BaaS to build agents as data, not code
Agents and workflows as data instead of code. Julep is a backend-as-a-service to build agents and workflows. Main features: 1. Experimentation Velocity: With most agent frameworks, agents are code that need to be deployed. To iterate on the prompts or update the agent, you need to make changes to the code and deploy it to your server. This makes agents hard to iterate on quickly. But with agents and tasks declared as data, all that happens in the background is make an api call to update or make a new entry in the database. This increases the experimentation velocity. 2. Scalability and…
What it does
In the maker’s words, at launch
Agents and workflows as data instead of code. Julep is a backend-as-a-service to build agents and workflows. Main features: 1. Experimentation Velocity: With most agent frameworks, agents are code that need to be deployed. To iterate on the prompts or update the agent, you need to make changes to the code and deploy it to your server. This makes agents hard to iterate on quickly. But with agents and tasks declared as data, all that happens in the background is make an api call to update or make a new entry in the database. This increases the experimentation velocity. 2. Scalability and long-running background tasks: Scaling is a hard software engineering problem and the solution is to define large scale systems to be distributed, stateful and scalable. Agents as data is a very helpful paradigm because you have to solve for this problem only once at the orchestrator level. Julep can handle 100s of thousands of executions paralely. 3. Updating an agent / User Personalization: Tools such as create agent, update agent etc. can update the agent recursively. Let’s assume an agent is chatting with a user and mentions that they only like to communicate in a professional tone. The agent can call a tool to 'update the agent' and modify/update the instructions to include that the user only likes to communicate in a professional tone. This was the reason to create a backend when the market was flooded with agent frameworks. In Julep, you can declare a workflow in YAML, and it can automatically scale Millions of users.
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Launched alongside, August 2025
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I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images. https://kilopx.com/
Work · 2025 · benholmen.com
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Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters. This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg. raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required! We're releasing this to give early users a sense of the latency and voices…
Dev tools · 2025 · github.com
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I was wondering how I can arrange objects along a spherical helix path, and read some articles on it. I ended up learning about parametric equations again, and make this visualization to document what I learned: https://visualrambling.space/moving-objects-in-3d/ feel free to visit and let me know what you think!
Life & fun · 2025 · visualrambling.space
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For HTML Day 2025 [1], I made a web service that displays the current sky at your approximate location as a CSS gradient. Colours are simulated on-demand using atmospheric absorption and scattering coefficients. Updates every minute, without the use of client-side JavaScript. Source code and additional information is available on GitHub: https://github.com/dnlzro/horizon [1] https://html.energy/html-day/2025/index.html
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