nowfound

Alternatives

Products that do what BlastRadius does

Speed up Java CI by skipping unaffected tests safely.

  1. 1

    Let a fleet of parallel agents test your app in minutes

    May 2026

  2. 2DC
  3. 3
    Bullet240

    30-60% faster than Claude Code and Codex

    26d ago · codewithbullet.com

  4. 4

    Run collaborative AI-powered bug bashes without spreadsheets

    Dec 2025

  5. 5
    Offload93

    Offload your test suite to speed up the agent loop

    Mar 2026

  6. 6

    Fastest CI/CD platform for world’s best engineering teams

    2018

  7. 7
    WarpBuild144

    30% faster, 50% cheaper Github actions runners

    2023

  8. 8

    Validate agent-generated code before it ever reaches CI

    May 2026 · circleci.com

  9. 9
    Forge CLI107

    Swarm agents optimize CUDA/Triton for any HF/PyTorch model

    Jan 2026

  10. 10

    Use your repository to generate safe AI coding guardrails

    Jun 2026 · threedeep.tech

  11. 11

    Multimodal RAG platform, from POC to production in minutes

    Apr 2026

  12. 12

    Ask your Playwright tests why they failed

    Apr 2026

  13. 13

    Speed up your CI/CD pipeline

    2020

  14. 14

    One workspace for Claude, Codex, Gemini and your stack

    May 2026

  15. 15

    Autogenerate a complete mobile CI/CD pipeline in minutes

    2023

  16. 16WB

    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

  17. 17IN

    Tl;dr: I trained a classifier to route to the least expensive model and reasoning depth to complete the request. Coupling that with additional automated token efficiency techniques has yielded 3x usage for the same spend. For anyone interested in trying it themselves: https://nerfguard.com Various teammates and I switched over to Codex from Claude Code recently. We still bounce between the tools, but Codex’s speed and steerability coupled with performance gains were hard to ignore. One of the downsides was that the per token pricing kicked in way sooner. This is happening across…

    Jun 2026

  18. 18BA
  19. 19WF
  20. 20

    Open-source VMs-as-a-service. Contribute to stanford-mast/blast development by creating an account on GitHub.

    9d ago · github.com

  21. 21IB

    For the last 6 months, I've been building ORUS Builder, an open-source AI code generator. My goal was to fix the biggest issue I have with tools like v0, Lovable, etc. – they generate broken, non-compiling code that needs hours of debugging. ORUS Builder is different. It uses a "Compiler-Integrity Generation" (CIG) protocol, a set of cognitive validation steps that run before the code is generated. The result is a 99.9% first-time compilation success rate in my tests. The workflow is simple: 1.Describe an app in a single prompt. 2.It generates a full-stack application…

    Nov 2025

  22. 22PI
  23. 23FC

    Hi everyone, I’ve been working on an open-source tool called Flakestorm to test the reliability of AI agents before they hit production. Most agent testing today focuses on eval scores or happy-path prompts. In practice, agents tend to fail in more mundane ways: typos, tone shifts, long context, malformed input, or simple prompt injections — especially when running on smaller or local models. Flakestorm applies chaos-engineering ideas to agents. Instead of testing one prompt, it takes a “golden prompt”, generates adversarial mutations (semantic variations, noise, injections, encoding edge…

    Jan 2026

  24. 24AA

    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

Ranked by how close each launch is in meaning, then by votes. Refine with a description →