A high-level search agent
Hi HN — we’re building high-level capabilities for AI applications at Gensee: packaged tooling + infra that remove brittle low-level plumbing so teams can focus on their product’s real job. After speaking with many AI developers and experiencing it ourselves, we found that building agents requiring web content is often bottlenecked on the “search” part, as it involves iterations of search, crawl, extract, re-query, and error handling. We package all these search-related low-level details in an efficient and more intelligent way, so AI builders can get back to work on their core agent ideas.…
What it does
In the maker’s words, at launch
Hi HN — we’re building high-level capabilities for AI applications at Gensee: packaged tooling + infra that remove brittle low-level plumbing so teams can focus on their product’s real job. After speaking with many AI developers and experiencing it ourselves, we found that building agents requiring web content is often bottlenecked on the “search” part, as it involves iterations of search, crawl, extract, re-query, and error handling. We package all these search-related low-level details in an efficient and more intelligent way, so AI builders can get back to work on their core agent ideas. What Gensee Search Agent is behind the single API call: - Web searching + crawling + browsing - Built-in error handling + retries/fallbacks - Breadth-first search approach to search in parallel and rule out bad results early on - Goal-aware extraction that returns content closely related to your query and directly usable by downstream tasks Results: - Improved the GAIA benchmark accuracy for Owl (open-source implementation of Manus) by 23%. - Helped a San Diego developer boost his AI agent’s accuracy by 40%. What we’d love feedback on: - Corner cases where your agents struggle or customization needs for your agents - Output formats you want - How you’d like to control search quality vs. cost - Other features you care about (e.g., runtime monitoring, eval harnesses) We’ll stick around in the thread to answer questions and share implementation details. Thanks for taking a look!
Does the same job
all alternatives →
- GAGeniusrise, an open source framework and ecosystem for AI agents2023 · github.com · ▲9
Hello! Introducing geniusrise, an agent framework and component ecosystem for building AI agent networks that are as flexible as your team. landing page: https://geniusrise.ai (fancy but useless) docs: https://docs.geniusrise.ai (please check this out) github: https://github.com/geniusrise (for dear devs) ## Thought process Since the ChatGPT disruption, I've been pondering on what the tooling layer is going to look like for building LLM-interfacing agents. Saw a plethora of tools coming out as we witness here every week. I'd broadly categorize them into the…
- HAHyperFlow – A self-improving agent framework built on LangGraphApr 2026 · ▲8
Hi HN, I am Umer. I recently built an experimental framework called HyperFlow to explore the idea of self-improving AI agents. Usually, when an agent fails a task, we developers step in to manually tweak the prompt or adjust the code logic. I wanted to see if an agent could automate its own improvement loop. Built on LangChain and LangGraph, HyperFlow uses two agents: - A TaskAgent that solves the domain problem. - A MetaAgent that acts as the improver. The MetaAgent looks at the TaskAgent's evaluation logs, rewrites the underlying Python code, tools, and prompt files, and then tests the new…
- WBWe built an AI Website builder with better output2024 · dorik.com · ▲8
Hey HN, After GPT-3 created waves in the tech industry, a lot of AI tools were emerging and with that, some AI website builders But the results seemed way too generic to us. It felt like the developers were rushing to catch the wave instead of building a proper tool We took our time, did months of RnD and finally came up with something better than what others in the market are doing. It’s got better design output. While it’s still in beta, I wanted to show HN what we did. Will appreciate the feedback when you guys try it out. Here is the link to signup for the beta:…
More ai this month
the category →
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.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
Launched alongside, August 2025
the whole month →
- IS
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
- KT
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
- IW
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
- TC
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
Dev tools · 2025 · sky.dlazaro.ca