Data & RAG
What Change Data Capture Costs at 1 TB a Month: Five Tools Compared
A closer look at Estuary, Fivetran, Airbyte, AWS DMS, and Google Cloud Datastream, with published rates, reproducible calculations, and the…
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Retrieval, data pipelines and the cost of moving data, for people building AI systems.
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Data & RAG
A closer look at Estuary, Fivetran, Airbyte, AWS DMS, and Google Cloud Datastream, with published rates, reproducible calculations, and the…
Data & RAG
A bigger context window makes some retrieval pipelines unnecessary. The harder question is which ones, and what it costs to replace them.
Data & RAG
Nine platforms, three questions: how fresh your data really gets, which systems they connect, and what they cost once everything is…
Data & RAG
Naive RAG is dead. The agentic era demands something richer a full discipline for feeding the right knowledge, memory, and tools to LLMs at…
Data & RAG
How a reasoning-based, tree-search framework achieved 98.7% accuracy — and quietly challenged a $2.2 billion industry
Data & RAG
How a simple architectural pattern became the $11 billion standard for making AI actually useful — and how you can master it
Data & RAG
How to architect your database infrastructure for massive scale without breaking your application — or your budget
Data & RAG
Your RAG system retrieves the right documents. It matches keywords. It semantically searches vectors until it finds “relevant” chunks.
Data & RAG
Retrieval Augmented Generation has gone through one of the most dramatic shifts in the field of artificial intelligence. In the early years…
About
I write practitioner-first explainers on what's actually changing in AI: new models and benchmarks, coding agents like Claude Code, Python and the cloud tools developers use every day, and what all of it means for engineering careers.
My articles appear on Medium in publications like Artificial Intelligence in Plain English, Python in Plain English and AWS in Plain English. LogitPost collects all of them in one place, alongside pieces I publish here first.
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