Source Authorship Forensics

Ember — human-written, or AI-generated?

A source-level read of ExxDreamerCode/Ember v1.1.1, contrasted with Stockfish.

Authors D.r.e.A.m.e.R (ExxDreamerCode) & Boris Nagaev (starius) Language Rust Scope ~8,000 LoC · 145 commits · 2 developers Eval NNUE (+ Syzygy, Polyglot book) Analyzed 2026-07-10 Method source read + git history + testing artifacts Stockfish similarity Strong →
Verdict · Human-Written

Human — and unusually thoughtful, with a genuine two-person collaboration.

Ember is a personal learning project (its Russian-language README says as much) that grew a real collaborator: two distinct developers commit here, exchanging work through actual pull requests. The history is full of quantified, incremental engineering, and the project includes a hand-curated regression suite so distinctive — complete with video demos of the engine's own blunders — that it could only be a person's work.

No AI residue of any kind: no generated-text markers, no agent artifacts, no incoherence. Just two people building an engine and documenting its mistakes carefully.

Confidence: High — the collaboration, the testing culture, and the code all point the same way.

Part of a series applying the same lens: the AI-pasted Luna, the agent-built Owen, and the human-written rudim, Crustik, Catalyst and tomitankChess.

1The "stupidities" suite — a fingerprint of human care

The single most human artifact in the repo is its test methodology: a curated library of the engine's own blunders, each proven fixed.

// stupidities/cases/S-0001/case.json
"title": "Search heuristics choose non-defensive rook moves under king attack",
"status": "fixed",
"fen": "4r1k1/1p3pp1/1p1p3p/1Pr5/4Ppn1/1B1P1N1q/1RP2P2/3QR1K1 w - - 0 23",
"bad_move": "b2b1",
"reference_best_move": "b3d5",
"reference_note": "...b2b1 and b2a2 are consistently refuted by ...Rc5-h5 and
                   ...Qxf3/Qf2 mating lines.",
"before": { "depth_moves": { "6": "b2b1", "8": "b2a2", "10": "b2a2" } },
"fix":    { "summary": "Correction history now updates only after root searches,
             and LMP/null move pruning are guarded in tactical king-pressure positions." }
Why this is decisive: each case pins a specific position where the engine played a losing move, records what it chose at each depth before and after the fix, explains the tactical refutation in prose, and ships .mp4 video demos (base-before-bad.mp4base-after-fixed.mp4). This is painstaking, idiosyncratic human QA — the opposite of anything a language model emits on its own.

2A real collaboration, and real engineering

Two developers, working the way open-source engines are actually built.

#SignalWhat it showsWeight
1Two distinct authors merging via PRs (e.g. "Merge pull request #16 from starius/shrink-nnue")Genuine multi-person open-source workflowDecisive
2The curated, video-documented "stupidities" regression suiteIdiosyncratic human testing methodologyDecisive
3Quantified perf commits: "mailbox lookups in movegen and search (+23% NPS)"Measured, incremental optimisation — a real dev loopStrong
4Russian personal README; casual commits ("mend", "Revert some fixes")An individual's voice and workflowStrong
5Nix flake, Python training notebooks, Elo-test configsA fully-outfitted, seriously-maintained projectSupport
6Zero AI residue or agent artifactsNo generated-code fingerprintsSupport

3Compare & contrast with Stockfish

Where it resembles Stockfish
NNUE evaluation, magic bitboards, shared transposition table
Modern search: SEE, NMP, LMP, correction history, quiescence
Syzygy tablebase support and Polyglot opening book
PR-based multi-developer workflow with regression tests
Where it differs
Rust vs C++; ~8k LoC and two authors vs a vast, decades-old team effort
An avowed learning/experimentation project rather than a title contender
Bespoke video-backed "stupidities" QA rather than Fishtest-scale SPRT

Bottom line

Ember is a human-written, collaboratively-developed Rust engine — a personal learning project that attracted a second contributor and matured into a properly-tooled codebase. Its hand-curated, video-documented library of the engine's own blunders is the kind of painstaking, personal craftsmanship that no generator produces. It belongs firmly on the human side of the series, and stands out for the care in how it is tested.