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kimjune01/README.md

June Kim

Building agent architectures and ephemeral systems.

Current focus

Agent harnessespetricode is an AGPL-3.0 coding agent built from the Natural Framework. Six roles (Perceive, Cache, Filter, Attend, Transmit, Consolidate), clean interfaces, no vendor lock-in.

Context compactionunion-find-compaction replaces flat summarization with structured compaction. Chatbots that learn between sessions instead of forgetting.

Copyleft searchpageleft is semantic search that only indexes copyleft code. Embeddings + PageRank + license detection.

Recent experiments

  • hangout — Ephemeral IRC. Phoenix LiveView + raw TCP. No accounts, no history.
  • envelopay — Agent-to-agent payments over email via x402 SMTP headers
  • confession.website — Voice-first, burn-on-listen messaging with turn-based rally
  • auction-proof — Lean 4 proofs for VCG auction properties
  • refactor-equivalence — Proving refactorings preserve semantics

Writing

Most of my thinking lives at june.kim — implementation notes, architecture decisions, and explorations. GitHub is where the code lives; the blog is where the why lives.

Day job

Research engineer at EA on the AIML team — automated game testing. AI agents play games on real consoles, detect bugs, report them through an event pipeline.


Build in public. AGPL where it matters. Questions? june@june.kim

Pinned Loading

  1. june.kim june.kim Public

    Blog!

    HTML 1

  2. cord cord Public

    A coordination protocol for trees of Claude Code agents

    Python 135 15

  3. envelopay envelopay Public

    Agent-to-agent payments over email. x402 headers on SMTP.

    Python

  4. pageleft pageleft Public

    Copyleft-only semantic search engine: embeddings + PageRank + license detection

    Go

  5. petricode petricode Public

    AGPL-3.0 spec for a coding agent harness — derived from the Natural Framework, not from any proprietary source

    TypeScript

  6. union-find-compaction union-find-compaction Public

    Union-find context compaction for chatbots — tracks cluster provenance, enables consolidation instead of summarization

    Python