Show HN: Give your AI agent a brain that understands your codebase
Bitloops is an alpha-stage tool that creates a local, typed, and queryable model of a codebase to improve AI agent efficiency and collaboration. It reduces redundant repository crawling by enabling agents to query structured data through DevQL and maintain shared context across sessions. The system supports multiple AI coding agents and provides features like checkpoint history, reviewable workflows, and local data storage by default.
- ▪Bitloops builds a local, queryable model of codebases to improve AI agent understanding and reduce redundant file crawling.
- ▪The tool supports AI agents like Claude Code, Codex, Cursor, Gemini, Copilot, and OpenCode by providing a shared, maintained codebase model.
- ▪Bitloops captures AI-assisted work in sessions and checkpoints linked to commits, prompts, and file changes for reviewability.
- ▪Users can query codebase state using DevQL and GraphQL through a local dashboard or integrations.
- ▪Data is stored locally by default, with optional remote stores and telemetry controlled by configuration and user consent.
Hacker News (Newest) files mainly under programming. We currently carry 5,306 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/bitloops/bitloops |
| Publication time | Sun, 17 May 2026 05:22:37 +0000 |
| Retrieval time | 2026-05-17T05:33:58.675Z |
| Last seen | 2026-05-17T05:33:58.675Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | Jlb-nhb_InHj |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Stop giving your AI agents the same repo tour. Bitloops builds and maintains a local, typed, queryable model of your codebase so AI agents, developers, and reviewers can work from shared system state instead of rediscovering the repository from raw text. Website · Docs · Quickstart · DevQL · Discussions What Bitloops Gives You AI coding agents are powerful, but most of them still start every task by crawling the repository again: read files, grep for symbols, infer architecture, guess which tests matter, inspect old docs, and compress all of that into a prompt. Bitloops gives them a maintained operating picture instead. You need Bitloops gives you Better agent context A local, queryable model of files, artefacts, symbols, dependencies, tests, checkpoints, and history.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.