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arkaigrowth/README.md

Hey, I'm Alex

I build agentic systems the way you'd build any production system: deterministic cores, agentic edges. The predictable parts run as tested code with real contracts (exit codes, schemas, golden cases). The models handle judgment and ambiguity at the boundaries, and nothing they touch gets trusted without a gate.

Day job: AI Ops at a PIM/DAM SaaS company, where I run agentic automation across product data operations. Nights and weekends: the repos below :-)

What that looks like in practice

arkai Rust orchestration kernel for AI workflows. Event-sourced, resumable pipelines with strict safety and cost controls.
gmail-mcp-server Multi-account Gmail MCP server built security-first: macOS Keychain token storage, injection-safe process exec, attachment quarantine, and two-step confirmation before anything destructive. 69 tests green.
pangram-fit An AI-detection fitness loop with a deterministic fabrication gate. The detector scores the rewrite; a red-teamed claims-diff flags invented facts before they win. 400+ tests, stdlib-only.
eval-factory Evidence-backed improvement lifecycle for agent tooling: a real state machine (captured to promoted), fingerprint dedup, blind-eval gates, and hash-verified promotion receipts. Agents that modify their own tools need audit trails.
agent-skills Nine skills and a command pack in daily use: tiered repo security scanning, LLM-output validators, agent-fleet safety guardrails, credential hygiene, and more.
rlm MCP server implementing Recursive Language Model patterns: treat 10M+ token contexts as external variables instead of stuffing the window. Based on MIT research.

How I work

  • Contracts before vibes. Every pipeline node gets a verifiable interface: JSON schemas, typed exit codes, golden-case tests. If an agent performs the same transformation twice, it becomes a script.
  • Adversarial by default. Multi-model review (Claude and GPT cross-checking each other), refute-first verification passes, and fabrication gates on anything an LLM claims.
  • Security is a feature. Prompt-injection hardening, least-privilege tool access, quarantined untrusted input, and human approval gates on irreversible actions show up in everything I ship.

Elsewhere

Building Arkai tooling in the open. Say hi on LinkedIn.

Pinned Loading

  1. arkai arkai Public

    Arkai is a Rust-based orchestration kernel for AI workflows. It coordinates tools like Fabric, RAG systems, and schedulers using event-sourced, resumable pipelines with strict safety and cost contr…

    Rust 2

  2. eval-factory eval-factory Public

    Evidence-backed improvement lifecycle for AI agent skills: a real state machine, fingerprint dedup, inline-secret scanning, and hash-verified promotion receipts with a required human gate.

    Python

  3. agent-skills agent-skills Public

    Nine production Claude Code skills and one command pack: repo security scanning, LLM-output validators, agent-fleet guardrails, credential hygiene. Deterministic cores, agentic edges.

    Python

  4. gmail-mcp-server gmail-mcp-server Public

    Security-first multi-account Gmail + Workspace MCP server: macOS Keychain token storage, injection-safe exec, attachment quarantine, two-step confirmation before anything destructive.

    TypeScript

  5. pangram-fit pangram-fit Public

    Treat an AI-text detector as a fitness function for rewriting, with a deterministic claims-diff that flags fabricated facts against the source. Zero runtime deps, shell-first, for Claude Code and C…

    Python

  6. rlm rlm Public

    Recursive Language Model MCP server — handle 10M+ token contexts by treating them as external variables. Based on MIT research (arxiv 2512.24601).

    Python