Show HN: Banksia – Build and run adaptable, accountable AI teams
Banksia is a Python‑based platform that lets users build and manage adaptable AI teams through a visual console or conversational operator. It supports Linux and macOS, uses SQLite by default, and can be configured for PostgreSQL. The tool emphasizes accountability by tracking responsibility hierarchies, revisions, and results throughout a workflow.
- ▪Banksia requires Python 3.12 or newer and can be installed via pipx, offering both a visual Console and a chat‑based Operator for team design and execution.
- ▪The system stores data in SQLite out‑of‑the‑box, with optional PostgreSQL support for more complex deployments.
- ▪Workflows define reusable responsibility trees, allowing teams to adapt sequential, parallel, or hybrid execution strategies while preserving state and history.
- ▪Durable state handling enables teams to pause, replan, retry, and resume work without losing accepted history, ensuring traceable accountability.
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,586 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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/ringlochid/banksia |
| Publication time | Tue, 28 Jul 2026 12:50:13 +0000 |
| Retrieval time | 2026-07-28T12:54:47.015Z |
| Last seen | 2026-07-28T12:54:47.015Z |
| 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 | DyDSxZ158QJM · 1 stories |
| 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
Banksia Build adaptable, accountable AI teams in minutes—and run them on complex work. Design them easily, run them reliably, and stay in control from the first decision to the final Result. Get started · Documentation · Starter teams Watch the Banksia tutorial Install and start Banksia requires Python 3.12 or newer and currently supports Linux and macOS. Install the command-line application in an isolated environment with pipx: pipx install banksia banksia init banksia serve Open http://127.0.0.1:18125/. The installed package includes the visual Console. Guided initialization chooses a default workspace, configures a Task provider, and can configure the separate Operator that helps you build and run teams. Banksia uses SQLite by default, so a local installation needs no database server.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.