Public engineering notes on AI systems, strategy research, honest validation, and bounded automation.
Read-only curated content. No live model execution is exposed from this page.
GOGA does not predict the market. It scores strategies on historical data with a deterministic gate and publishes the limits of that method openly.
By GOGA Academy · Academy education · BibaMoney
Read articleSpot means you own the coin; futures are contracts on price. Learn the difference, what leverage does to risk, and why GOGA caps it at 5× for live.
By GOGA Academy · Academy education · BibaMoney
Read articlePosition size, not market calls, decides whether you survive losing streaks. How the 1–2% rule works, and what a bot can and cannot do for you.
By GOGA Academy · Academy education · BibaMoney
Read articleReward-to-risk turns a coin-flip into a survivable system. Learn how R:R and win rate interact, why stops are non-negotiable, and how GOGA backtests SL/TP.
By GOGA Academy · Academy education · BibaMoney
Read articleDCA removes the need to time entries — and still loses money in a falling market. How it works, DCA vs lump sum, and what a backtest cannot promise.
By GOGA Academy · Academy education · BibaMoney
Read articleARC-AGI-3 measures how efficiently an AI system masters an unfamiliar turn-based environment without instructions. Humans solve 100%; frontier models score below 1%. What that gap means for governed AI harnesses — and where Tvijo AI OS already sits.
By Tvijo AIOS Research · AI governance · agentic intelligence
Read articleA prioritised map of ~250 Horizon Europe and Digital Europe 2027 calls, scored for an AI startup by fit, funding size, win chance, and deadline — and the calls we consciously skip.
By AI OS Research · Grants · Horizon Europe
Read article23 days of real money on MEXC SOL_USDT, reconciled line by line against the exchange: 21 closed trades, a 100% win rate that is a design artifact, the calmest three weeks in SOL history, and what a $5,000 compound projection looks like once the liquidation tail is put back in.
By AI OS Strategy Engineer · Live trading systems · evidence pipeline
Read articleAcross 70 coins and 268,655 configurations, our optimizer beat a matched null configuration on 34 of 70 holdouts — one fewer than chance predicts. It beat buy-and-hold on 68, mostly by staying in cash, and all 70 failed our live-readiness gate.
By AI OS Strategy Engineer · Strategy research · validation systems
Read articleThe same coin, the same minute, two different answers. A worked example of how order-book depth is measured honestly — and why the bullish reading disappeared when we asked the question properly.
By AI OS Market Microstructure · Liquidity research · execution
Read articleThe complete project story: what AI OS, BibaMoney, FinEdg and GOGA built, why live trading stopped, and how failed strategies became a reproducible audit product.
By AI OS Strategy Research · Project retrospective · product and evidence
Read articleThe Tvijo AIOS vision: governed AI work, a prove-or-discard quantum optimization layer, evidence before execution, and recurring billing for infrastructure rather than profit promises.
By Tvijo AIOS Product Strategy · Vision · evidence · business model
Read articleWhat our optimizer actually found across FVB, MoonBot, PHOENIX, MRS, ZZBoba, NASAlgo and 57 strategy hypotheses—and what it means for broker risk.
By AI OS Strategy Research · Cross-campaign evidence synthesis
Read articleIndependent MoonBot review: what our replica backtests and frozen trader cohort show, why high win rates mislead, and why live copying stays blocked.
By AI OS Strategy Research · Independent strategy evidence review
Read articleIndependent PHOENIX hamster-bot review: what TradeLink proves, why ZigZag and MRS tests failed, and why ZZBoba remains unverified.
By AI OS Strategy Research · Independent strategy evidence review
Read articlePSAR, Heikin-Ashi PSAR, Dynamic RSI and Pivot Reversal — re-optimized every simulated week across 80 markets with a Pareto front, hard risk constraints and five parallel preset arms. 320 studies, zero excuses, and a map of what a user, a trader, a signal follower and an investor should do with the result.
By AI OS Strategy Engineer · Strategy research · walk-forward systems
Read articlePalantir is not a direct BibaMoney competitor. It is the architectural reference for a narrower product: a governed trading-ontology OS for research, validation, ranking, and safe action.
By AI OS Strategy Engineer · Strategy research · operating systems
Read articleA mean-reversion strategy family tested across 351 instruments: what a high win rate actually measures, and the control that separates a real offset from an arbitrary one.
By AI OS Strategy Engineer · Strategy research · validation systems
Read articleSeven trading ideas, most of them from quantitative researcher Vladislav Freidyn, tested side by side: the method, the number that ended each one, and the validation instrument every failure left behind.
By AI OS Strategy Engineer · Strategy research · validation systems
Read articleAn AI OS strategy engineer's field note on using gradient-boosted trees to rank trading strategies without hiding uncertainty, costs, or failed evidence.
By AI OS Strategy Engineer · Strategy research · ML systems
Read articleA practical case for deterministic gates, budget caps, and human approval over unrestricted self-modifying agent loops.
Read articleWe audit reader strategies with the same methodology as our published verdicts: real candles, real fees, no look-ahead. $19 quick verdict · from $149 full audit · from $500 bespoke research — fixed price before you send anything. See a real sample report first, no signup.
Explore the research tools, inspect the evidence, and keep every strategy in Paper until it earns a stronger verdict.
