Open to opportunities

Moses Man

Agentic Prompt-Driven Developer

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I approach projects with an engineering-first mindset: understand the constraints, architect a solution, build something that holds up under real conditions. Most of my work starts as a problem I encounter directly, then I iterate until the system is reliable enough to depend on.

Currently focused on agentic AI systems and the infrastructure that makes them work in practice, not just in demos. Longer term, I'm working towards quantum engineering, where computation, physics, and mathematics all intersect.

0 Active Projects
0 Public Commits live
0 Infra Stack Layers
0 Certifications
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01
Profile

About

I'm Moses, a Year 11 student based in the UK with a specific interest in systems that are both technically correct and operationally reliable. That means I care about things like error handling, API rate limits, network segmentation, and whether the agent actually degrades gracefully when a tool call fails at 2 a.m.

Most of my projects start as a concrete problem I run into: Oracle Cloud provisioning errors, agent orchestration that breaks on edge cases, or networking configs that need real traffic to validate. I prototype quickly in Python, then harden the parts that matter.

My interest in quantum engineering isn't a vague aspiration - it's a long-term direction that motivates what I learn now: linear algebra, computational complexity, low-level systems programming, and the physics that underpins quantum information. I'm building the technical vocabulary today so I can work at that front when the time comes.

I'm also an agentic prompt-driven developer: I design systems where AI agents coordinate tools, handle failures gracefully, and execute multi-step workflows under real constraints — not just single-shot chat interactions. PolyBrain, PolyGnosis, and my homelab infrastructure all reflect that philosophy: build the orchestration layer first, then let the agents do meaningful work.

A

Systems Thinking

I care about how components interact, not just what they do in isolation.

B

Iterative Engineering

Prototype, stress-test, fix, repeat. No demo-grade projects.

C

Quantum Path

Building foundations in maths, physics, and computation for quantum engineering.

02
Selected work

Featured Projects

01

OCI OcC Fix

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A purpose-built Python utility that addresses the OCI console provisioning bottleneck, specifically, the persistent "Out of capacity" error that blocks ARM instance creation. It automates the retry workflow instead of requiring manual console polling.

  • Automated provisioning retry loop with configurable backoff strategy
  • Eliminates manual console interaction for repeated provisioning attempts
  • Minimal configuration surface - designed to run with a single command
Python Oracle Cloud Infrastructure Automation
View on GitHub
02

PolyBrain - LatticeAG

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An AI agent orchestration framework that coordinates multiple tool calls, LLM invocations, and workflow state as a coherent system - rather than treating each interaction as an isolated prompt-response pair. Built on LatticeAG infrastructure.

  • Multi-step agentic workflows with structured tool-delegation and subagent orchestration
  • Protocol-based tool definitions enabling composability across different backends and contexts
  • Error-handling and retry logic at the orchestration layer, not just at individual tool calls
Python AI Agents Orchestration LatticeAG
View on GitHub
03

PolyGnosis - LatticeAG

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An adversarial multi-model consensus protocol for Hermes Agent. Three or more frontier models solve independently from dynamically assigned expert personas. A critic cross-reviews every solution. Formal ranking algorithms produce mathematically sound consensus. A constitutional quality gate prevents synthesis regressions.

  • Parallel solve phase with 3+ model families, dynamic persona generation from problem context
  • Adversarial critique phase — a hostile model hunts bugs, hallucinations, and security flaws per solution
  • Formal consensus via Reciprocal Rank Fusion and Borda Count, plus a constitutional quality gate
Python AI Agents Consensus Protocol LatticeAG
View on GitHub
04

Homelab

Ongoing

A deliberately minimal but functionally dense homelab environment where I learn networking, self-hosting, and service reliability through running real infrastructure at home - proper network-segmented services with policies.

  • OPNsense routing and firewall rules - real traffic, real policies, real debugging
  • OpenMediaVault for storage with backup strategies that prioritise reliability over capacity
  • Cloudflare integration for DNS and controlled HTTPS exposure beyond the LAN
  • Home Assistant for device automation with a focus on reliability and local-first execution
OPNsense OpenMediaVault Cloudflare Home Assistant Networking
03
Infrastructure

Homelab / Network

My homelab exists because network diagrams don't teach you how traffic actually behaves under pressure. It started with an OPNsense box and grew into a small environment that exercises the full stack: routing, firewalling, DNS, storage, backups, device automation, and controlled external access.

Every service running here was chosen because it forced me to understand something specific: OPNsense for traffic flow and policy enforcement, OpenMediaVault for storage reliability and backup discipline, Cloudflare for DNS and secure edge exposure, and Home Assistant for tying automations into something that maintains itself. The point isn't to have a homelab - it's to build genuine operational understanding by running systems that have consequences when they break.

OPNsense

Routing, firewalling, VLAN segmentation, and real traffic monitoring. Hands-on network security.

OpenMediaVault

NAS, storage pools, and backup automation. Data reliability as a first-class concern.

Cloudflare

DNS management, HTTPS tunnel exposure, and controlled external access beyond the LAN.

Home Assistant

Device automation, sensor aggregation, and local-first orchestration with cloud fallbacks.

Network Topology

Click any node to expand details. Animated lines show traffic flow.

VPS Internal

04
Experiment

Playground

Run Python directly in your browser with Pyodide — no backend, no install. Edit the snippet and hit Run.

Output
Click Run to execute Python in the browser.
05
In progress

What I'm Working On

My GitHub history reflects how I actually develop: small, verifiable commits that represent real problem-solving, not bulk pushes designed to look productive. Each commit in PolyBrain or OCI OcC Fix corresponds to a specific bug fix, an architecture decision, or a new capability I needed for my own workflows.

Next on my list: going deeper into the mathematical foundations needed for quantum engineering - linear algebra, probability theory, and computational complexity - while continuing to build out the orchestration capabilities in PolyBrain.

Recent GitHub Activity live

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Contribution Focus

PolyBrain
PolyGnosis
OCI OcC Fix
Homelab
Study
Latest Commit live
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Most Active Repo live
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06
Capabilities

Technical Skills

Languages & Software

Python (primary)

Python across all projects - scripting, API orchestration, automation, and agent development. Focused on building reliable, production-oriented tools in the language I know best.

AI & Agent Systems

LLM API Integration Tool Delegation Agentic Workflows Multi-step Orchestration

Building AI agents that coordinate tools and handle real-world errors, not just single-prompt interactions. Focused on systems that work in production conditions.

Infrastructure & Networking

OPNsense OpenMediaVault Cloudflare Home Assistant Git & GitHub Actions Docker & Self-Hosting

Practical experience with network segmentation, firewall policy enforcement, storage reliability, and service automation through daily homelab operation.

Future Direction

Quantum Mechanics Foundations Linear Algebra Computational Complexity

Building the technical vocabulary - in mathematics, physics, and low-level computing - needed to work credibly in quantum engineering when the field matures.

07
Credentials

Certifications & Learning

Issued

Generative AI Essentials: Using LLMs to Work with Data

IBM
Apr 2026
LLMs Generative AI Data
Issued

Getting Started with Cybersecurity

IBM
Apr 2026
Cybersecurity Threat Analysis
In Progress

GitHub Foundations Certification

GitHub
Git GitHub
In Progress

Basics of Quantum Information

IBM
Quantum Computing Quantum Information Qubits
In Progress

Cisco Certified Network Associate (CCNA)

Cisco
Networking VLAN Routing
08
Writing

Latest Posts

Recent activity from my LinkedIn - technical notes, project updates, and things worth sharing.

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09
Reach out

Get in Touch

I'm always interested in conversations about AI systems, infrastructure, quantum computing, or anything technically adjacent. If you have an opportunity, a collaboration idea, or a question about something I've built - reach out on LinkedIn.

Moses Man

linkedin.com/in/moses-man

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