, running experiments, and producing guidelines. The Qualifications section has three bullet points covering required background in psychology, statistical methods, and lab study experience. The Goal section states: "Make existing computer systems easier to use." Below this, separated by white space, is the second posting with a brown header and folder icon reading "Alternate Timeline — Augmentability Designer (1985)". It follows the same structural layout with Company (Xerox PARC Media Systems Lab), Position (Augmentability Designer), and Description about inventing new ways humans can think and create through computing. Its Responsibilities section has four bullet points about prototyping devices, exploring collaborative systems, designing learning environments, and collaborating across disciplines. The Qualifications section lists three requirements including background in computer graphics, prototyping abilities, and imagination for societal change.
August 29, 2025 at 5:24 PM
impactology.bsky.social
"Delft Students on Software Architecture (DESOSA) is a collection of technical essays in which students explore the software architecture of 28 different open source systems"

desosa.nl/about
About Arie van Deursen and Casper Boone Delft Students on Software Architecture (DESOSA) is a collection of technical essays in which students explore the software architecture of 28 different open source systems. These essays are available as a series of blog posts for easy browsing, besides being available in ebook form as pdf and epub. These essays were written as part of a master level course on Software Architecture that took place in the spring of 2020. The essays emerged as they were written, with most of them posted in March / April 2020. In total over 120 students worked in teams of four, studying over 30 different systems. The course is open by design, with students not just learning from the teacher, but primarily from each other and from the wisdom of the open source communities. The course builds on ideas in open learning from (the late) Erik Duval, and on Amy Brown and Greg Wilson’s book series addressing the Architecture of Open Source Applications1. Students could decide for themselves whether to publish their essays, or whether to keep them visible to other students only. The large majority (28 out of 30) of teams decided to make their work public, with the result visible here.
August 23, 2025 at 12:16 PM
impactology.bsky.social
A collection of short guides to concept design & software design more generally by Daniel Jackson

essenceofsoftware.com/tutorials/

Case studies in concept design by Daniel Jackson
essenceofsoftware.com/studies/
Tutorials A collection of short guides to concept design & software design more generally A gentle introduction How software succeeds January 8, 2024 · 9 min · Daniel Jackson On software design Design vs. engineering August 2, 2022 · 4 min · Daniel Jackson How great design happens August 2, 2022 · 4 min · Daniel Jackson Form, context & misfits August 2, 2022 · 5 min · Daniel Jackson Generic fitness criteria August 2, 2022 · 5 min · Daniel Jackson Simplicity August 2, 2022 · 2 min · Daniel Jackson Levels of design August 2, 2022 · 3 min · Daniel Jackson Beyond the user interface August 2, 2022 · 3 min · Daniel Jackson Divergent and convergent design September 11, 2023 · 3 min · Daniel Jackson Tactics for divergent design September 11, 2023 · 7 min · Daniel Jackson On concept design Software = concepts August 23, 2022 · 6 min · Daniel Jackson Operational principles August 2, 2022 · 11 min · Daniel Jackson Concept purposes September 11, 2023 · 7 min · Daniel Jackson Apps are state machines August 2, 2022 · 10 min · Daniel Jackson Concepts are state machines September 14, 2022 · 8 min · Daniel Jackson Concept state May 23, 2023 · 14 min · Daniel Jackson Concept criteria: what’s a concept? September 11, 2023 · 8 min · Daniel Jackson Concept composition and sync September 14, 2022 · 11 min · Daniel Jackson Concept dependencies and subsets September 11, 2023 · 10 min · Daniel Jackson Concept modularity September 22, 2022 · 12 min · Daniel Jackson Case Studies Case studies in concept design Shorter case studies Breaking Integrity: Three Examples April 2, 2023 · 5 min · Daniel Jackson The Class Number Dilemma February 24, 2022 · 3 min · Daniel Jackson Upvote: An Example Concept November 17, 2021 · 5 min · Daniel Jackson Zoom’s Missing Concept August 21, 2022 · 5 min · Daniel Jackson Longer case studies A GPT-powered tutor July 11, 2023 · 20 min · Daniel Jackson Android Camera API July 11, 2023 · 10 min · Daniel Jackson Concept Piggybacking in DNS March 11, 2022 · 11 min · Daniel Jackson Facebook and Dark Patterns March 25, 2022 · 13 min · Daniel Jackson Redesigning Zoom’s Reaction Concept July 12, 2022 · 16 min · Daniel Jackson
August 23, 2025 at 6:28 AM
impactology.bsky.social
Infographic for Code Quality & Debugging
This is a code quality infographic titled "Code Quality & Debugging - Best Practices for Investigation and Prevention" with a CodeGuide logo, designed in the clean, professional visual style of medical guidelines. The infographic is divided into three main sections: When should code be investigated? - A four-step debugging methodology presented in a grid of flow cards: 1. Reproduce First - Create smallest deterministic repro case with fixture data, seed, container 2. Binary Search - Use git bisect; add assertions and checkpoints to narrow scope 3. Read Errors Carefully - Focus on first cause, not final symptom; follow stack traces 4. Instrument & Test - Add temporary counters; enable verbose logs; swap components Common code quality issues - Six issue cards arranged in a grid format, each containing warning signs, quick fixes, and prevention strategies: God Objects & Long Functions Warning Signs: Mixed concerns; no seam for testing; functions over 50 lines; classes handling multiple responsibilities Quick Fix: Break into smaller modules; add seams; extract methods; create unit tests Prevention: Enforce max function/class size in linting; code review standards; SOLID principles High Coupling & Low Cohesion Warning Signs: Every change ripples across modules; tight dependencies; hard to isolate for testing Quick Fix: Introduce interfaces; dependency injection; create adapter layers Prevention: Hexagonal architecture; ports & adapters; clear domain boundaries
August 23, 2025 at 5:15 AM
impactology.bsky.social
What if most common causes of bugs in software and way to fix them were presented like how medical guidelines are presented via infographics
This is a medical infographic from The BMJ (British Medical Journal) titled "Infertility testing: Initial investigation and referral" that provides a visual summary of when and how to investigate fertility issues. When should patients be investigated? The flowchart shows two main pathways: 1. Regular menstrual cycle: - Age under 35 years AND no risk factors: Investigate after 12 months of regular unprotected intercourse - Age over 35 years OR important risk factors: Investigate after 6 months of regular unprotected intercourse 2. Irregular menstrual cycle (defined as less than 24 days or more than 35 days between menstruation): Investigate after 6 months of regular unprotected intercourse Prior conditions requiring earlier investigation include: - Chemotherapy, substance or anabolic steroid use - Pelvic infections, sexually transmitted infections or tuberculosis - Pelvic or testicular surgery - Endometriosis, large uterine fibroids, endometrial polyps, endometrial hyperplasia or malignancy or suspected Müllerian anomalies Which tests should be performed? The infographic outlines several testing categories: 1. Tubal patency testing with either: - Hysterosalpingography (HSG) - Sonohysterogram (SHG) / Hysterosalpingo contrast sonography (HyCoSy) This is a table titled "Code Quality Guidelines (Medical Analogy Style)" that presents software development issues using medical terminology and provides both acute treatments and prevention strategies. The table has three columns: Condition (Bug Type), Acute Treatment (Fix After It Happens), and Avoid Future Recurrence. The conditions and their treatments include: Ambiguous requirements - Clarify intent with product owners and add explicit tests for edge cases. Prevention involves using living documentation, acceptance criteria, and BDD specs. Hidden state and side effects - Refactor to isolate state, introduce immutability, and add logging. Prevention uses functional principles, pure functions, and dependency injection. Concurrency/ordering errors - Add locks, retries, or message ordering and reproduce with tooling. Prevention involves designing with async models, idempotency, and backpressure. Boundary mistakes (off-by-one, array limits) - Patch logic and add regression tests. Prevention uses property-based tests, static analysis, and assertions. Null/undefined values - Add null guards, default values, or migrations. Prevention involves using non-nullable types, optionals, contracts, and schema validation. Error handling gaps - Patch missing try/catch and add retries with jitter. Prevention standardizes error contracts and linting for unhandled promise/errors.
August 23, 2025 at 4:57 AM
impactology.bsky.social
TIL Michael Faraday apprenticed as a bookbinder; self-taught science from books and never had formal credentials 😍

The Fascinating Story of Michael Faraday by Niall Leah

freedium.cfd/https://nial...
Mr.Riebau later showed these notes to a regular customer at the store named Mr. Price. Mr. Price, unlike Mr. Faraday, was exceptionally well connected in London society with links in the scientific community. Impressed by the notes, he pulled some strings to allow Faraday to attend a series of lectures by Sir Humphry Davy, a pioneer in the forefront of chemistry and Faraday's hero! Faraday was absolutely enthralled by the lecture. Burning with passion and enthusiasm, he scribbled heaps of notes. Afterward, he sent a letter to Davy requesting a shot at being his lab assistant. Faraday had seen the light; he wouldn't miss this opportunity. His first letter wasn't answered. His letter slipped into the void that any medium writer would be familiar with. Or so he thought... Before long, fortunately, or unfortunately, depending on your perspective, Davy was temporarily blinded during an experiment, and Mr. Price recommended Faraday to take over as a temporary lab assistant. After accepting, Faraday showed his hard work, knowledge, and attention to detail, determined to make a great impression on his idol. When his temporary position ended, he sent Davy a letter asking for a full-time position as his assistant. He would take any position no matter how small, so long as it involved science. Alongside the letter, he attached the notes he had written so enthusiastically. They numbered over 300 pages! and discussed the points in Davy's lecture in precise detail. He wanted to show he had both the passion and the understanding needed to do the work. Davy was impressed both by the notes and the hardworking Faraday. He returned a letter saying he would do whatever he could to help Faraday. Unfortunately, Faraday would change science forever. He would go on to make numerous achievements in the fields of chemistry, electromagnetism, and electricity. His discoveries made considerable contributions to the modern life we live today. In Chemistry, he discovered Benzine, notable for being a beneficial property in both understanding chemical bonding and for making new materials. He also added proof to John Dalton's claim that all cases could be liquified by becoming the first to liquefy Chlorine and Ammonia. He established the foundation of the concept of the electromagnetic field following a discovery by Hans Christian Orsted, who had proved that a magnetic field was created by an electric current going through a wire. These efforts would lead Faraday to make the first electric motor. Later he would utilize the discoveries in electromagnetism to create the first electrical generator known as the Faraday disk. This allowed mechanical energy to be converted to electrical energy paving the way for the use of electricity to be viable in emerging technologies and machinery.
August 22, 2025 at 6:56 PM
impactology.bsky.social
What constitutes a good explanation?

Have you given or experienced explanation of anything in this manner?
What constitutes a good explanation? Anything that unpacks the experience of where and how a concept is applied to make or do something useful, such that it increases your ability to perceive situations things with more depth that were hidden before, thereby increasing your ability to imagine, question and make things with more specificity and detail. Basically anything that breaks down how and where a concept is used to create or do something helpful. It should help you see things more clearly and deeply things that might’ve been hidden before so you can better imagine, question, and build stuff with more detail and precision. The understanding that comes from these kind of explanations repeatedly is a process of becoming a different person, it builds new meaning networks in your mind. So a good explanation lets people see more than they could before and then use that new seeing to make better things. Now think about this, how would you explain _______ (your idea/your research topic) with explanations like that. That kind of explanation would constitute explaining _____from first principles
August 17, 2025 at 11:33 AM
impactology.bsky.social
Systematic Method for Designers by L. Bruce Archer h/t @borisanthony.net for sharing this years ago

Dubberly's concept map on archer's checklist www.dubberly.com/wp-content/u...
Image 1: Preliminaries Receive enquiry Evaluate enquiry Estimate office workload Prepare preliminary response Briefing Receive instructions Define goals Define constraints Programming Establish crucial issues Propose a course of action Data collection Collect readily available information Classify and store data Analysis Identify sub-problems Analyse sub-problems about ends Prepare performance specification Reappraise programme and estimate Phase 1—'Receive brief, analyse problem, prepare detailed programme and estimate' Phase 2—'Collect data, prepare performance (or design) specification, reappraise proposed programme and estimate' Image 2: Synthesis Resolve problems about ends Postulate means for reconciling divergent desiderata in specification Develop solutions-in-principle to problems about means arising from specification Postulate outline overall solution(s) Development Define design idea Erect a key model Develop sub-problem mutual solutions Develop overall solution(s) Validate hypotheses Communication Define communication needs Select communication medium Prepare communication Prepare communication Transmit information Winding up Wind up project Close records Phase 3—'Prepare outline design proposal(s)' Phase 4—'Develop prototype design(s)' Phase 5—'Prepare (and execute) validation studies' Phase 6—'Prepare manufacturing documentation' Image 3: Systematic Method for Designers 61 Figure 2 The basic relationship at the point of use. [First diagram shows a simple triangle with "Man" at top, "Tool" and "Work" at bottom corners, all enclosed in a circle labeled "Environment"] Figure 3 The activities contained in a man-tool-work environment system. [Second diagram shows a more complex circular system with multiple interactions between Man, Tool, Work, and Environment with various labeled connections] Table 1 Activity 1 Environment acts on man 2 Man performs work 3 Work reacts on man 4 Man operates tool 5 Tool reacts on man 6 Tool performs work 7 Work reacts on tool 8 Work acts on environment 9 Environment acts on tool 10 Tool has side effects on environment 11 Environment acts on man
August 15, 2025 at 1:18 PM
impactology.bsky.social
This is about manipulating desirable difficulty, pushing the learner past comfort but without hitting overload the sweet spot for neuroplasticity.

So the personalization doesn't happen for content but rather in curating hard problems for people.
Here's the word-for-word transcription of the text in the image: "Curiosity Aligned Learning Topologies" Is it possible to create interrelated topology of problems? Instead of a curriculum topology being where nodes are concepts, could it be the nodes are set of slow rich problems Where it create 10-12 intense context rich slow problems based on what the learner knows and what they want to learn, with concepts & pathways adapted to the problem nodes Like depending on the user's goal it activates only those nodes aka only those problems that are relevant to their background knowledge, interest and goal The challenge of this is defining the data attributes of both start state and end state in a way that the system can establish similarity Lets say the start state and the end goal state doesn't have much dependencies between them (for example lets say start state is a sociology student who knows qual research and his end state goal is to learn differential equations) Now the system has to find out set of problem nodes that can find some degree of similarities between them such that solving those problem nodes gets them closer to end state Why would a sociologist care about modelling how one thing changes when another thing changes smoothly (what a differential equation does) The motivations behind that could be a bridge. A friend suggested to just go search for sociology papers that have the words "differential equation" in them and and just look at what they use them for For example : "Simulate how misinformation spreads in a protest", Kate Starbird studies the spread of rumors. Kate Starbird's Research Group Archive | Human Centered Design & Engineering https://www.hcde.washington.edu/research/archives/starbird Misleading Ourselves: How Disinformation Manipulates Sensemaking https://www.researchgate.net/publication/ 385107666_Misleading_Ourselves_How_Disinformation_Manipulates_Sensemaking Can Problems Be Nodes in a Topology? Traditional topologies use concepts as nodes and edges represent logical or pedagogical dependencies. But CALT flips this: Problems are the nodes, and the edges are cognitive, conceptual, methodological, or motivational bridges between them. Each problem: Encodes a small epistemic region (concepts + methods activated) Has preconditions (entry requirements) Has postconditions (skills unlocked, concepts reinforced, worlds made visible) Can be linked via multi-dimensional relationships: methodological transfer, context analogies, conceptual bridges Start State → Goal State via Problem Nodes The challenge becomes: How can a user move from their current epistemic state (start node) to a desired epistemic state (goal node) through a set of problems? Example: Start state: A sociology undergrad, trained in qualitative research and sensemaking Goal: Understand and use differential equations You're not going to throw the heat equation at them. Instead, you ask: "Why might someone like this want to learn differential equations?" And your system finds: Problems like: ○ "Model how rumors cascade through a population" (uses system dynamics) ○ "Simulate trust decay in online communities" (uses rate of change, delay feedback) ○ "Analyze how exposure to conflicting narratives modulates belief" (dynamical systems) These problems are: Motivationally resonant Topologically connected by the idea of dynamic change over time — the conceptual intuition behind DEs.
August 15, 2025 at 12:33 PM
impactology.bsky.social
A bias for energy conversation holds back brain from growing new synapses, to learn new things.

Gen AI supports this resistance, question is how could they break this

Turn AI tutor from an answer-giver into a challenge curator, making learning process effortful but winnable

x.com/err_mk/statu...
Rohan Paul @rohanpaul_ai · 14h 🎯 Andrej Karpathy on how to learn. There are a lot of videos on YouTube/TikTok etc. that give the appearance of education, but if you look closely they are really just entertainment. This is very convenient for everyone involved : the people watching enjoy thinking they are learning (but actually they are just having fun). Learning is not supposed to be fun. The primary feeling should be that of effort. It should look a lot less like that "10 minute full body" workout from your local digital media creator and a lot more like a serious session at the gym. You want the mental equivalent of sweating. I find it helpful to explicitly declare your intent up front as a sharp, binary variable in your mind. If you are consuming content: are you trying to be entertained or are you trying to learn? And if you are creating content: are you trying to entertain or are you trying to teach? You'll go down a different path in each case. So for those who actually want to learn. Unless you are trying to learn something narrow and specific, close those tabs with quick blog posts. Close those tabs of "Learn XYZ in 10 minutes". Consider the opportunity cost of snacking and seek the meal - the textbooks, docs, papers, manuals, longform. Allocate a 4 hour window. Don't just read, take notes, re-read, re-phrase, process, manipulate, learn. How to become an expert at a thing: Iteratively take on concrete projects and accomplish them depth wise, learning "on demand" (i.e don't learn bottom up breadth wise). Marko ✓ @err_mk The reason the learning is difficult is because brain is fighting against growing new synapses. In a similar way as your body is fighting against a workout. It's about the principle of energy conservation: the brain wants to use the minimum amount of energy it has to. That is why we need to fight against us. We need to find motivation that will bypass this and make the brain start growing new synapses.
August 15, 2025 at 12:29 PM