Give your docs an agent that drafts from what actually shipped, not from guesswork.
Buda runs doc gap triage, source research, page drafting, release notes, style review, and staleness checks in one shared workspace, where writers, agents, specs, and tickets stay connected and every page lands as a draft someone approves.
The product ships weekly. The docs describe last quarter.
The truth about a feature is split across the PRD, a design doc, the Jira ticket, the pull request description, a Slack thread, a demo recording, and the docs page itself. No two agree completely.
Before a writer types a sentence, they have to reconstruct what actually shipped: which flag went live, which parameter was renamed, which screenshot is now wrong. That archaeology often costs more than the writing.
A generic model writes fluent documentation for behavior that does not exist. Missing docs annoy a reader. Confidently wrong docs get trusted, copied into code, and repeated back by every assistant that indexes the page.
A docs owner cannot see which pages went stale after the last release, which draft came from which source, or who reviewed the change. The doc set keeps no changelog of its own.
Build a workflow around an AI agent for documentation.
Ask a docs chatbot a question and it answers from whatever the page already says, right or wrong; Buda is one shared workspace where writers, engineers, agents, source files, and review rules stay connected.
Six agents share one docs workspace: gap triage, source research, drafting, release notes, style review, and drift detection. Work passes between them, so the brief that fed a draft is still attached when the style pass runs.
Agents gather sources, draft pages, write changelog entries, and flag inconsistencies, then hand each one to a person. Agents prepare the work; humans decide what ships.
Specs, tickets, pull request descriptions, transcripts, the style guide, the glossary, and the current doc set live in one workspace, so an agent drafts from what is there now rather than a copy from three sprints ago.
Six agents, one docs workspace, and reviewable artifacts rather than black-box automation: every draft arrives with the sources it leaned on.
Clusters incoming doc requests, from support tickets to reader feedback, sales questions, and engineering asks, into a ranked list of pages that are missing, thin, or contradicting each other.
Pulls the spec, the merged pull request, the ticket thread, and the demo transcript for one feature into a single brief, with every statement linked back to where it came from.
Writes the page from that brief and your template: concept, prerequisites, steps, parameter table, and a working example, with anything the sources did not answer marked as an open question.
Turns merged pull requests, ticket titles, and feature flags from one release into changelog entries grouped by audience, with breaking changes and migration steps pulled to the top.
Reads a draft against your style guide and glossary, flagging terminology that drifted, headings that break the information architecture, and claims that contradict another page in the set.
Compares published pages against what shipped since they were last touched, then lists the ones describing a renamed field, a removed endpoint, or a screenshot the UI no longer matches.
Pick one workflow, assign the agents, and read the first draft that comes back with its sources. Free pilot — no credit card.
Pick the one documentation job your team repeats every release, and leave the rest alone.
Four weeks against one doc type is enough to know whether a writer stops rewriting the drafts from scratch.
Doc gap triage, source research, page drafting, release notes, or staleness review. Take whichever one your team redoes every release.
A workflow you can check in an afternoon beats one that produces drafts nobody has time to read.
Create the workspace, load the style guide, glossary, templates, and current doc set, then bring in the writers and the engineers who verify accuracy.
Write down who approves what: which drafts an agent may prepare alone, and which pages need a named reviewer before publishing.
Read a release worth of drafts, briefs, and drift reports. Check whether each claim traces to a source you would have used yourself.
Note which pages the agent got most of the way there, and which ones a writer had to start over on.
If the drafts hold up, run the same setup for a second product area, a second doc type, or the API reference.
If they do not, you close it out with the briefs, drafts, and review notes still on file, plus a clear reason why.
Documentation is a trust function. Readers act on what a page says, and so do the coding assistants that index it, which makes a confidently wrong page more expensive than a missing one.
Inside one shared workspace, agents do the gathering, drafting, and checking, and a writer or the engineer who owns the behavior reads the draft and decides whether it goes live. Buda makes no promise that a draft is accurate or complete, which is exactly why the review step exists.
Do not use AI to publish a page, sign off an API contract, or clear security and compliance documentation on its own; a person owns the last read.
Treat it as an operations layer for the doc set: it carries the searching, drafting, and checking, and leaves accuracy, judgment, and the call to publish with the people whose names are on the page.
It is software that takes on repeated documentation work: sorting doc requests, gathering the specs and tickets behind a feature, drafting pages and release notes, checking a draft against the style guide, and flagging pages that have gone stale. None of it touches the live docs site — it sits in the workspace until a writer opens it.
A docs chatbot reads your published pages and answers a reader's question, so it inherits whatever is already wrong. An agent works on the doc set itself: reading specs, tickets, and pull requests, drafting and revising pages, and preparing changes for someone to review before they ship.
No. It can absorb the gathering, the first draft, and the consistency pass. Deciding what a reader needs, how much detail belongs on a page, and whether a technical claim is true is still the writer's and the engineer's call.
Look for the doc job that comes around every release and takes a writer only minutes to check against its sources. Release note drafts, a source brief for a single feature, or a style pass on pages that already exist are the usual candidates.
Your style guide, glossary, templates, and current doc set sit in the workspace beside every draft, and the execution history shows which source each statement came from. Nothing publishes on its own. Buda makes no accuracy claim about a draft, which is why the reviewer's read is the control rather than a fallback.
It can. Buda's workspace includes Git alongside the browser, terminal, and drive, so an agent can work from the repository your docs already live in and hand back a change. What it produces still goes through review the way any other pull request does.
Product docs, API references, and internal engineering docs, plus release notes and the handbook nobody remembers to update. The same setup works for a public docs site, a reference generated from a spec, or a changelog.
Put the gathering and the first draft on agents, and give your writers back the hours that judgment actually needs.
Start with one workflow: doc gap triage, source research, page drafting, release notes, or staleness review.
Free pilot · No credit card · Live in 30 minutes