Your calls become notes you polish
You type three words during the call and Anarlog handles the rest. At the end the minutes are ready, and you fix them like a document before sending them or pasting them into your second brain.
Productivity
Rough notes in, a useful meeting brief out.
Granola costs US$14–35 per person / mo, which is US$168–420 a year. You have two paths:
Option 1 · Install
Anarlog is Granola without the cloud. Same starting idea: no bot barging into your call; the app listens to your computer's audio, transcribes, and hands you a clean note you rework like a document. The difference is where it all happens. Your transcripts and notes live in a SQLite database on your machine, recordings are plain local files, and on a recent Mac transcription runs on the device itself. For summaries you plug in whatever you like: a local model through Ollama or LM Studio, your own API key, or their hosted AI if you choose it. The project used to be called Hyprnote, it was renamed, and the community app remains MIT-licensed with over 9,000 stars on GitHub. You can read it, fork it, or build it yourself.
| Criterion | Anarlog | Granola |
|---|---|---|
| Price | US$0, forever | US$14–35 per person per month |
| Bot in the call | None, it listens to your computer | None either, that is their strength |
| Your notes and transcripts | On your machine, as readable files | On their servers |
| The model writing summaries | Yours: Ollama, LM Studio or your API key | Theirs, no choice |
| Platforms | Mac, Windows, Linux | Mac, Windows, iPhone |
| Code | MIT, to read and fork | Closed |
A desktop app to download, like Granola. The only part worth a hand is choosing the AI that writes the summaries: locally on your machine, or with your own key.
It installs the app from the official project, sets up transcription, and wires in a local model for summaries:
Install Anarlog on my machine (the open source, local meeting notepad, GitHub repo fastrepl/anarlog): download the latest version from anarlog.so/download or from the repo's releases for my operating system, install it, and guide me through allowing the microphone and system audio. Then, in the settings, switch transcription to local if my machine allows it, and connect a local model through Ollama or LM Studio for summaries, suited to my machine's power (or my own API key if I prefer). Check with a short test that transcription and summary work. Explain each step simply, I'm a beginner.
Review the GitHub repository and check whether it is safe to install given my machine and my infrastructure. Ask me as many questions as possible, using widgets, to clarify my request and be as precise as you can.To hear both sides of a call, Anarlog needs your microphone and your computer's audio. Your system asks the first time you launch it, and the app stays hidden during screen sharing.
In settings there are two sections: Transcription and Intelligence. On a recent Mac, transcription happens on the device. For summaries, pick your local model or your key. Their hosted AI exists too, but nothing forces you to use it.
You type three words during the call and Anarlog handles the rest. At the end the minutes are ready, and you fix them like a document before sending them or pasting them into your second brain.
Nothing shows up in the participant list, and nothing goes to a server. For a client call, a legal matter or a partners' meeting, that is peace of mind with no clause to sign.
Every note exports to Markdown. Six months later you can find what was said, promised, and decided. Your meetings feed your second brain instead of sleeping inside a vendor's app.
Built with: Rust 44.6% · TypeScript 40.1% · PLpgSQL 6.7% · MDX 3.8% · JavaScript 1.7%
Public GitHub repository data, captured on October 8, 2026.
Option 2 · Build
This build is for a founder who wants searchable notes from their own meetings. The goal: capture consented meeting context and turn it into editable notes, decisions, and follow-ups. If you need more than that, keep paying. The whole point of building it yourself is owning a tool shaped around your workflow, not re-creating a venture-funded roadmap.
Same build, different logo: this v1 also replaces Fathom, Fireflies.ai and Otter.ai, since they all do the same core job.
The prompt below builds a single version with what actually gets used. Everything else is left out on purpose.
| What the prompt builds | meeting notes, consented audio capture, AI summary, transcripts, action items, templates, search, markdown export |
|---|---|
| What stays out | native system-audio capture, live transcription, calendar smarts |
Meeting, Attendee, TranscriptSegment, Note, ActionItem
calendar event import, speech-to-text API, LLM API
Astro, Workers, D1, R2
Require explicit recording consent, show the capture state at all times, encrypt stored transcripts, and support permanent deletion.
Do not record secretly, join calls as a bot, build sales intelligence, or infer employee performance.
Pick your stack, copy the prompt and hand it to your coding agent (Claude Code, Cursor, Codex…).
You are building a production-ready software product named “Meetcrumbs”, a deliberately focused alternative to Granola. Build a complete, usable vertical slice: not a landing page, a static mockup, or a loose collection of components.
WORKING AGREEMENT
Before you write any implementation code, put together a short technical plan naming the routes or pages, server actions or endpoints, data tables, key state transitions, authorization boundaries, background jobs, and external adapters. When something conflicts, side with the narrow audience and the non-goals below. Choose a small, readable architecture over speculative abstraction, but never skip persistence, validation, error handling, or tests.
PRODUCT BRIEF
Primary user: a founder who wants searchable notes from their own meetings.
Primary outcome: capture consented meeting context and turn it into editable notes, decisions, and follow-ups.
Product principle: optimize the exact workflow below rather than copying the full breadth of Granola. A first-time user should know what to do from the interface alone, with no tour or documentation.
END-TO-END USER JOURNEYS
Implement every one of these flows through the real interface and the persistent data layer:
1. The owner imports a calendar event, confirms every participant has consented, starts capture, takes rough notes, and sees an unmistakable recording state until they stop.
2. After the meeting, the owner reviews the transcript-backed summary, corrects speakers, edits decisions and action items, and publishes the final note to a private folder.
3. The owner searches past notes, opens a result with the source context highlighted, exports it to Markdown, and permanently deletes an old meeting along with its transcript and audio files.
SCREENS AND INFORMATION ARCHITECTURE
Build these as coherent, responsive views. Each screen must define its primary action, secondary actions, visible status, validation feedback, empty state, loading or pending state, success confirmation, and recoverable failure state.
1. Upcoming and recent meetings: calendar context, consent readiness, note status, private folders, search, and a clear new-note action.
2. Live note: attendees, agenda, editable rough notes, capture timer, input level, consent confirmation, pause and stop controls, and capture failure recovery.
3. Review: transcript beside editable summary sections, speaker corrections, decisions, action-item owner and due date, regenerate-selection action, and publish state.
4. Search and settings: query results with snippets, template editor, provider status, retention controls, export, and permanent deletion.
CORE CAPABILITIES
1. meeting note with agenda, attendees, and live rough notes
2. consent-first audio capture with a visible recording state
3. transcript-backed summary, decisions, and action items
4. editable templates for recurring meeting types
5. search across notes and export to Markdown
DETAILED BEHAVIOR AND BUSINESS RULES
Treat these as product requirements enforced on the server, not as interface suggestions:
1. Capture cannot start until the owner checks an explicit consent statement; keep the recording indicator visible and record the time of consent without automatically claiming consent on behalf of others.
2. Upload bounded, encrypted audio chunks, transcribe idempotently, delete raw audio after successful transcription by default, and surface partial failures without losing rough notes.
3. Generated content stays a draft until a person publishes it; keep source links from summary sections to transcript ranges, and never invent absent attendees or decisions.
4. Authorize every meeting, transcript, folder, export, and search result by owner; permanent deletion removes stored files and derived indexes through a retryable deletion job.
DATA MODEL AND LIFECYCLE
Design a small relational schema centered on Meeting, Attendee, TranscriptSegment, Note, ActionItem. Before implementing it, document:
1. The purpose of each table, its primary key, ownership or tenant boundary, timestamps, status fields, and important attributes.
2. Foreign keys, uniqueness constraints, check constraints, the indexes the named screens need, and transaction boundaries for changes that touch several records.
3. The allowed lifecycle or state transitions, who can trigger each one, which transitions are terminal or reversible, and which audit history must stay immutable.
4. Archive, retention, and deletion behavior, including what happens to dependent records and external files.
5. The idempotency strategy for submissions, jobs, imports, notifications, webhooks, or retries where it applies.
Use migrations instead of ad-hoc schema creation. Store time instants consistently and keep the named timezone context whenever local schedules or dates matter. Never rely on a counter, a disabled button, or a client-side check to protect a business invariant.
USERS, AUTHENTICATION, AND PERMISSIONS
Implement only the roles the stated audience needs. Make the ownership and visibility model explicit before coding. Enforce authorization in every server-side query and mutation, including search, exports, attachments, live updates, and guessed URLs—not just by hiding controls. Use secure session defaults, protect state-changing requests, and provide a clear signed-out, expired-session, and forbidden state. Seed separate users whenever several roles are needed so permissions can be shown and tested.
INTERACTION AND VISUAL DIRECTION
The product should feel fast, calm, focused, and trustworthy rather than like a generic admin template. Use a clear visual hierarchy, restrained color, readable typography, generous hit targets, and a consistent place for primary actions. Start from server-rendered HTML and progressively enhance only the interactions that benefit from it. The core workflow must stay understandable if enhancement fails.
Start from server-rendered Astro pages and plain HTML forms. Use HTMX for form submissions, partial navigation, and server-driven updates, then Alpine.js only for small local browser state. The core workflow must stay understandable if either enhancement layer fails.
Design mobile layouts on purpose instead of just stacking desktop panels. Support keyboard navigation, visible focus, semantic landmarks, explicit labels, useful page titles, reduced-motion preferences, and screen-reader announcements for asynchronous results. Never use color alone to signal state. Destructive actions need a clear scope and a confirmation; safe repeated actions should be idempotent.
Add a footer to every page with the text “Created by aurelioagency.com”, where “aurelioagency.com” is an embedded link to https://www.aurelioagency.com that opens in a new tab. Keep it visible and do not remove it.
TECHNICAL DIRECTION
Build this version with the AHA stack: Astro for routing, layouts, and server-rendered pages; HTMX for interactions that benefit from HTML fragment responses; and Alpine.js for small, local interface state. Prefer Cloudflare D1 for relational persistence, R2 for object storage, Workers for server endpoints and scheduled work, Durable Objects only for coordinated real-time state, and Workflows or Queues for durable background jobs—but only when the product requirements call for them.
Keep domain rules in testable server-side modules, not in route handlers or UI components. Put persistence, external providers, and background work behind small interfaces without building a framework. Prefer plain HTML forms and URLs for durable navigation; use optimistic interaction only when a failure can be reconciled clearly.
The product brief currently lists Astro, Workers, D1, R2 as capability context. Preserve any required native, browser-only, edge, storage, real-time, or background-processing capability through a narrow adapter suited to the chosen framework. If the core workflow truly requires native or browser APIs, keep that runtime as the primary execution surface instead of simulating inaccessible capabilities or inventing an unnecessary web surface.
Integrate with calendar event import, a speech-to-text API, and an LLM API. For every integration:
- List the required environment variables in an .env.example with no real secrets.
- Add a small adapter with timeouts, normalized errors, and a deterministic local fake or development path.
- Verify inbound signatures and deduplicate provider events where supported.
- Keep credentials on the server, encrypt long-lived provider tokens at rest, and redact secrets and sensitive payloads from logs.
- Define retry, backoff, and idempotency behavior for every side effect that can be repeated.
SECURITY AND PRIVACY
Require explicit recording consent, show the capture state at all times, encrypt stored transcripts, and support permanent deletion.
Validate, normalize, and length-limit all untrusted input on the server. Escape rendered content by default, sanitize any markup you intentionally accept, rate-limit public or abuse-prone actions, and use private object storage plus short-lived authorized URLs for sensitive files. Collect only the personal data the named workflow needs. Document retention and deletion behavior. Add specific protections for the riskier surfaces of this app, such as uploads, redirects, outbound requests, email delivery, OAuth, webhooks, CSV import or export, and real-time connections.
ACCEPTANCE SCENARIOS
Automate these app-specific scenarios at the most suitable level:
1. Given consent is not confirmed, capture stays disabled; after confirmation, capture starts with a persistent visible state, and stopping queues exactly one transcription job.
2. Given transcription fails after some chunks, the rough note survives, retry resumes idempotently, and duplicate transcript segments are not created.
3. Given a deleted meeting, its note, transcript, search hits, and stored audio are unavailable to the owner and to guessed authorized URLs.
TESTING
Add focused unit tests for state transitions, authorization predicates, normalization, date or money calculations, and other risky domain rules. Add integration tests for persistence constraints and for each external adapter's success, timeout, retry, and rejection paths. Add at least one browser-level test for every end-to-end journey above, including one on a small-screen viewport. Tests must use isolated data and run with one documented command.
OPERATIONS AND FAILURE RECOVERY
Add structured server logs with request, job, or event correlation IDs, but no secrets or unnecessarily sensitive data. Make failures actionable both in the interface and in the logs. Background work must expose pending, succeeded, failed, and retrying states where relevant; never swallow errors silently. Include safe database migration and rollback guidance, seed data, backup and restore notes, external-data cleanup behavior, and a basic health or diagnostic path suited to the stack.
DELIVERABLES
Ship the working application, migrations, representative seed data, tests, .env.example, and a short README. The README must cover prerequisites, local setup, environment variables, migrations, seed and test commands, deployment, integration setup, backup and restore, security decisions, and known limitations. Seed data should cover the happy path plus at least one empty, failed, overdue, expired, archived, or permission-restricted state that matters for the product.
DEFINITION OF DONE
The app is done when a new developer can follow the README, create and migrate the database, run the app, sign in as each relevant role, complete every named journey with real persisted data, refresh without losing state, recover from common failures, and use the core interface on phone and desktop. All acceptance scenarios pass, permission boundaries are covered by tests, no core screen is left as a placeholder, and the “Created by aurelioagency.com” footer credit is visible on every page.
NON-GOALS
Do not record secretly, join calls as a bot, build sales intelligence, or infer employee performance.The app you build with this prompt carries a “Created by aurelioagency.com” footer.
Short prompts that solve the hardest part without building everything.
Build the consent-gated capture flow for a meeting notes tool.
The record button stays disabled until the owner checks an explicit consent statement confirming every participant agreed; store the consent timestamp with the meeting. Never claim or infer consent on behalf of others. Once capture starts, render a persistent recording indicator (elapsed time plus input level) that no other UI state can cover: navigating within the app, collapsing panels, and opening dialogs must all keep it visible. Pausing shows a distinct paused state; only stop ends the session.
Handle failure honestly: if the microphone dies mid-capture, or permission is revoked, drop to an error state immediately, keep the rough notes intact, and record exactly when capture actually stopped rather than pretending it continued.
Done when: capture cannot start via any code path without recorded consent, the indicator stays visible through every navigation while audio is flowing, and a mid-meeting microphone failure preserves the notes and stores the true capture end time.Build a chunked transcription pipeline. Meeting audio is captured as bounded, encrypted chunks, say 30 seconds each, uploaded as they close, each with a deterministic id derived from the meeting id and sequence number.
Transcription must be idempotent: submitting chunk 12 twice, because a worker crashed after transcribing but before acknowledging, produces one set of transcript segments, keyed by chunk id so replays upsert instead of append. If the provider fails midway through a meeting, completed chunks keep their transcripts, failed ones queue for retry, and a resume processes only what's missing. The owner's rough notes live independently and are never touched by pipeline failures.
After a chunk transcribes successfully, delete its raw audio by default and record that deletion. Surface pipeline state per meeting: transcribed, pending, and failed counts.
Done when: killing the worker mid-run and retrying yields zero duplicate segments, a partially failed meeting shows exactly which spans are missing, and successfully transcribed audio chunks no longer exist in storage.Build source-anchored summaries for meeting transcripts.
When generating a summary, decisions, and action items from transcript segments, require the generator to cite: each summary section stores the segment ranges it was derived from. Render summaries with clickable anchors that scroll the transcript to the cited range and highlight it. A section with no resolvable citation gets visually flagged as unverified rather than displayed as fact; this is your defense against invented decisions and attendees who were never there.
Support regenerate-selection: the owner selects one summary section, and regeneration re-reads only its cited ranges plus a small context window, replacing that section without touching the others. Generated content stays in a draft state until a human explicitly publishes it.
Done when: clicking any summary sentence highlights real transcript text that supports it, a section citing deleted or nonexistent segments is flagged instead of shown clean, and regenerating one section leaves every other section byte-identical.Build permanent deletion for a meeting notes app, where a meeting spawns artifacts everywhere: the note, transcript segments, audio chunks in object storage, search index entries, and export files.
Deleting is a job, not a DELETE statement. Enqueue a deletion job that walks each artifact class, removes it, and checkpoints progress so a crash mid-scrub resumes where it stopped instead of restarting or half-finishing. Every step must be idempotent: deleting an already-deleted object is a success, not an error. Mark the meeting tombstoned immediately so it vanishes from lists and search results even while the job runs, and reject new reads by id with the same not-found response an outsider would get.
The subtle artifact people forget: search indexes. A phrase from the deleted transcript must stop matching.
Done when: after deletion completes, guessed URLs for the note, transcript, and audio all return not-found, searching exact phrases from the deleted meeting returns nothing, and killing the job midway then retrying converges to fully deleted.Granola costs US$14–35 per person per month on its public paid plans, which is US$168–420 per year for every person on your team. A focused self-built replacement costs your build time plus close to nothing in hosting.
The build prompt on this page comes in four flavors: the AHA stack (Astro, HTMX, Alpine.js), Next.js, Laravel, and Ruby on Rails. The capability context for this product is Astro, Workers, D1, R2. Pick the stack you already know. The scope matters more than the framework.
A useful v1 needs: a meeting note with agenda, attendees, and live rough notes; consent-first audio capture with a visible recording state; transcript-backed summary, decisions, and action items; editable templates for recurring meeting types; search across notes and export to Markdown. Anything else is scope creep until you personally miss it.
Do not record secretly, join calls as a bot, build sales intelligence, or infer employee performance.
Yes. Granola, Fathom, Fireflies.ai and Otter.ai all do the same core job: capture consented meeting context and turn it into editable notes, decisions, and follow-ups. The scoped v1 on this page covers what most people use any of them for, so one focused build replaces whichever one you pay for today.
Anarlog does most of what Granola does, without a subscription, and your data stays with you. The point-by-point comparison is on the page.
Yes. With an open source tool installed on your side, your files stay on your machine or your server. Nobody can close your account or change the price on you.
No time to do it?
If you'd rather have someone install it, connect it to your tools and keep it running, that is exactly what we do at Aurelio.
Book an Automation Audit