Show HN: I built a local data lake for AI powered data engineering and analytics https://ift.tt/Uodh2BO

Show HN: I built a local data lake for AI powered data engineering and analytics I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You don’t have to setup local LLMs, it comes built in. This is completely free. No cloud account required. Downloading the software - https://ift.tt/J6UHuAV Watch a demo - https://www.youtube.com/watch?v=C6qSFLylryk Check the code repo - https://ift.tt/d1XPahV This is still early and I'd genuinely love your feedback on what's broken, what's missing, and if you find this useful for your data and analytics work. https://ift.tt/zvfxTBG April 9, 2026 at 02:41AM

Show HN: Skrun – Deploy any agent skill as an API https://ift.tt/J9mILFq

Show HN: Skrun – Deploy any agent skill as an API https://ift.tt/p0RxwoZ April 8, 2026 at 06:04PM

Show HN: Orange Juice – Small UX improvements that make HN much easier to read https://ift.tt/bIpNPvy

Show HN: Orange Juice – Small UX improvements that make HN much easier to read http://oj-hn.com/ April 8, 2026 at 11:38PM

Show HN: Unicode Steganography https://ift.tt/UqrizRl

Show HN: Unicode Steganography I built a demo of two Unicode steganography techniques, zero-width characters and homoglyph substitution, in the context of AI misalignment. The first is about the use of two invisible zero-width characters (ZWS and ZWNJ) to binary encode text. The second is much cooler. Most characters in the Latin and Cyrillic alphabets look nearly identical, but have different unicode. If you have text to encode and convert it into binary representation (1s and 0s), you could take plain english "carrier" text and for each 1 in the binary representation you could substitute the Cyrillic letter equivalent. Decoding the message requires traversing the text and seeing where Cyrillic letters could have been substituted but weren't, and where they were, leading to 0s and 1s respectively, which can be built back into your original hidden text. In both cases, these are detectable, but the interesting problem for me is whether an LLM could eventually invent an encoding that goes unnoticed by both us, and automated detection. If LLMs were able to covertly include messages in plaintext, misaligned AI Agents could eventually communicate across MCP/A2A and individual chat session boundaries undetected. A deceptive LLM might seem helpful, but work against your goals. It could tell other agents it interacts with over MCP/A2A to help it discreetly fail, signal intent, and avoid tripping oversight/safety mechanisms. Furthermore, oversight mechanisms become more difficult to implement if we can't believe our own eyes. https://ift.tt/OVetC9r April 7, 2026 at 06:27PM

Show HN: Marimo pair – Reactive Python notebooks as environments for agents https://ift.tt/zex5US1

Show HN: Marimo pair – Reactive Python notebooks as environments for agents Hi HN! We're excited to share marimo pair [1] [2], a toolkit that drops AI agents into a running marimo notebook [3] session. This lets agents use marimo as working memory and a reactive Python runtime, while also making it easy for humans and agents to collaborate on computational research and data work. GitHub repo: https://ift.tt/tV5Us73 Demo: https://www.youtube.com/watch?v=6uaqtchDnoc marimo pair is implemented as an agent skill. Connect your agent of choice to a running notebook with: /marimo-pair pair with me on my_notebook.py The agent can do anything a human can do with marimo and more. For example, it can obtain feedback by running code in an ephemeral scratchpad (inspect variables, run code against the program state, read outputs). If it wants to persist state, the agent can add cells, delete them, and install packages (marimo records these actions in the associated notebook, which is just a Python file). The agent can even manipulate marimo's user interface — for fun, try asking your agent to greet you from within a pair session. The agent effects all actions by running Python code in the marimo kernel. Under the hood, the marimo pair skill explains how to discover and create marimo sessions, and how to control them using a semi-private interface we call code mode. Code mode lets models treat marimo as a REPL that extends their context windows, similar to recursive language models (RLMs). But unlike traditional REPLs, the marimo "REPL" incrementally builds a reproducible Python program, because marimo notebooks are dataflow graphs with well-defined execution semantics. As it uses code mode, the agent is kept on track by marimo's guardrails, which include the elimination of hidden state: run a cell and dependent cells are run automatically, delete a cell and its variables are scrubbed from memory. By giving models full control over a stateful reactive programming environment, rather than a collection of ephemeral scripts, marimo pair makes agents active participants in research and data work. In our early experimentation [4], we've found that marimo pair accelerates data exploration, makes it easy to steer agents while testing research hypotheses, and can serve as a backend for RLMs, yielding a notebook as an executable trace of how the model answered a query. We even use marimo pair to find and fix bugs in itself and marimo [5]. In these examples the notebook is not only a computational substrate but also a canvas for collaboration between humans and agents, and an executable, literate artifact comprised of prose, code, and visuals. marimo pair is early and experimental. We would love your thoughts. [1] https://ift.tt/tV5Us73 [2] https://ift.tt/qZVonOU [3] https://ift.tt/WH2F1jC [4] https://www.youtube.com/watch?v=VKvjPJeNRPk [5] https://ift.tt/Nt1aSiG... https://ift.tt/tV5Us73 April 7, 2026 at 11:17PM

Show HN: C64 Ultimate Toolbox for macOS https://ift.tt/IEOwqsx

Show HN: C64 Ultimate Toolbox for macOS My wife got me a Commodore 64 Ultimate ( https://ift.tt/bqIsknO ) for my birthday, and it became an obvious hassle to have to keep an entire monitor connected to it just to tinker with it. When I found out the Ultimate FPGA board has built-in support for streaming the video and audio data over the network, as well as a REST API allowing for file and configuration management, I set to work on an app to remotely control my new device. - View and hear your Commodore 64 Ultimate or Ultimate 64 device over the network, with a fully configurable CRT shader so you can dial in just the right retro feel. - View and manage files on your device, including support for drag and drop folder/file upload, as well as the ability to run and mount disks, create new disk images, and more. - BASIC Scratchpad is a mini-IDE in the app where you can write BASIC apps and send them directly to any of your connected devices to run. - Keyboard forwarding allows you to interact with your device with your computer keyboard, includes a keyboard overlay for Commodore specific keys your keyboard definitely doesn't have. - Visual memory viewer and editor, along with a terminal-like memory viewer and editor for debugging and tinkering. - Built-in support for recording videos and taking screenshots cleanly. - Fully native macOS AppKit app. Here's a rough and ready demo video I recorded and sent to App Review for the 2.0 release which was approved yesterday: https://www.youtube.com/watch?v=_2wJO2wOGm8 Please note again this app only works with Commodore 64 Ultimate or Gideon's Ultimate 64 devices. Ultimate II does not have the data streams feature to power the display. https://ift.tt/Us0YBFZ April 7, 2026 at 10:09PM

Show HN: I successfully failed at one-shot-ing a video codec like h.264 https://ift.tt/CAwiMFW

Show HN: I successfully failed at one-shot-ing a video codec like h.264 Read an article yesterday about the H.264 codec increasing their licensing fee by an astronomical amount. And as always, my first shot was how hard could it be to try and build a codec which could be that efficient. I've personally been on a drive to improve my ability to one-shot complex features, products, or make even surgical changes. It's been a few months since I've been doing that, and honestly, results have been great for both work and work/life balance. This was a fun experiment. It burned through tokens, but it helped me identify some more improvements I could make to my one-shot agent teams/swarms, notably in the area of brevity and creating a testing rubric when dealing with domains I don't have prior knowledge in. Ultimately, I did not achieve the compression that I hoped I would, but it was fun seeing the swarm discuss it amongst themselves. https://ift.tt/AVsBLd6 April 4, 2026 at 05:10PM