Blog
News, guides, and updates from Curtis Foster.
Fix the corpus: a field guide to RAG data quality
RAG failures usually start before retrieval. Learn how to audit, clean, chunk, and test the corpus behind a reliable AI application.
How I build a self-certifying review loop for production AI
Production agentic AI needs more than a final answer. Here is how I build review loops that test evidence, correct failures, and know when to stop.
From technical program management to AI builder: what transferred, and what didn’t
Technical program management teaches you how to move complex work. AI building adds uncertainty, product judgment, and a tighter feedback loop.
The three numbers I watch on every AI product I ship
AI products fail in the gaps between quality, latency, and cost. Here is the practical dashboard I use before users find those gaps for me.
Hiring your first AI engineer as a non-technical founder: what to actually screen for
Your first AI engineer does more than write code. Here is how to screen for judgment, product sense, and the habits that keep an AI team sane.
Agentic pipelines: what a self-correcting review loop actually buys you
A self-correcting AI review loop does more than catch mistakes. It gives your agentic pipeline bounded recovery, better evidence, and clearer operating costs.
The distribution moat most AI startups ignore until it is too late
A strong AI product is not a distribution strategy. Here is how to build a repeatable path from first user to durable growth before paid acquisition becomes a crutch.
Why AI cost telemetry belongs in your MVP, not your Series A
Your MVP does not need perfect finance reporting. It does need to show what each AI action costs before usage turns into a surprise.
How a non-technical founder can run an AI product day to day
You do not need to become an engineer to run an AI product well. You need clear operations, visible failure points, and a small system you can trust.
When to fine-tune, when to use RAG, and when to write a better prompt
A practical AI decision framework for choosing prompts, retrieval, or fine-tuning without wasting time, money, or engineering effort.
The startup metric almost nobody instruments: retry storms
A retry storm can turn one failed AI request into a four-figure bill. Learn how to spot the pattern, measure it, and protect AI reliability.
Zero to one with generative image and video pipelines using Imagen, Veo, and FFmpeg
A practical guide to building a reliable AI video pipeline with Imagen, Veo, and FFmpeg, from the first still image to a finished export.
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