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For engineering teams who verify a claim by running it

Project, Agentic AI, Multi-Agent, Orchestration

Agentic Orchestration Platform

Home-Lab Agent Fleet — deterministic verification gate, private fork of exo (open-source distributed inference), with an ops-hardening branch

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Agentic AI deployments fail without a deterministic verification layer — hallucination drift, no adversarial hardening. Most orchestration layers publish no replay evidence at all.

Topographic data-mesh backdrop in navy and royal blue
Agentic AIMulti-AgentOrchestrationDeterministic Replay
171/177
Adversarial prompts caught, on its own synthetic corpus (n=284, written for the repo)
Industry
Independent / open source
Duration
home lab, ongoing
Roles
7 qualified
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The Problem

Agentic AI deployments fail without a deterministic verification layer — hallucination drift, no adversarial hardening. Most orchestration layers publish no replay evidence at all.

Approach

Built a multi-agent verification council: each agent specializes in a failure mode (prompt injection, boundary probe, distribution shift, context window overflow). The inference substrate is my private fork of exo (open-source distributed inference), with an ops-hardening branch; walkthrough on request.

PythonQdrantexo ringMLXOpenAI-compat API

Proof Metrics

171/177Adversarial attempts caught, on its own synthetic corpus (n=284, written for the repo)github.com/mpuodziukas-labs/llm-adversarial-gate — clone & verify

Want this on your team?

This work maps to 7 qualifying roles. Remote, open to mid-level and senior IC roles.