The fix
Public trading turns process failures into product requirements.
The product fix was obvious: close-option audits need to be exhaustive.
If a position does not close, the system should surface every reason clearly: the first blocker, the explanation that sounds most actionable, and every other blocker in the chain.
What the audit should expose
Underlying filters, spread type filters, P/L thresholds, DTE rules, quote availability, stale marks, naked-short protections, and broker-shape constraints all need to be visible.
Partial visibility is dangerous because it can be correct and still incomplete.
For your own open spread, ask Aurora: “Read the configured close rule and audit this position without placing an order. List every blocking condition, including symbols, spread type, profit threshold, days to expiration, quote/mark availability and broker constraints. After an approved configuration correction, re-evaluate the whole rule and show which blockers remain.” Keep the audit response with the configuration you reviewed.
Aurora gave me a real explanation. The problem was that live trading decisions need the full audit context, especially when the portfolio is moving fast and I am already biased toward action.
So I fixed the close-option audit path so close evaluations do not short-circuit on one reason. Aurora and the UI should be able to show the full set of blockers.
That is a direct product improvement from a real portfolio mistake.
Platform update
The Backtest Corpus Explorer is how Aurora gets better at finding strategies.
The NVDA mistake was an execution problem: when money is moving fast, the system needs perfect observability before I touch the trade manually.
But execution is only half the battle. The other half is finding better strategies in the first place. The irony is that while I was panic-selling NVDA, I was supposed to be fixing exactly that.
The Backtest Corpus Explorer is the first version of that idea: a way to browse trading strategies by return, alpha, drawdown, Sortino ratio, cadence, asset class, signal frequency, and indicator structure.
To support the Explorer, I relaunched 270,584 historical backtests through the current engine. The rationale was simple: Aurora should not have to invent every strategy idea from scratch. It should be able to search a large, comparable dataset, find patterns that worked, and use those patterns as starting points.
The first Explorer view keeps completed runs with real strategy definitions, usable return stats, and comparable strategy and indicator rows. That leaves 130,633 strategy backtests for search and comparison.
The important part is what the rerun exposed: fleet sizing, memory pressure, worker routing, and environment tuning. I fixed those and made the engine more efficient under heavy load.
That is how the Explorer becomes useful. It gives Aurora a research surface and gives the engine a bug-mining surface. When the data shows impossible results, I can find the engine behavior that produced them, fix it, rerun the affected strategy shapes, and improve the corpus.
The next step is direct Aurora integration. When Aurora creates strategies, it should be able to search this corpus first instead of starting every idea from a blank page.
Where it stands
The hardest part is obeying the rule when it is working.
The portfolio is up 16.6% in nine days.
That is a great headline. It is also the easiest part to misunderstand.
The real update is that the system is working, and the system is exposing where it needs better rails. The portfolio found a winner. Aurora found a configuration issue. I made a manual process mistake. The audit path got better. The backtest engine got stronger. The corpus explorer came online.
This week, the portfolio made money. The product got better. I got a reminder that the hardest part of systematic trading is not writing the rule.
It is obeying it when the portfolio is up $4,059.15 in nine days.
Every trade, every AI model test, every bug, and every hard lesson is documented in public.
Read The SeriesThe open runbook, agent bakeoff, weekly live scoreboard, and failure archive are in the Public Portfolio Challenge repository →
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