An AI software factory is a pipeline where agents propose and deterministic gates and accountable humans dispose. Here is how we follow one change through seven stages.
Passing tests do not prove a page works. Here is how we make AI agents open the real page, read the screenshot, and fix the browser path until proof is fast.
Our ai agent dispatcher never starts sibling chats. It prints a copy-paste packet and keeps a ledger, while a separate supervisor runs bounded workers inside its own session.
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Risk based code review for AI agents means deterministic path rules set the floor, agent evidence can only raise it, and humans stay required where a miss costs the most.
A developer burned a token budget on one multi-agent review, so we measured where the tokens went. Here is what an AI code review costs, what cut it, and what did not.
We split AI code review into a deterministic gate, fresh single-purpose reviewers and a computed tally, because one long-running reviewer skims its checklist and never asks the big questions.
How we test AI agent instructions like code: reproduce a missed rule from a real review, encode a bad and a good answer, score both with a rubric, and keep the case forever.
Agents are slow and CI is expensive for the same reason. Here is how we moved to CI for AI agents that runs on request, with loose iteration and one strict merge requirement.
We cut always-loaded agent instructions by about 76% without deleting knowledge, by moving guidance to the narrowest layer agents reliably find before it applies.
An AI coding agent sandbox is an environment contract, not a prompt. Here is how we made every checkout, cloud session, and worktree prove it is ready before an agent writes code.
What semi automated trading means, how it differs from full automation, real tool examples, and the risk controls it still needs before you click submit.
There's no universal minimum to trade options. See real broker requirements, contract costs, approval levels, and fees that determine what you actually need.
DLL in trading means Daily Loss Limit: a per-session loss cap on prop firm accounts. Learn how it works, how it differs from drawdown, and how to size around it.
Learn the types of slippage in options trading: negative, positive, and zero slippage, what causes each, and how order type and liquidity affect fills.
A breakdown of real-time algo monitoring: the four layers to track, alert thresholds that avoid fatigue, and how to diagnose failures fast.
Post-only orders guarantee maker-side execution or cancellation. Learn how they work, why exchanges cancel or reprice them, and when to use one.
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