Is Grep All You Need? How Agent Harnesses Reshape Agentic Search(arxiv.org)
61 pointsby Anon844 hours ago14 comments
  • alexrigleran hour ago
    Combining regex filtering with semantic ranking using multi-vector embeddings has yielded good results for me. I use ColGREP from the LightOn team asa daily driver - https://github.com/lightonai/next-plaid/blob/main/colgrep/RE...
  • quinncom22 minutes ago
    Don’t presume this study has anything to do with programming. They measured an agent’s ability to search long conversations, not code.

    > We evaluate on a 116-question representative subset of the LongMemEval benchmark (Wu et al., 2025), which tests an agent’s ability to answer questions over long conversations spanning multiple sessions.

  • piekvorst31 minutes ago
    I have always used traditional grep to search codebases. It serves me better than an IDE when there’re lots of scattered and frequent queries.

    grep’s design is surprisingly winning, exceeding expectations to this day.

  • gbaconan hour ago
    This is a surprising result. With structured inputs like source code, I’d expect grep to outperform semantic search, but natural language’s errors and inconsistencies seem to leave so many cracks for information to fall through.
    • sdesolan hour ago
      This paper is based on quality so I don't think it should be that surprising if you take loops into consideration. What the agent finds in the first pass, can help if formulate the next grep if needed.
  • piker2 hours ago
    I recently watched the new Palantir + Kirkland & Ellis fund formation platform demo, and I was surprised to see how effective the union of structured data was in an agent harness. We're used to dealing with flat files and comparing here basic ways of searching, essentially, long strings, but using Palantir's "Ontology" graph framework, I think Kirkland is going to be able to achieve some exception and differentiating outcomes in legal tech. The whole idea assumes that they've got great structured data already, and perhaps that's the real valuable unknown, but giving an agent those tools is super powerful.

    I wrote about it[1] and came away with a different view on both Palantir and the future of agentic workflows personally.

    [1] sorry, LinkedIn: https://www.linkedin.com/pulse/fund-managements-killer-app-d...

  • hmokiguess2 hours ago
    Tangential, I have a hook that rewriters grep to rg but lately I wonder if this is actually wasteful as the model is so biased to grep, is there a way to shim/alias perhaps?
    • sdesolan hour ago
      My CLI does something close to this:

      https://github.com/gitsense/gsc-cli

      `gsc grep` is just an alias for `gsc rg`, mostly because agents are much more likely to reach for “grep” than “rg”.

      It works pretty well, but it is not a perfect drop-in replacement. `grep` and `ripgrep` differ in a few details, especially around glob/wildcard behaviour and flags. What I found works is to not use `grep` in search examples, and have the CLI spit out an error message for the AI saying this is `ripgrep`, so it needs to use `ripgrep` syntax.

    • celrodan hour ago
      If performance is the concern, ugrep will get you most of the way there relative to gnu grep, and should be fully grep compatible in terms of syntax:

      https://github.com/Genivia/ugrep#aliases

      Claude Code may ship with ugrep already.

    • cyanydeez37 minutes ago
      I've been on a look out for any harness that properly secures a protocol to the LLM, but they're all just "here's some tools, hopefully you don't use bash for everything".
    • verdverm2 hours ago
      Many harnesses are doing this already, "Grep" is the tool name, ripgrep is the implementation

      It depends on if it is using Grep the harness tool or Grep from the bash tool

      • hmokiguessan hour ago
        I see it using the Bash tool infrequently though sometimes Grep. I'm on Claude Code for now due to subscription lock-in, been contemplating moving to pi though
        • joelfriedan hour ago
          My experience here (also Claude user) is that the model uses different tools in different contexts. I see rg more on frontend and grep more on backend work. I imagine it defaults to using the tool it has more learning around within the contexts it's reaching for and since for the most part it's 6 of one or half a dozen of the other you'll see environment specific usages for these tools in claude for now. I imagine eventually it'll standardize but we're early yet on such things.

          If you'd told me a decade ago I'd finally learn some sed in 26 because I'd want to understand what the AI was doing I'd have told you you were crazy . . .

        • Analemma_27 minutes ago
          Why do you have subscription lock-in? Even if you pay for a yearly subscription, Anthropic will refund you pro rata if you cancel early.
  • liminal11 minutes ago
    Is <blank> the only ML paper title?
  • jeffchuberan hour ago
    If you are truly bitter-lesson pilled - give the agent all the tools and let it decide which to use.

    - regex (grep) - hybrid search (bm25+vector)

    this X vs Y is uninteresting when the answer can be both.

    • bachittlean hour ago
      Exactly this, and this tool called qmd is what I use for the hybrid search portion. It also uses local LLMs to provide summaries on your own markdown data too. My agents use both depending on what type of search they are doing, and both provide good results.

      https://github.com/tobi/qmd

    • pastel8739an hour ago
      That assumes that the agent knows which one is better. And to bake in which one is better via post-training would require a study like this to establish where each one works well
      • fnordpiglet36 minutes ago
        I’ve got a custom ultra high performance streaming semantic search I exposed as a tool and the RL bias in Claude is almost insurmountable without copious and consistent steering. Codex will follow instructions and use the tools I ask it to but for gods sake between Claude asking to take a nap because it’s getting late in the session and it regressing to RL biased tools like grep it’s maddening. When I can get it to use my compositional tools tool calls drop from like 20-50 to 3-4, but it’s almost impossible to steer.
    • dominotwan hour ago
      it will only use tools it was trained on? what's the benfit of givig it all the tools.
    • worthless-trashan hour ago
      I'm still disappointed that ai can't use ctags, its used for finding strings and patterns, its right there.
      • sdesolan hour ago
        > I'm still disappointed that ai can't use ctags,

        What do you mean by this? Do you mean not automatically build the index?

  • kwilletsan hour ago
    I'm curious to see what patterns it's grepping.
  • yodon2 hours ago
    Feels important, but I wish they also had compared against something like MeiliSearch or Algolia.
    • verdverm2 hours ago
      100%, there's even Typesense, open source Algolia, which can do hybrid search and a number of other fancy things

      I'm currently working on a markdown kb / search tool for my agents, in part built on TS

  • sys_647382 hours ago
    Surely 'strings' would be even better?
  • greenavocadoan hour ago
    This has been posted before, but a dead-simple pattern that helps enormously with steering the model to the right code area is a DESIGN.md that it creates, updates, and references periodically.
  • sdesolan hour ago
    [flagged]
  • wseadowntownan hour ago
    [dead]