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Title: TechScribr

Publisher:  sayan.biswas
Message frequency:  0.16 / day

Message History

How a solo developer ships an AI-built options-market data and research system: two AI architects working in isolation, priced adversarial findings, human gates, and the bugs the process actually caught.

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A practical guide to attribution rules, conversion deduplication, randomized holdouts, and the gap between credited revenue and causal lift.

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How prompt caching reuses identical LLM input prefixes, why causal attention makes it possible, when the economics work out, and how to diagnose cache misses.

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Bid Landscaping series - Part 1: Learning the Win Curve from the Auctions We Lost · Part 2 (this post): From Win Curve to Bidding, Pacing, and Its Limits Part 1 built the object: for a given context, the win curve $W(b)=\Pr(\text{win}\mid \text{bid } b)=1-S(b)$, estimated with Kaplan-Meier from wins (which reveal the clearing price exactly) and losses (right-censored at our bid)...

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