Show HN: Wazear – A visual AI orchestrator where agents review each other https://ift.tt/3Br8Uuo

Show HN: Wazear – A visual AI orchestrator where agents review each other Hey folks, For the past month I've been working on a visual AI orchestartor tool that allows users to create a pipeline similar to SDLC. Basically you fire up Wazear, create a project and add your brief. You select the agents (each agent serves a role such as planner, architect, etc...) and set which agent reviews which other agent's work and let it do the work. At any point you can pause the pipeline to review output yourself. You can check it out here: https://wazear.space . Any feedback is welcome. Thank you very much. Best Regards. April 3, 2026 at 04:52AM

Show HN: I thought merging two photos with AI would be a weekend project. Nope https://ift.tt/MG1n6jI

Show HN: I thought merging two photos with AI would be a weekend project. Nope At a friend's gathering, someone mentioned wanting to add her late father into a family photo. I figured this would be trivial — modern image models are powerful, just send two photos and ask the AI to merge them. She said she'd tried, but the results were weird and unstable, and she didn't know how to describe what she wanted. I went home and tried it myself. With a well-written prompt and two good photos, it works. But real-world use cases aren't two good photos — it's a modern family photo plus a damaged old portrait, or two old photos from different decades. That's when things fall apart. I looked at existing tools. Most showcase merges between clean, well-lit, modern photos. Nobody was solving the hard version: mismatched eras, damaged sources, different poses, different formality levels. I thought it would be a weekend project — one system prompt and done. After 200+ test iterations I realized stable results require much more than prompt engineering. The main challenges: The AI subtly changes faces during merging. The result looks "similar" but isn't the same person. For someone trying to add a deceased loved one, that's a complete failure. Posture and scale need to match. If the group is sitting on grass and the added person is standing like a giant, it's obviously fake. Casual accessories from a reference photo break formal scenes — sunglasses on the head at a wedding, sportswear at a ceremony. Old photos have low resolution, damage, and no color. Merging, restoring, and colorizing at the same time makes everything harder. It supports headshots, half-body, and full-body reference photos. Old and damaged photos work too — with optional colorization and restoration. Still an MVP. Free to use once per day, no login required. https://ift.tt/BqK79zC Would love to hear about edge cases that break it. https://ift.tt/BqK79zC April 3, 2026 at 03:32AM

Show HN: Minimal Brain Teaser Web Game (Handcrafted, No AI) https://ift.tt/8LyNj1G

Show HN: Minimal Brain Teaser Web Game (Handcrafted, No AI) Built and open-sourced in the era before AI. I’m sure you know where to find the code. https://mehuleo.github.io/encircle/ April 3, 2026 at 01:00AM

Show HN: NASA Artemis II Mission Timeline Tracker https://ift.tt/8LF6JME

Show HN: NASA Artemis II Mission Timeline Tracker https://ift.tt/AaXpbi0 April 2, 2026 at 12:40AM

Show HN: Linux Kernel Documentation Index-Every Page in the Linux Kernel's Docs https://ift.tt/knlEQyX

Show HN: Linux Kernel Documentation Index-Every Page in the Linux Kernel's Docs https://ift.tt/2OpPtC7 April 1, 2026 at 11:39PM

Show HN: DreamGraph MCP v5 – An open source autonomous cognitive layer https://ift.tt/Swk6bt9

Show HN: DreamGraph MCP v5 – An open source autonomous cognitive layer https://ift.tt/8IuNdvf April 1, 2026 at 07:16AM

Show HN: TraceLit – debug LeetCode step by step https://ift.tt/oyhc8zX

Show HN: TraceLit – debug LeetCode step by step I built TraceLit because I was tired of manually dry-running LeetCode problems, especially trees and recursion problems where it’s easy to lose track of execution. You paste code and input, run it, and step through execution line by line. It helps you see variable changes, control flow, and where things start going wrong. It’s especially useful for recursion, trees, linked lists, and simulation-style problems. You can try it here: https://tracelit.dev No signup required. I’d love feedback on which problem types this feels most useful for, and what feels confusing. https://tracelit.dev/ April 1, 2026 at 04:36AM