Rogerio Chaves (@_rchaves_) on X (Twitter)

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Rogerio Chaves is a creator on X (Twitter) in the 2K–3K follower range, publishing for AI agent builders and developers focused on monitoring token usage and controlling costs in agent workflows, based in Netherlands. Profile last checked 2026-06-25.

Observed facts (from the public profile):

Profile bio

Building LangWatch: https://t.co/ez7kW1C6z9 create-agent-app: https://t.co/UZVdkdZDpz

What this creator posts about, and who reads it (AI-inferred)

Recurring topics: token cost optimization for agents, context window traps, agent observability and monitoring, LangWatch product promotion

Audience: AI agent builders and developers focused on monitoring token usage and controlling costs in agent workflows

Provenance: inferred by AI from public content, not stated by the creator — confidence 0.40 · read from 3 recent posts · updated 76 days ago.

Audience read from this creator’s own recent posts, not from platform-declared categories. It is our reading, and it can be wrong.

Recent content samples (what the inference above was drawn from)

1M CONTEXT WINDOW IS A TRAP BY BIG AI TO MAKE YOU SPEND MORE ON TOKENS tl;dr: we did an analysis with 2,451 agent sessions, each 2x context size added costs 6x the tokens, even cached, with no evidence that earlier…

If you want to stop BigAI from sneakily increasing token cost, support us on product hunt

Claude Code very smart. Claude Code make code. Claude Code also make bill. Big bill. -But where token go? -Did cache work? -What tool agent use? -Why agent spend 20 minutes fighting one login command? -Why agent call…

See the original post on X (Twitter)

Where this creator sits among comparable accounts

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Koinon Link indexes X (Twitter) creators in Software with grade, authenticity and contactability broken down — see the X (Twitter) × Software breakdown, or the Creator Index Report for the whole index.

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Creators next to this one by follower tier in the same slice. Each link opens that creator’s public profile — what they post about and who reads it, with no contact details.

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Machine-readable representations

Structured twins of this page for AI and agents — every inferred field carries its source, confidence and freshness.

• /kol/x/_rchaves_.json
• /kol/x/_rchaves_.md

AI retrieval activity

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