IBM Champion tests IBM Bob coding agent with daily-digest POC
An IBM Champion built a proof-of-concept daily digest using IBM Bob, IBM's coding agent, to pull and summarize articles from IBM RSS feeds and a YouTube channel. The user, who normally uses Cursor and Claude Code, found the tool adequate for ordinary app-building tasks, contrasting with Bob's typical mainframe modernization use case.
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AI news aggregator agent that filters and summarizes
An agent that automatically collects AI news from multiple sources, filters out noise, and provides concise summaries. It uses LLMs to understand user interests and generate personalized digests, saving time for professionals who need to stay informed without constant scrolling.
Harness engineer reports easy creation of complex AI agents for multi-step automation
A harness engineer on Reddit describes how they can now create agents in hours that automate long, multi-step workflows, including generating an AI video series where each character is sourced from five different models. The post highlights the growing accessibility of agentic AI for practical automation.
Developer shares an agent in 100 lines of Lisp
A developer posted a minimal agent implementation in 100 lines of Lisp on Hacker News, sparking discussion about lightweight agent design. The post received 82 points on July 7, 2026, highlighting community interest in compact, interpretable agent code.
Collection of 48 working AI agent examples in Python and TypeScript
A curated repository of 48 functional AI agent implementations covering common patterns like research, code review, SQL, data analysis, and web scraping. Each example is designed to be cloned and run immediately, solving the problem of broken or incomplete agent tutorials for developers building AI systems.
abap_wiki: Agent-driven engine turns SAP S/4HANA custom objects into citable Markdown/Obsidian knowledge base
A new open-source tool, abap_wiki, uses AI agents to extract SAP/ABAP custom objects from S/4HANA systems and convert them into citable Markdown/Obsidian pages. The engine aims to create a verifiable, AI-native knowledge base for both humans and AI agents, differentiating itself from simple RAG by providing structured, citable context. The project includes a measured benchmark for model selection.