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Products that do what p99.chat – the assistant for software performance optimization does

Hi HN! We’re the team behind CodSpeed (https://codspeed.io), a continuous performance testing tool. Today, we're really excited to launch our new product: p99 (https://p99.chat), an assistant for software performance optimization. Through CodSpeed, we have been working with hundreds of projects doing performance optimization. What struck us was how fragmented the tooling landscape is. You would identify a performance regression in their CI, or worse, in production, then disappear into a rabbit hole of benchmarking frameworks, sampling profilers, memory profilers,…

  1. 1
    beLow176

    Inline insights with C/C++ that shows CPU, memory, energy

    Dec 2025

  2. 2CA

    A recent HackerNews comment - “For one programmer's hourly cost, you could run 4000 CPU cores continuously. Can there really be no practical way to apply thousands of cores to boosting the programmer's productivity?” https://news.ycombinator.com/item?id=19339467 This is what we have come up with. The current productivity tools - Slack, Asana, Trello, Facebook Workplace, etc. - are great, but lack direct access to your code. Building a tool directly around the code makes it more powerful for software developers: CoDiff. https://codiff.com The foundation of CoDiff is a…

    2019

  3. 3IM

    Hey HN! I made a completely open sourced alternative to Weights and Biases with (insert cringe) blazingly fast performance (yes we use rust and clickhouse) Weights and Biases is super unperformant, their logger blocks user code... logging should not be blocking, yet they got away with it. We do the right thing by being non blocking. Would love any thoughts / feedbacks / roasts etc

    2025 · github.com

  4. 4

    Build fast & better with ChatGPT prompt sequence automations

    2025

  5. 5OA

    https://github.com/gugarosa/opytimizer Did you ever reach a bottleneck in your computational experiments? Are you tired of selecting suitable parameters for a chosen technique? If yes, Opytimizer is the real deal! This package provides an easy-to-go implementation of meta-heuristic optimizations. From agents to search space, from internal functions to external communication, we will foster all research related to optimizing stuff. Use Opytimizer if you need a library or wish to: - Create your optimization algorithm; - Design or use pre-loaded optimization tasks; -…

    2021

  6. 6LS

    Earlier this year, I took a month to reexamine my coding habits and rethink some past design choices. I hope to rewrite and improve my FOSS libraries this year, and I needed answers to a few questions first. Perhaps some of these questions will resonate with others in the community, too. - Are coroutines viable for high-performance work? - Should I use SIMD intrinsics for clarity or drop to assembly for easier library distribution? - Has hardware caught up with vectorized scatter/gather in AVX-512 & SVE? - How do secure enclaves & pointer tagging differ on Intel, Arm, & AMD? - What's…

    2025 · github.com

  7. 7WB

    Hi, we are working on a tool for speeding up test runs, by skipping tests unaffected by code changes. Effectivly, Saving 80-95% of the time, by skipping 80-95% of tests. We started a few months ago, and have managed to get into a few production CI systems. All our prospects and users are on holiday right now. So we decided to repackage and open-source for local test running. available here (https://github.com/nabaz-io/nabaz) under MIT license. One line change: pytest -v -> nabaz test --cmdline "pytest -v" Stalk us on GitHub, or just Star us. Ask questions, we'll answer in…

    2022 · github.com

  8. 8CP

    I'm building an AI platform, FlowChai and found a neat use case for it today that I thought would be useful to HN readers. I use GPT4 heavily for writing / editing code, but a major downside is that it doesn't know about new projects. I made the connection today that I could upload the zip file of a Github repo to FlowChai and then write prompts just like with ChatGPT with code questions. While the original intent for this platform is more around natural language, it's neat how this works so well. It's powered underneath by pgvector and OpenAI embeddings.

    2023 · flowch.ai

  9. 9AS

    I'm a combat veteran living paycheck to paycheck with no computer science degree. I built an AI system that benchmarks 60x faster than industry leaders. Real benchmarks (Dec 12, 2025): - 3.43ms response time (vs 50-200ms industry average) - 337 queries/second (vs 50-150) - 0% error rate, 100% uptime - Constitutional AI with 1,235 specialized "brains" Built it in 3 weeks. 4 U.S. patents pending. Full story + independent benchmarks: https://thebrokenwayfoundation.org Not asking for money. Just need technical validators to verify this is real.

    Dec 2025

  10. 10AA

    Hey HN! We built Achilles, a tool that automatically accelerates your Python code. It identifies performance bottlenecks, rewrites those functions in optimized C++, and seamlessly patches them into your running program—without you changing a single line of code. In CPU-intensive, loop-heavy tasks, we've observed performance improvements of 100-1000x. Achilles can be installed via pip and works with just a single command. We'd appreciate your feedback, and feel free to give us a star if you find it interesting!

    2025 · github.com

  11. 11BO

    Read the full blogpost at https://rach.codes/blog/Introducing-Bhumi (click on reader to see the technical breakdown!) AI inference should be fast, but in practice it’s painfully slow. Inference bottlenecks slow down LLM-powered chatbots and AI workflows everywhere. I built Bhumi to fix that. Bhumi is a Python library designed for developers, yet its performance-critical core is implemented in Rust (via PyO3) for near-native speed. This hybrid approach delivers up to 2.5x faster response times across providers like OpenAI, Anthropic, and Gemini—without changing the…

    2025 · bhumi.trilok.ai

  12. 12IE

    Quick note on how it works and how I've done my batch embedding engine IgniteMS. The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper. I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire…

    Jun 2026 · github.com

  13. 13C0

    Hello, everyone! We posted on HackerNews a couple of weeks ago debuting CoDiff (https://news.ycombinator.com/item?id=19593637), a productivity tool centered around your code. Since then, we’ve received a lot of useful feedback from the community that we have integrated with our product. Now, even as an individual, CoDiff (https://CoDiff.com) can boost your productivity by notifying you as soon as your local changes conflict with upstream commits. Conversely, if you do not see a conflict marker on your files within CoDiff, you can rest assured that you will be able to…

    2019

  14. 14MI

    Hi! Recently I've launched - mybfio.io - platform for software reviews with social network aspect. Prehistory Many great system are already in place that allow people to search and rate software products, including the site I am publishing this post on. However I have always felt that those systems are not specifically centered around product/software development lifecycle (releases, real users feedback over a product entire lifetime, so on) and often too broad or not designed specifically for that type of work, which is ok. Why? As an opensource author I would like to have constant…

    2021

  15. 15CC

    I finished building Codr.cc last night. Codr is a code snippets sharing website much like pastie or snipt.org, but with a few innovations. First is that it autodetects the language and highlights it accordingly. The second, killer feature, is that it allows you to create snippets from files on your computer. You can select a file using the file browser, or you can drag and drop it into the site. The app will read its contents and create a snippet from it - ready to share. -- Now, I'm a college student in need of some quick cash. Recently I sold wrttn.in rather quickly thanks to HN, and I…

    2011

  16. 16CN

    As a solo developer on a sizeable project, I found myself facing the challenge of creating documentation, a task I admittedly do not enjoy. Fortunately, ChatGPT arrived just in time. After experimenting with it, I discovered that it generates high-quality documentation for code files, even better than what I could produce manually. This realization led me to develop Code-Narrator, a client that simplifies the documentation process. Code-Narrator (https://github.com/ingig/code-narrator) utilizes GPT-4 to analyze your code files and automatically generate documentation. The…

    2023 · github.com

  17. 17FO

    title doesn't let nuance, ofc it's not the app that's faster but the way you can use it with Groq inference for example.

    May 2026 · mumbli.app

  18. 18IM

    I built this using semantic search and the ChatGPT API, which was just released the other day. What makes it special is it not only understands the code you're debugging, but also pulls in additional context like relevant documentation to help answer your questions and suggest code changes. Ultimately, my goal is to take the hassle out of pasting error messages into Google, finding a vaguely related StackOverflow post, and manually integrating the solution into your code.

    2023 · useadrenaline.com

  19. 19MS

    Hey, I'm Nick from Nutrient, I want to share our newly released MCP Server that enables document workflows using natural language — things like redacting, merging, signing, converting formats, or extracting data. While many MCP servers have traditionally been developer-focused, we recognized that the technology could be highly effective in promoting the adoption of tools that are often hidden from end-user interfaces. We’re really interested to see if this side of the protocol could continue to mature. One thing we struggled with was the inability to receive documents from the client (no…

    2025 · github.com

  20. 20SR

    Hi HN! Sipp is an open-source AI inference library for running local models in browsers with up to 3x faster decode speeds than alternative libraries. My background is in HCI (human-computer interaction) and graphics programming. Me along with my co-founder have been experimenting and thinking a lot about what the next user experience will look like when tokens are commodified to the point of being essentially “free.” A motivation for us was to try to move beyond the chat app and information retrieval use cases that are dominant now, and figure out how AI could instead act as a continuous…

    Jun 2026 · sipp.sh

  21. 21FA

    Hi HN, We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization. AIBooster provides: Real-time monitoring of GPU, CPU, memory, and power consumption. Clear visibility into performance bottlenecks, helping developers optimize AI workloads. Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements. Significant cost savings by maximizing infrastructure efficiency. It's free to try, requires minimal setup, and integrates seamlessly into your…

    2025 · fixstars.com

  22. 22UA

    I've been using LLMs for long discovery and research chats (papers, repos, best practices), then distilling that into phased markdown (build plan + tests), then handing those phases to Codex/Claude to implement and test phase by phase. The annoying part was always the distillation and keeping docs and architecture current, so I built Unpack: a lightweight GitHub template plus docs structure and a few commands that turns conversations into phases/specs and keeps project docs up to date as the agent builds. It can also generate Mintlify-friendly end-user docs. There are other…

    Feb 2026 · github.com

  23. 23SA

    Hi guys, we're Wilhem from Paris and Jean-Daniel from Tokyo, software engineers with a passion for all things cloud (IaaS, PaaS, SaaS). We recently decided to tackle the problem of Capacity Planning with Stacktical, a Scalability Prediction service (https://stacktical.com). For a decade, we've been observing our clients and colleagues trying to nail down their strategy using repeated cycles of defining, collecting and interpreting load testing campaigns. It's funny how most people don't realize how demanding the work of infrastructure managers and their teams really is... While…

    2016

  24. 24CA

    Hi HN — I'm the creator of FastMCP and wanted to share a new project we've open-sourced called Colin. I obviously love MCP, but I also use skills extremely heavily in my day-to-day work. Being exposed to both has made me very aware of a tension: - Anything with dynamic information, I ship over MCP. This takes work to set up and requires conversational boilerplate to refresh in every conversation. - Anything behavioral, I put in skills. They're lightweight, used automatically, and feel great. But I would never put dynamic information in a skill because keeping it up to date is a pain. And yet…

    Jan 2026 · github.com

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