diff --git a/contributors/sania-gurung.json b/contributors/sania-gurung.json index a0738892..74d2a0ef 100644 --- a/contributors/sania-gurung.json +++ b/contributors/sania-gurung.json @@ -6,5 +6,5 @@ "skills": ["machine-learning", "opencv", "pytorch", "sql", "data-preprocessing", "tensorflow", "neural-networks", "java", "deep-learning", "scikit-learn", "computer-vision", "pandas", "ollama", "python", "nlp", "numpy", "llm", "object-detection", "keras", "data-science"], "interests": ["agents", "NLP", "AI-pipelines","LLMs"], "track": "A: Agent Builders", - "my_twin": "I'd track the gap between when I sit down to work and when I actually start — because some days I open my laptop and I'm writing code within minutes, and other days I spend an hour rearranging tabs and convincing myself to begin. I suspect it has something to do with how the previous day ended, whether I finished something or left it half-done, but I've never had the data to confirm it. I want to know if that pattern is real, and if it is, I want to catch it before I waste another morning." + "my_twin": "I'd track the gap between sitting down and actually starting — because some days I'm deep in code within minutes, and other days an hour slips by before I've written a single line. My hunch is that it comes down to how the previous session ended: finishing something cleanly versus leaving things mid-thought. I've never had the data to know if that's true, and I want to find out before I keep losing mornings to it." } diff --git a/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/agentic-ai-one-pager.pdf b/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/agentic-ai-one-pager.pdf new file mode 100644 index 00000000..f5fe6324 Binary files /dev/null and b/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/agentic-ai-one-pager.pdf differ diff --git a/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/prompts.md b/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/prompts.md new file mode 100644 index 00000000..c1524375 --- /dev/null +++ b/submissions/sania-gurung/assignments/AI AGENTS-taxonomy and ontologies/prompts.md @@ -0,0 +1,21 @@ +# AI Agents — Taxonomy and Ontologies: Research Prompts + +These are the prompts I used when researching AI agents, how we classify them, and how we map their relationships. I typed these into Claude and used what came back to write my three one-pagers. + +--- + +## Prompt 1 + +> Can you explain what an AI agent actually is in plain English — like what makes something an agent and not just a regular program or chatbot? Then tell me about the main frameworks people use to build them: LangChain, LangGraph, CrewAI, and AutoGen. For each one I want to know what it was originally built for and honestly where it fails or causes problems — not just the good stuff. + +--- + +## Prompt 2 + +> I want to understand how people categorize or classify AI agents. What are the different ways you can sort them — like by how they work with other agents, how much they do on their own without a human, and what kind of environment they run in? Is there something important that nobody in the AI industry is really talking about when it comes to classifying these systems? + +--- + +## Prompt 3 + +> Help me understand all the things an AI agent is connected to and how those connections work. I mean things like — how does it use memory, how does it interact with tools, how does it relate to other agents around it, how do you keep track of what it did and why, and who or what controls what it is allowed to do? For each of these I want to know what is usually missing or not handled well in the frameworks people are using today. diff --git a/submissions/sania-gurung/assignments/README.md b/submissions/sania-gurung/assignments/README.md new file mode 100644 index 00000000..ce9bef83 --- /dev/null +++ b/submissions/sania-gurung/assignments/README.md @@ -0,0 +1,37 @@ +# Assignments — Sania Gurung + +**Submission for:** LPI Developer Kit Program +**Author:** Sania Gurung +**Email:** saniagurung5452@gmail.com + +--- + +## Assignments + +### 1. AXON Networks (`axon-networks/`) + +**Files:** `axon-networks-one-pager.md` · `axon-networks-one-pager.pdf` · `prompts.md` + +Research into AXON Networks and their NEURA platform, covering: + +- **What AXON Actually Does** — NEURA as a closed-loop telecom automation system built on a digital twin, sold as Operations-as-a-Service (OaaS) +- **Geopolitical Dimension** — What it means when a foreign AI system autonomously controls a country's critical telecom infrastructure; AI sovereignty and long-term dependency risk +- **Security Vulnerabilities** — Agent hijacking via telemetry manipulation, digital twin breaches, and multi-tenant isolation failures +- **Build vs Buy** — Why domain-specific infrastructure demands proprietary builds, and when open-source is enough + +--- + +### 2. AI Agents — Taxonomy and Ontologies (`AI AGENTS-taxonomy and ontologies/`) + +**Files:** `agentic-ai-one-pager.md` · `agentic-ai-one-pager.pdf` · `prompts.md` + +Deep research into what AI agents are, how we classify them, and how to model everything they connect to, covering: + +- **Framework Comparison** — LangChain, LangGraph, CrewAI, and AutoGen — what each was built for and where each breaks in practice +- **Taxonomy — Three Dimensions** — Coordination style (solo → swarm), autonomy level (L1–L5), and deployment context (digital → embodied) +- **The Missing Dimension** — Consequence severity: the industry classifies agents without accounting for how bad the worst-case failure looks +- **Ontology — Agent Relationships** — Memory, tools, environment, agent-to-agent trust, audit layer, and runtime governance — and what's missing in each + +--- + +*Last updated: May 2026* diff --git a/submissions/sania-gurung/assignments/axon-networks/axon-networks-one-pager.pdf b/submissions/sania-gurung/assignments/axon-networks/axon-networks-one-pager.pdf new file mode 100644 index 00000000..864b8e04 Binary files /dev/null and b/submissions/sania-gurung/assignments/axon-networks/axon-networks-one-pager.pdf differ diff --git a/submissions/sania-gurung/assignments/axon-networks/prompts.md b/submissions/sania-gurung/assignments/axon-networks/prompts.md new file mode 100644 index 00000000..e1cd5b35 --- /dev/null +++ b/submissions/sania-gurung/assignments/axon-networks/prompts.md @@ -0,0 +1,27 @@ +# AXON Networks — Research Prompts + +These are the prompts I used when researching AXON Networks. I just typed these into Claude and used the responses to build my understanding and write the one-pager. + +--- + +## Prompt 1 + +> I keep hearing about AXON Networks as some kind of telecom AI company but I have no idea what they actually do. Can you break it down for me simply — what is their NEURA product, what is a digital twin in this context, and what does Operations-as-a-Service mean for a telecom company that uses them? Also how is what they built any different from just plugging in LangChain or AutoGen? + +--- + +## Prompt 2 + +> AXON Networks is doing something with Cassava Technologies across African countries. Why does that actually matter beyond just being a business deal? I want to understand — if a foreign AI company is running your country's internet infrastructure autonomously, what does that mean for that country? Is this a good thing or should people be worried? + +--- + +## Prompt 3 + +> What could actually go wrong if an AI is running a live telecom network on its own with no human approving every decision? Like what would a real attack look like — could someone trick it with fake data, what happens if the digital copy of the network gets hacked, and how does sharing infrastructure across multiple telecom companies make things riskier? + +--- + +## Prompt 4 + +> Should companies just build their own AI agent framework from scratch like AXON did, or is it better to use something like LangChain or AutoGen that already exists? What are you actually giving up or gaining on each side? Is there a way to do both — use open-source for some parts and build your own for the bits that really matter?