iacguy · HN

Show HN: Durable AI agents without the workflow engine

@hijak01 · X

check out the demo

@matebenyovszky · X

I use multiple providers Claude Code, Cursor, Codex, Hermes, Antigravity etc. and multiple machines. Over time, each one ended up with its own slightly different skills and tools 😰 So I started where a playbook is a portable bundle containing my MCP/OpenAPI servers, skills, prompts, personas and memory, which I can take with me into whichever environment I’m using. I’m still trying to figure out whether this is useful beyond my own workflow. Ideas? 🤔 🍎 Source / open source on Github: matebenyovszky/agentplaybooks I also built an npm CLI that audits a project and syncs the same skills and MCP definitions across harnesses.

@v1b3_x · X

I built a persistent, Git-like memory engine for LLM agents so they never lose context across session. works with ClaudeDesktop <—> Claude Code <—> Codex

jackcollinshq · Product Hunt

YAGNI Proactive agent teams you manage like humans

@vitverb · X

hi :) One tap back to the work you meant to finish. No tasks to manage. Nothing to set up. Local-first

u/Funky_Chicken_22 · Reddit

OSS to SaaS positioning problem: when the user persona and the buyer persona are completely disjoint Founder here. Sharing a positioning problem I think a lot of OSS-to-SaaS founders hit and don't talk about publicly. Context: I have been running an OSS project (world-model-mcp) with ~2,500 monthly PyPI installs. Two weeks ago I opened up the hosted companion, Etch, at etch.systems. Launched publicly on Product Hunt at 12:00 PDT yesterday. The positioning problem: OSS user persona: in

gb2d_hn · HN

It was with the transience of valuable agent session dialogue in mind that I built https://www.agentkanban.io - A key feature is context capture in the tasks which you create on the board and then progress in agent sessions. Supported agents are currently Claude and Github CoPilot in VS Code. All of your context is captured in the task and can be reloaded into new agent sessions at any point in the future. Tool use is intentionally discarded because it is proprietary in nature and therefore brea

u/OGMYT · Reddit

I built LOLM, a lower-cost LLM agent that shows what it actually did — looking for blunt feedback I’m one of the founders/builders behind LOLM. Most AI products show an answer but hide whether the system retrieved anything useful, verified the result, switched models, hit a limit, or simply stopped. LOLM exposes those parts through controller events and run receipts. It includes: - Live agent - CLI - Coding and small app-building workflows - Memory and self-hosting options - Control decis

matt413 · HN

Schedule tasks for your AI agents from Google Calendar

screm · HN

Product analytics (and evals) for agent sessions on your MCP

@guru3s · X

IMF team for when your AI agent ( Ethan Hunt ) is about to fail v0 at