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We've created a comprehensive Retrieval Harness for modern agentic retrieval in 2026. The harness provides a persistent data pipeline that can connect to a data source, index and update a large knowledge base, and expose a broad set of tools akin to filesystem operations (semantic/keyword search, regex grep, file... show more

Jerry Liu

85,798 subscribers

57,248 views • 3 months ago •via X (Twitter)

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24 Comments

Adnan Qidwai3 months ago

btw the GitHub doesn't seem public yet

Jerry Liu3 months ago

sorry about the above - just made it public!

Ira Rothken3 months ago

This looks very promising for AI legal apps and ESI analysis.

Kevin Madura3 months ago

Have you tested it on OBLIQ-Bench?

Pinkman3 months ago

hybrid search across the whole index with read, grep, and find is basically giving an agent the same tools a developer would use on a local filesystem

Eugene Yaroslavtsev3 months ago

@jerryjliu0 i haven't been able to find a bug bounty / security program link on gh/llama's official site - got a link?

AW3 months ago

jerry,dropped you a DM about a paid collab

KYD 玩 ai3 months ago

Treating retrieval as a persistent tool surface, with search, grep, file search, and read operations, feels much closer to how agents actually investigate large knowledge bases than one-shot RAG calls.

Dmytro Palaniichuk 🇺🇦3 months ago

The filesystem metaphor is the right abstraction. Moving from "query the index" to "navigate the knowledge base" made agents far more predictable — they scope reads before writing, like a good engineer. Partial-update primitives, or is re-index always full corpus?

Christian Müller3 months ago

Persistent pipeline plus a bounded, filesystem-like tool surface is a strong combo here. The reliability jump comes when each tool call returns a typed result the next step can rely on, not free-form text the agent has to re-parse every run.

srijanarya3 months ago

The filesystem-style tools were never my bottleneck. Index freshness was. "Index and update a large KB" buries the ugly part: an agent retrieving mid-reindex and answering off a stale chunk. Does the harness guarantee read-during-update consistency?

Sean Kerr — AI, minus the hype3 months ago

The persistent pipeline is the right call. Most "agentic retrieval" pain isn't recall — it's the agent re-indexing the world every run because nothing survives between calls. The harder half: teaching it when it has enough to stop retrieving.

Nahid3 months ago

persistent data pipeline opens up new possibilities

Shashank Nidhi3 months ago

Your harness builds a fresh index, but it never flags when a source document drifts. Staleness is a harder problem than retrieval. A vector store can answer a query, yet it has no idea the underlying truth moved two weeks ago. If you attach a provenance check on each update, the agent can decide whether to trust the result.

Nhost3 months ago

The quiet shift here is that retrieval starts looking more like an agent exploring a filesystem: search, grep, read, follow the thread. That's much closer to how people actually research a case

Oleksandr3 months ago

agentic retrieval feels like giving an agent a local filesystem watching legal agents actually crawl PDFs is next‑level

Anshuman Singh3 months ago

The persistent-pipeline framing matches what we hit with travel data: static snapshots rot fast, so continuous dedup plus per-row source tags are what keep agent citations honest. Curious how the harness handles provenance when two indexed sources conflict, do you keep both with lineage or resolve to one?

Jabir | AI Systems3 months ago

👍🏻

Sebastian Buzdugan3 months ago

index v2 will live or die on permission drift, not tool breadth

Pawzard3 months ago

agents out here getting a whole filing cabinet meanwhile i still cant find my keys 😭

The Guy With A Hat3 months ago

Another OCR. Sweet, is there a paper attached?

egesea3 months ago

Retrieval is becoming less about finding information. It's becoming the workspace where agents think and act.

Makaroni3 months ago

curious how it handles drift tho like the knowledge base updates mid-task and the agent already cached stale context

Brosko3 months ago

ngl 'filesystem operations but for vibes' is actually the unlock agents been fumbling retrieval tasks for too long fr 🔥

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169,184 views • 1 year ago

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39,872 views • 7 months ago

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91,697 views • 1 year ago

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420,133 views • 5 months ago

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Clara Shih

49,651 views • 2 years ago

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74,286 views • 3 months ago