Synthesis — Engineering Education

The evolving thesis. Spun out 2026-08-04 from three of the most-starred educational repositories in software: coding-interview-university (~352k★), awesome-system-design-resources (40.2k★) and ai-engineering-from-scratch (~33k★). nirdiamant-prompt-engineering (7.8k★) joined on 2026-08-05. Small corpus, and the shape is provisional.

Current thesis

Two of the three are shaped by an exam, and the third is the control.

coding-interview-university and awesome-system-design-resources are both organized around what a hiring process tests. That is not a criticism, it is their stated purpose — one is a multi-month plan for passing coding interviews, the other ships “How to Answer a System Design Interview Problem” alongside 60+ graded practice problems. What they teach is downstream of what is assessed (interview-preparation), and the scope decisions show it: coding-interview-university explicitly excludes frontend, full-stack and SQL, which is a strange omission from a computer science education and an obvious one from an interview plan.

ai-engineering-from-scratch has no exam behind it — there is no standardized AI-engineering interview to prepare for — and it is built differently. Its pedagogy is build-it → use-it → ship-it: implement the thing by hand, then use the framework equivalent, then produce a reusable artifact, across 17 capstones. It is the only one of the three that produces something at the end rather than readiness to be questioned.

The correlation is one observation on three sources and could easily be coincidence. What makes it worth stating is that it is testable: the next curriculum to arrive either has an assessment regime behind it or does not, and either teaches by curation or by construction.

The fifth source was the real test, and the correlation did not survive it. developer-roadmap is the case the paragraph below asks for: a curated-pointer curriculum with no assessment behind it. There is no standardized DevOps or product-manager interview the way there is a coding interview, and the project teaches nothing itself — it is a graph of topics pointing at other people’s documentation. Under the thesis it should have been build-it-by-hand. It curates.

What the exam actually predicted, looking back, was scope rather than pedagogy: coding-interview-university drops frontend and SQL because the interview does. developer-roadmap’s scope comes from somewhere else entirely — job titles, one roadmap per role a company hires for. That is a third shaping force beside the exam and the discipline, and it explains a shape the first four could not: a curriculum can be organized by what the labour market names without being organized by what it tests.

So the standing claim narrows to something still useful and no longer clean: where an assessment regime exists, it shapes scope. Pedagogy is chosen on other grounds.

The fourth source landed on the predicted side, and it barely counts as a test. nirdiamant-prompt-engineering has no exam behind it and teaches constructively — as predicted. But its subject is prompt engineering, a technique domain with no hiring pipeline, so the missing exam was settled by the subject before the author decided anything. A real test needs a case that could have gone the other way: a curated-pointer curriculum with no assessment behind it, or a build-it-by-hand one aimed squarely at an interview. Until one arrives the correlation stands at three informative data points and one free one.

Three forms, and each rots differently

The corpus now holds three ways of building a curriculum. A meta-curriculum points at other people’s material. ai-engineering-from-scratch writes original lessons that ask you to build the thing by hand. nirdiamant-prompt-engineering is an executable-curriculum: the lesson is a notebook that already runs, and the reader edits it.

Sorting them by what breaks is more useful than sorting them by effort. Curated pointers suffer link rot, which is loud — a dead link announces itself. Executable lessons suffer dependency drift, which is quiet: a pinned library moves or a model behind an API is retrained, and the notebook may keep running while teaching something that has stopped being true. Build-from-scratch instructions barely decay at all, because they depend on nobody’s service staying up. That ordering is the reverse of the ordering by how quickly a reader gets a result, which is the trade the three forms are actually making.

Two more forms landed on 2026-08-09, and the decay ordering held. prompt-engineering-guide is a reference: written lessons and a Prompt Hub indexed by the task the reader arrives with, with no sequence and nothing recording where anyone is. adrianhajdin-uber-clone is a clone-project: one commercial application rebuilt end to end, the build order standing in for a syllabus.

Both slot into the rot ordering, and the clone goes to the top. A reference decays on two clocks — the technique pages age slowly (chain-of-thought is still chain-of-thought) while the per-model pages age fast, and DAIR.AI’s shelf of GPT-4, Phi-2, Mixtral, Flan and OLMo is being consulted in 2026. A clone decays fastest of anything here, because its dependencies are five commercial services with independent release cycles: a changed free tier or a redesigned console breaks a step in a video that cannot be edited. Link rot takes years; a vendor’s onboarding redesign takes a weekend.

And “build it” turns out to name two opposite things. ai-engineering-from-scratch implements by hand before touching a framework; the Uber clone implements nothing and integrates Clerk, Stripe, Neon, Google Maps and Geoapify. Both are construction, and the vocabulary of curation-versus- construction cannot tell them apart. The real split is from scratch against from services — one leaves the learner understanding a mechanism, the other leaves them having shipped a product, and neither prepares for the question the other answers.

The pedagogy claim finally has a controlled comparison

The founding correlation narrowed, over five sources, to: where an assessment regime exists it shapes scope; pedagogy is chosen on other grounds. Every data point until now was consistent with it and none was controlled — the subjects differed, the authors differed, the exams differed.

prompt-engineering-guide and nirdiamant-prompt-engineering are the first pair that holds the variables still. Same subject (prompting technique), same absence of a hiring pipeline, same self-published-repo genre, published within the same era. One chose 22 runnable notebooks; the other chose written explanation with a lookup table. Same conditions, opposite form.

That is as close to a natural experiment as this corpus is likely to get, and it settles the negative half of the claim: the assessment regime does not determine pedagogy, because here it is held constant and pedagogy varies anyway. What does determine it stays unanswered — author preference, subject maturity, and what the audience will actually read are all live candidates, and the 10× star gap between the two (77.4k against 7.8k) hints at the third without evidencing it.

The commercial pattern also stopped being about individuals. Every source in the corpus has something to sell beside the free artifact; until now the seller was always a person with a book, a course or a site. dair-ai is an organization with an Academy, corporate training and a consulting line. The one publisher here with no evidenced commercial layer is javascript-mastery, and the honest statement is that the repository simply does not show one — not that none exists.

The exam itself arrived, not just curricula shaped by it

llm-interview-questions-hoang is a different kind of object from everything above: not a curriculum but a bare assessment — 50 LLM interview questions with model answers, no path, no capstone, nothing to build. Every prior source lets you infer the exam behind the syllabus; this one is the exam, printed.

It strengthens the founding thesis by removing the inference step. The claim was “syllabus follows assessment,” argued from what curricula include and omit. A pure question bank, self-published and promoted for interview prep, is that assessment with the curriculum stripped away — the same regime, stated directly (interview-preparation).

Two smaller things it fixes. It is the corpus’s first source on the AI/LLM-engineering interview (the founding three cover CS fundamentals and system design), and it shows what that interview rewards today: recall of mechanism — define tokenization, distinguish LoRA from QLoRA — the flashcard end of the pedagogy axis whose opposite pole is ai-engineering-from-scratch‘s build-it-by-hand. It does not touch the corpus’s central hole: still no outcome data, and a question bank says even less than a curriculum about whether answering it predicts doing the job.

The dominant form is the meta-curriculum

Two of the three teach almost nothing themselves. They are structured collections of links to other people’s blog posts, videos, papers and engineering write-ups — awesome-system-design-resources aggregates from Discord, Netflix and Stripe engineering among others; coding-interview-university describes itself as curated pointers.

That form has a property worth naming early: its quality is unusually hard to assess. A textbook can be reviewed. A list of 400 links cannot, practically, and its value depends on curation judgement that leaves no visible trace — you cannot see what was rejected. Popularity is the only signal on offer and popularity here is enormous, which is exactly the condition under which it is least informative.

The disposition the whole corpus assumes, examined for the first time

Every artifact here is built for a learner working alone, by choice, without an instructor. That learner has a name in the education literature — self-directed — and until 2026-08-06 this spoke held not one source that had looked at the disposition itself rather than sold something to it. self-directed-disposition-study (ITiCSE 2025, six researchers, 496 reflections from 264 students at four institutions) is that source, and it complicates the corpus from two directions at once.

What students mean by self-directed is mostly “go find other material.” Of 380 coded behaviours, utilizing external resources accounts for 148 — nearly four times the next category, and more than planning ahead (23), self-assessment (39) and reviewing against expectations (3) put together. The meta-curriculum form is that single behaviour productized: someone else has already done the finding. Whether that is a service to the learner or a removal of the one thing they were practising is not something either the study or this corpus can currently answer, and it is the sharpest question the spoke has.

The biggest reported obstacle to self-direction is assignment structure. Twelve of the 27 not-self-directed responses blamed the shape of the task — “there is really no room to add new tools and techniques that were not discussed” — ahead of unsuccessful effort (7), self-sufficiency (4) and motivation (3). A curriculum in this corpus is an assignment structure with the grade taken off. The finding does not transfer automatically, and the study cannot test it: its setting is a classroom with a deadline. But it puts a mechanism under a suspicion the spoke had no way to voice, and it means the executable-curriculum end of the corpus — the most structured form here — is the form the evidence would predict least self-direction from, not most.

The authors’ own resolution is a tension rather than a recommendation: loosening structure to invite autonomy will increase the second-largest impediment, unsuccessful effort. Their answer is scaffolding that is deliberately faded, which no curriculum in this corpus does — a roadmap is the same density at week 1 and week 40.

What the corpus cannot say

Whether any of this works. Four sources, ~433k combined stars, and zero evidence of learning outcomes — no completion rates, no pass rates, no follow-up on anyone who finished. The star counts measure intent to learn, which is not the same as learning and is probably not even correlated with finishing. Nothing here should be read as a claim that these curricula are effective, only that they are what a very large number of people reach for.

Three of the four maintainers sell something adjacent — ashishps1 runs the AlgoMaster platform, nir-diamant has a book and a newsletter above 50,000 subscribers — which now looks like the normal condition of the genre rather than a fact about particular authors. nirdiamant-prompt-engineering also carries a custom non-commercial licence, the most restrictive terms in the corpus and a reminder that “open educational repository” covers a wide range of actual permissions.

The designed curriculum finally arrives

Every source here until now grew by accretion: a repository, a star count, a maintainer’s judgment about what belongs. cs2023 is the other kind of object — the ACM/IEEE-CS/AAAI undergraduate guidelines, argued to by a joint task force and endorsed by three societies in January and February 2024. Having one of each lets the corpus say something it could not say with repositories alone.

The repository corpus is popularity-selected, and the selection is visible. CS2023 makes Society, Ethics and the Profession and Human-Computer Interaction first-class knowledge areas. Neither is meaningfully present in developer-roadmap, coding-interview-university or awesome-system-design-resources, which sort toward what gets someone hired. That is not a failing of the repositories; it is what optimizing for interview-preparation does to scope. The guidelines are the control that makes the effect measurable rather than asserted.

And the traffic runs both ways. CS2023 has no counterpart to executable-curriculum — material you run rather than read — and says nothing about the self-direction self-directed-disposition-study measures and finds unevenly distributed. A curriculum specifies content; the repositories specify a practice. The corpus has been treating them as competing answers to one question and they are answers to two.

What this does not settle is the spoke’s standing complaint above. CS2023 is a specification, not evidence: it reports no outcomes either. Adding it moves the corpus from four popularity-selected sources with no outcome data to five sources with no outcome data, one of which was designed rather than accreted. The whether-any-of-this-works question is untouched.

One limit worth keeping visible: the 400-page final report would not extract here, so what this wiki holds is the knowledge-area structure and the endorsements, not the CS Core / KA Core tiering or the hour counts. Those are the part that actually constrains a department, and they remain unread.

The exam with no curriculum in between

kernel-exploit-dojo is the standing claim — where an assessment regime exists, it shapes scope — at its limit. Every earlier case reached the conclusion through an author: coding-interview-university drops frontend and SQL because the interview does, but jwasham still wrote a study plan. This archive skips that step. Its scope is not shaped by the exam, it is the exam: 100+ past CTF problems kept with the files the organizers distributed, a working exploit and a writeup, indexed by bug class, primitive, technique, difficulty and solve count.

So the claim survives its most extreme test, and what it produces there is a problem-archive — a fifth form, and the first that is neither authored nor merely a set of pointers. The maintainer’s contribution is the classification and the grading.

A second assessment regime, and it is a better instrument. Everything the spoke has concluded about exams came from one kind of exam, whose properties went unexamined because there was nothing to contrast them with. A CTF is public where an interview is private, scored per problem where an interview is pass/fail, and uses each problem once before releasing it. Those last two are why an archive of this shape can exist at all in security and cannot exist for the hiring interview that shapes most of this corpus. The form is not rare here because it is unpopular; it is rare because the dominant exam keeps its problems.

The corpus gets its first number that is not marketing. The standing caveat on every source has been that stars measure intent to learn rather than learning. This archive carries per-challenge difficulty grades and solve counts, generated by competitions rather than by the maintainer. That is a signal about the item — how many teams landed the problem under time pressure — not about the learner, and it is inherited rather than measured here, so its comparability across events is unestablished. It still moves the corpus off zero on the axis that has been empty since founding, and it does so from the regime that publishes scoreboards. If outcome evidence ever arrives in this spoke, the shape of this source suggests where to look for it.

What has not changed. No sequence, no progress tracking, no license, and no outcome data. Coverage is decided by what got competed on, which is the popularity selection cs2023 exposed in the repository curricula arriving through a different door. And the archive’s own decay mode is new to the corpus: not link rot or dependency drift but relevance, as the bug classes it drills get patched out of the target.

The regime with a sanction behind it

cs2023 gave the corpus a designed curriculum against a shelf of accreted repositories, and the comparison did real work — it exposed the repositories’ popularity selection. What it could not do is compel anything. Three societies endorsed it; no department loses anything by ignoring all 270 CS Core hours.

abet-computing-criteria is the version with consequences. It is an assessment regime of a kind this spoke had not held: it examines the program rather than the candidate, and withdrawal of accreditation is a real cost. So the founding claim — where an assessment regime exists, it shapes scope — gets its strongest instance, and the scope it produces is the one the repositories drop. Ethics and professional responsibility, teamwork, and communication are not encouraged there; they are outcomes a program must demonstrate its graduates attain. developer-roadmap, coding-interview-university and awesome-system-design-resources carry none of the three, and that gap is no longer a repository failing to match a recommendation. It is a repository omitting what an accredited degree is required to contain.

The two prescriptive documents will not add up, and that is worth stating plainly. CS2023 measures in topic hours, ABET in semester credit hours. 270 and 40 are not comparable quantities, neither document maps its unit onto the other’s, and no arithmetic in this wiki should pretend otherwise. What survives the incommensurability is a shared shape: both fix a floor of required computing and mathematics, and both refuse to name courses. ABET says so outright — “the curriculum requirements specify topics, but do not prescribe specific courses.” Two independent bodies, drafting decades apart for different purposes, both stopped at the same boundary between what a curriculum must contain and how a department may arrange it.

And the corpus’s hole survives them both. ABET has bound US computing education for decades and reports no outcomes: no evidence that graduates of programs meeting its hours do better than graduates of programs that do not. The does-any-of-this-work question now has two prescriptive documents and one popularity-selected shelf standing over it, and still nothing measuring a result.

Open questions

• Is the exam/pedagogy correlation real? Answered 2026-08-05, in the negative. developer-roadmap is the named falsifier — curated pointers, no assessment behind it — and it arrived. The surviving claim is narrower: an assessment regime shapes a curriculum’s scope, not its pedagogy, and job title is a third organizing force the founding three did not show. Successor question below.

• Does a curated curriculum remove the practice it teaches? (opened 2026-08-06) self-directed-disposition-study finds resource-finding is what students overwhelmingly mean by self-direction (148 of 380 coded behaviours). The meta-curriculum does that work for them. Either it lowers a barrier or it removes the rep — the corpus holds no evidence either way, and this now outranks most of what is below it.

• Does anyone finish? No completion or outcome data in any founding source. This is the corpus’s central hole and it may be unfillable from repositories alone.

• Who are these for? A 352k-star CS study plan and a 40k-star system-design collection imply either an enormous population of self-taught entrants or an enormous population of bookmarkers. The distinction matters for every other question here and no source addresses it.

• Where is the boundary with the subjects themselves? A curriculum about system design belongs here; a source making a claim about how to build a distributed system belongs in the spoke that owns the claim. The founding three were cleanly on this side. The fourth was the hard case and it sharpened the rule: nirdiamant-prompt-engineering teaches a technique domain that no spoke owns at all, so “route the claim to the claim’s owner” had nowhere to point. It came here on shape: it is a course, meant to be worked through in sequence, where the hub’s parked DAIR.AI guide is a handbook indexed for lookup. Course-shaped versus reference-shaped is a workable line, and it is narrower than the original rule: it decides where the teaching artifact files, and leaves the discipline homeless either way.

• What decides pedagogy, if not the exam? (opened 2026-08-05, replacing the question above) Two curricula here build from scratch and three curate, and the assessment regime no longer sorts them. Candidate explanations the corpus cannot yet choose between: subject maturity (you can hand-roll a transformer, you cannot hand-roll the DevOps toolchain), author resources, or intended session length. Needs a curriculum whose author states why they chose one over the other.

• How big can the subject get before it stops being a discipline? Three founding sources taught computer science, system design and AI engineering. The fourth teaches one technique. If curricula keep narrowing, this spoke either owns every tutorial series ever written or needs a floor, and nothing in the corpus says where that floor is.

Growth edges

Ranked; each names the kind of source that would close it (see ../QUALITY.md → Growth edges).

1. First T1, and the spoke has no tiered floor at all CLOSED 2026-08-06, and its institutional-curriculum successor CLOSED 2026-08-08 by cs2023 (ACM/IEEE-CS/AAAI, T1). Floor now T1 2 / T3 6. Its prescriptive-half successor CLOSED 2026-08-10 (research pass): the report extracts fine as fourteen section PDFs, and cs2023 now holds the CS Core / KA Core / Non-core scheme, the full 17-area hour table, and the four per-topic skill levels. 270 CS Core hours is the binding total. What replaces it: nobody here has checked whether the guidelines are followed. CS2023 says a curriculum must cover all CS Core topics; no source in this wiki says any department does. — needs: a university’s own syllabus or degree map traced against the CS Core list, or an accreditation review reporting conformance.
2. Any outcome data — the corpus holds popularity and nothing else. — needs: a study of self-directed learning completion or hiring outcomes, T1/T2.
3. What decides pedagogy, if not the exam? New 2026-08-05. developer-roadmap broke the founding correlation — curated pointers with no exam behind it — leaving two builders and three curators with nothing sorting them. — needs: a curriculum whose author states the choice and the reason for it, or a comparison across curricula that treats pedagogy as the variable.
4. The assessment side, from the assessors — every source here is written by candidates or for them; nothing represents the people setting the exam. — needs: T1/T2 on technical hiring practice or interview validity research.

Coverage edges (added 2026-08-08, at the curator’s request for a wider backlog). These widen what the spoke covers instead of answering an open question above; one ordinary solid source closes any.

5. Where learners actually are. freeCodeCamp, Coursera and The Odin Project deliver most of this material and none has a page, so the spoke holds curricula (developer-roadmap, cs2023) with no vehicle underneath. — needs: platform documentation plus enrolment or completion figures.
6. Bootcamps, and the one place outcomes get published. Growth edge 2 wants outcome data; the CIRR reporting standard is where it exists, contested as it is. — needs: the CIRR standard plus one audited outcomes report.
7. Accreditation. CLOSED 2026-08-11. abet-computing-criteria (T1, the 2026–2027 Computing Accreditation Commission criteria) is the binding document: 30 semester credit hours of computing generally, 40 SCH of computer science and 15 of mathematics/statistics for a CS program, six mandatory student outcomes including ethics, teamwork and communication. Successor, unmet: the two prescriptive documents do not share units. CS2023 counts topic hours (270 in the CS Core); ABET counts semester credit hours (40). Nothing in either maps onto the other, so the corpus cannot say whether an ABET-accredited program covers the CS Core. — needs: a crosswalk between the two, or a department’s degree map traced against both.
8. Findings, not just venues. iticse is a conference page with no research under it — pair programming, worked examples, retrieval practice all have decades of results. — needs: a SIGCSE or ICER study, T1.

Cross-spoke adjacency

• ../machine-learning-wiki — owns machine learning as a subject. ai-engineering-from-scratch is here because it is a curriculum; a source teaching a technique to make a claim about it routes there. The seam is the same one mathematics-wiki draws against its applied siblings.
• ../bit-manipulation-wiki — owns bitwise technique, one sub-section of coding-interview-university. The park record that preceded this spoke declined that route explicitly, and the reasoning still holds.
• ../agentic-tooling-wiki and ../research-wiki — own agent machinery and tools-for-thought respectively. A guide teaching a tool routes there; a curriculum teaching a discipline routes here. agentic-tooling-wiki was the logged runner-up when nirdiamant-prompt-engineering routed.
• Nobody owns prompt engineering. Worth stating plainly, because this spoke now holds a curriculum for it: the discipline has no spoke. DAIR.AI’s Prompt Engineering Guide has sat in the hub _inbox under the prompt-engineering tag since 2026-07-26 for that reason, and this was the second prompting source to arrive. If a prompt-engineering spoke ever spins out, the claims inside these 22 notebooks belong to it and this page keeps only the curriculum.

Index — Engineering Education Wiki

Catalog of every page, grouped by schema.org @type. Spine: synthesis (thesis), log.md (history), this file (catalog). Spun out of the hub _inbox on 2026-08-04 (3 sources: a CS-fundamentals study plan, an AI/ML build-it curriculum, a system-design resource collection). Star counts and “N learners” are marketing numbers on a dated snapshot — record the date, and never read popularity as evidence that the curriculum works.

DefinedTerm (concepts)

• meta-curriculum — a curriculum made of pointers to other people’s material rather than original teaching; the dominant form here, and the one whose quality is hardest to assess · form
• executable-curriculum — a curriculum whose lessons are runnable programs the reader edits and re-runs; the third form, and the one that decays by dependency drift rather than link rot · form
• interview-preparation — the assessment regime most of these curricula are shaped by; what gets taught is downstream of what gets tested · practice
• problem-archive — past exam problems kept with their solutions, indexed for retrieval rather than ordered for study; the fifth form, and the only one that can carry item-level difficulty data · form
• capture-the-flag — the security competition format; the corpus’s second assessment regime and the first that is not a hiring interview — public, per-problem scoring and single-use problems, which is why an archive can exist here and not around the interview · assessment
• clone-project — one commercial application reproduced end to end, with the build order standing in for a syllabus; the fourth form, and the one whose scope is inherited from a product rather than chosen · form

Person

• mihaela-sabin — computing-education researcher (UNH); lead author of self-directed-disposition-study, the spoke’s first peer-reviewed source · thin node

• nir-diamant — author of nirdiamant-prompt-engineering and sibling notebook repositories on RAG, GenAI agents and agent memory; free lessons under a non-commercial licence with a book and newsletter beside them

• kamran-ahmed — creator of developer-roadmap/roadmap.sh; the corpus’s third individual self-publisher with a commercial layer beside a free repo — the pattern is now 3/3

• hao-hoang — author of llm-interview-questions-hoang; self-published LLM interview-prep via LinkedIn; the corpus’s second individual self-publisher (cf. nir-diamant). Distinct from research-wiki’s chao-huang despite the fuzzy-match.

• mito753 — maintainer of kernel-exploit-dojo; 696 commits of curation behind no visible commercial offer, the second break in the publisher-with-something-to-sell pattern · thin node

Organization

• dair-ai — publisher of prompt-engineering-guide; the corpus’s first organizational self-publisher, with an Academy, corporate training and consulting behind the free MIT guide · thin node
• javascript-mastery — the channel and handle behind adrianhajdin-uber-clone; the teaching is a free YouTube course and the repo is its answer key. Whether a commercial layer exists is not evidenced here, unlike every other publisher in the corpus · thin node

SoftwareSourceCode (sources)

• coding-interview-university — jwasham, ~352k★: a multi-month CS study plan — Big-O, data structures, algorithms, plus caches/processes/networking — explicitly excluding frontend, full-stack and SQL. A meta-curriculum: curated pointers, not lessons · source · T3 · github.com

• awesome-system-design-resources — ashishps1, 40.2k★, GPL-3.0: curated system-design links (scalability, CAP, networking, APIs, databases, caching, distributed systems, architectural patterns) plus 60+ graded practice problems; explicitly interview-framed, and the maintainer sells a course · source · T3 · github.com

• ai-engineering-from-scratch — rohitg00, ~33k★: 503 lessons across 20 phases, maths → classical ML → deep learning → LLM engineering → production, with 17 capstones. The cluster’s outlier — build-it-by-hand, not curated pointers · source · T3 · github.com

• developer-roadmap — kamranahmedse, 363.7k★/44.7k forks: 80+ interactive role-based and skill-based career roadmaps, authored as markdown nodes and synced to roadmap.sh. The spoke’s largest source and its founding-thesis test case — a curated-pointer curriculum with no exam behind it, which breaks the exam↔pedagogy correlation and introduces job title as a third shaping force · source · T3 · github.com

• nirdiamant-prompt-engineering — NirDiamant, 7.8k★, custom non-commercial: 22 runnable Jupyter notebooks, one per prompting technique, ordered in the README only. The first executable-curriculum here, the first on a technique domain rather than a discipline · source · T3 · github.com

• prompt-engineering-guide — dair-ai, 77.4k★/8.5k forks, MIT, 13 languages: 16 techniques, a 12-category Prompt Hub, per-model pages and a risks section, as written lessons plus a site. A reference rather than a sequence — indexed by the task you arrive with, with nothing tracking where a reader is. Same subject and same missing exam as nirdiamant’s, opposite pedagogy: the spoke’s first controlled comparison. “3 million learners” is a January 2024 marketing line still displayed in 2026 · source · T3 · github.com

• adrianhajdin-uber-clone — javascript-mastery, 1.9k★/692 forks, no license stated: a ride-hailing app rebuilt across 15+ features on React Native/Expo with Clerk, Stripe, Neon, Google Maps and Geoapify. The corpus’s first clone-project and the inverse of build-from-scratch — nothing is implemented, five vendor SDKs are integrated; the stars count the answer key, not the YouTube course that does the teaching · source · T3 · github.com

• kernel-exploit-dojo — mito753, 403★/62 forks, 696 commits, no license: 100+ Linux kernel exploitation CTF challenges (2020–2026) filed by bug class, primitive, technique, difficulty and solve count, each with the distributed files, an exploit and a writeup. The standing claim at its limit — scope is not shaped by the exam, it is the exam — and the corpus’s first problem-archive. Carries difficulty grades and solve counts: the first number here that is not marketing, though it describes the item and not the learner · source · T3 · github.com

Article (sources)

• llm-interview-questions-hoang — Hao Hoang, self-published PDF (May 2025): 50 LLM interview questions + model answers (tokenization, attention, LoRA/QLoRA, sampling, RAG, MoE, CoT, plus ML maths). The spoke’s first AI/LLM-engineering interview source, and the assessment regime printed directly rather than inferred from a curriculum · source · T3 · Google Drive PDF (held in raw/)

ScholarlyArticle (sources)

• self-directed-disposition-study — Sabin, Kumar, MacKellar, McCauley, VanDeGrift & Matsumoto, ITiCSE 2025: the spoke’s first T1 and its first source with nothing adjacent to sell. 496 reflections from 264 students, 18 sections, 4 US institutions. Students equate self-direction with finding external material (148 of 380 coded behaviours, ~4× the next); the top reported obstacle is assignment structure (12 of 27). Not disaggregated by course or student characteristics; US-centric · source · T1 · doi.org

Report (sources)

• cs2023 — ACM / IEEE-CS / AAAI undergraduate CS curriculum guidelines, endorsed Jan–Feb 2024: 17 knowledge areas (Computational Science dropped from CS2013’s 18; AI, security, PDC, ethics and mathematics expanded) plus a customizable competency framework. The corpus’s first designed curriculum against a shelf of accreted repositories — and the comparison shows the repositories’ popularity selection, since SEP and HCI are first-class areas here and near-absent there. 270 CS Core hours total across 162 knowledge units, the whole of what the guidelines actually require; MSF is the largest single block at 55 (read from the fourteen section PDFs, 2026-08-10) · source · T1 · csed.acm.org
• abet-computing-criteria — ABET Computing Accreditation Commission, 2026–2027 criteria: the rules a US computing department must meet to stay accredited. 30 semester credit hours of computing generally; computer science adds 40 SCH of CS and 15 SCH of mathematics/statistics with rigor “at least equivalent to introductory calculus,” plus a sixth student outcome. Ethics, teamwork and communication are mandatory attainments, not recommendations — the binding counterpart to cs2023‘s advice, in units that do not convert into CS2023’s topic hours · source · T1 · abet.org

Event

• iticse — ACM Innovation and Technology in Computer Science Education; 30th edition Nijmegen 2025, 32% overall acceptance. The venue where the completion/outcome evidence this spoke lacks actually lives · thin node

Synthesis

• synthesis — the thesis: three of the most-starred curricula in software are shaped by an exam, and the one that isn’t teaches differently