In this tutorial, we build a lightweight personal AI agent inspired by the architecture of nanobot, runnable entirely in Google Colab. We start from a provider abstraction, then add tool registration, session memory, lifecycle hooks, skills, and an MCP-style tool server. Rather than rely on an external framework, we recreate each building block ourselves to see how messages, tools, memory, and model responses fit together. The result is a provider-agnostic agent loop we can extend toward real LLM providers and production tools.
The post Build a Nanobot-Style AI Agent in Google Colab with Tool Calling, Session Memory, Skills, and MCP Servers appeared first on MarkTechPost.
In this tutorial, we work with NVIDIA's Open-SWE-Traces dataset to study agentic software-engineering trajectories for fine-tuning. We stream the data directly from Hugging Face, so we can process it efficiently in Google Colab without downloading everything locally. We normalize multi-turn agent conversations, parse final code patches, and build an analysis DataFrame covering trajectory length, tool usage, patch size, language distribution, and resolution outcomes. We then curate a supervised fine-tuning subset using success labels, token limits, language filters, and patch availability.
The post Building Supervised Fine-Tuning Data from NVIDIA Open-SWE-Traces: Trajectory Parsing, Patch Analysis, Token Budgets, and Tool-Use Metrics appeared first on MarkTechPost.
AI-driven match analysis could level the playing field, enhancing strategic insights for all teams, but may also intensify competitive pressures.
The post FIFA gives every 2026 World Cup team a bespoke AI agent for match analysis appeared first on Crypto Briefing.
In this tutorial, we build an OpenHarness style agent harness from scratch to see how a practical agent system works. We recreate the core building blocks: tool use, typed tool schemas, permissions, lifecycle hooks, memory, skills, context compaction, retry logic, cost tracking, and multi-agent coordination. We expose the full control flow instead of treating the framework as a black box. We keep everything runnable so we can experiment without API keys or extra infrastructure.
The post How to Design an OpenHarness Style Agent Runtime with Tools, Memory, Permissions, Skills, and Multi-Agent Coordination appeared first on MarkTechPost.
Tencent's Dayuan AI could revolutionize enterprise communication by enhancing efficiency and context-awareness, impacting business operations.
The post Tencent prepares to launch Dayuan AI agent for WeCom app rollout appeared first on Crypto Briefing.
A new benchmark designed to test strategic reasoning found an AI-controlled empire spent 50 turns developing nuclear weapons to stop a rival's cultural victory—only to lose the game anyway.
