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  • Can you also compare in the charts https://maki.sh?

    Should give you some competition.

    by tontinton
  • Does anyone else take these kinds of articles, drop them into ChatGPT, crank it up to Pro, and then have it write issues against your personal harness?
    by ChickeNES
  • How are people using custom harnesses cost effectively? Do they avoid Anthropic models so they can use OpenAI subscription pricing and open weights stuff?
    by __alexs
  • > But the moment you build your own agent, you’re on your own. It’s tricky wiring up the right primitives just well enough to match that “it just worked” feeling.

    It's wild to me to claim that it's tricky to customize one of these harnesses and for that to be the entire justification for an entirely different harness.

    It's really not that hard. If you want to reduce costs then all you need to do is practice delegation: instead of using the strong model, all the time to do everything, instead, you have the stronger model delegate well-defined tasks to a weaker model. Patterns like these are really easy to wire up.

    by samusiam
  • I remember reading about strands SDK and it looked great in terms how everything is an event that you can extend, so this harness feels quite about right.

    However, for this kind of customisation, Pi is actually quite great. One of the most things I love about Pi is ability to ask it to create an extension and it does it quite well as it’s part of their docs. Also ability to customise the system prompt to avoid the clutter that Claude Code add (around 20k system prompt that mostly had nothing to do with the code).

    The demo was showing something I have created for my Pi setup, which is asking me in each new session which skills and MCP I would to enable for the session. This works quite well if you have multiple projects where you don’t need all skills but just a small subset

    by Oras
  • > With Fable 5, Strands harness cost 77% less than Claude Code and scored higher on Terminal Bench 2.1.

    Terminal Bench 2.1 is saturated. Many token saving techniques would save money and score basically the same running Fable 5 against Terminal Bench 2.1. (They claim a better score but don’t say how much better. I’d bet my favorite hat that it’s not statistically significant.)

    This is at least the fourth time I’ve seen a project hit front page with a “save money with same score on saturated benchmark” claim.

    by seizethecheese
  • Why is Pi not in the benchmarks? Deepseek beats Strands and its built on Pi so that’s all I needed to know.
    by theturtletalks
  • I am increasingly hesitant to use non-native harnesses - model providers are now starting to train their agents for use within the harness. An eval like terminal bench can only capture so much data. I don't want to have to assess each harness every model release to make sure it's working as well as it can.
    by johnmlussier

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