Comparisons
Migrating from Pinecone to TheoRAG
An honest comparison of running RAG with Pinecone vs TheoRAG built into TheoKit. What works, what does not yet, and how to migrate gradually.
Paulo HenriquePosts
Paulo Henrique
Comparisons
Modal vs TheoCloud for AI agents
Modal is excellent compute-as-a-service. TheoCloud is an agent-shaped runtime. When to pick which for your AI agent workload.
Paulo Henrique
Comparisons
TheoMemory vs Mem0 — honest tradeoffs
Mem0 is a category leader in agent memory. TheoMemory is the memory layer of the Theo ecosystem. Honest comparison of what each one does best.
Paulo Henrique
Engineering
Memory and Context: the unidirectional rule that holds it together
Memory → Context, never the reverse. Four design rules (D1–D4) from cross-validating 12 production implementations — and the failure mode each one prevents.
Paulo Henrique
Engineering
Five stages of gradual context compaction
Compacting the whole context at 50% is wasteful. Waiting until 99% triggers Context Rot. The middle path is a five-stage pipeline that stops at the first stage that resolves the pressure.
Paulo Henrique
Engineering
Progressive disclosure: how to give an agent 200 tools without breaking it
Frontloading every tool schema works up to 10 tools. After that, accuracy collapses. Progressive disclosure inverts the default — Anthropic reports 134K → 8.7K tokens and 49% → 74% accuracy on Opus 4.
Paulo Henrique
Engineering
The five components of an agent memory system
A memory layer is not just a vector store. The taxonomy that emerges from production implementations and the CoALA paper is five components — Store, Write, Recall, Dream, Auxiliary LLM — and they cooperate in a continuous loop.
Paulo Henrique
Launches
Welcome to Engineering at Theo
Why we're starting an engineering blog now, what to expect, and how this fits into the larger Theo story.
Paulo Henrique