¿Puedo vibecodear Hedy?

PARCIAL · un fin de semana
precio $12.99/mesahorrarías $155.88/añotiempo de build un fin de semanacategoría 🎙️ notas de reuniónreemplazada por 0 personas

The pieces are all commodity now: capture audio, stream it through a local Whisper variant, keep a rolling transcript, and every few seconds ask a model for the next good question. An agent will get you that in one sitting on a laptop, and the transcript-plus-summary half will genuinely be fine. What it will not get you is a phone in your pocket that survives being backgrounded during a two hour lecture, or sub-second suggestions that arrive before the moment passes. Live assistance is a latency and UX problem more than an AI problem, and that is exactly the part that takes weeks of fiddling. Build it if you mostly sit at a desk; keep paying if you mostly do not.

el prompt
Build a local desktop meeting copilot. Stack: Python 3.11, FastAPI backend, a single HTML page with vanilla JS and a WebSocket, no build step. Run everything on localhost, no accounts, no telemetry, no cloud storage.

Audio capture: use sounddevice to record from a selectable input device at 16kHz mono. Document in the README that capturing the other side of a call requires a loopback device (BlackHole on macOS, a WASAPI loopback device on Windows) and let the user pick it from a dropdown of available inputs. Optionally mix two devices (mic plus loopback) into one stream.

Transcription: faster-whisper with the small.en model by default, configurable via .env. Process audio in 5 second chunks with a 1 second overlap, maintain a rolling transcript in memory, and push each new segment to the browser over the WebSocket with a timestamp.

Assistance loop: every 15 seconds, or on a manual "nudge" button, send the last 2000 characters of transcript plus a short session brief the user typed at the start to an LLM via the OpenAI-compatible API. Key comes from OPENAI_API_KEY in .env. Ask for exactly three things in JSON: two suggested questions to ask next, one factual note or definition worth knowing, and one line of what seems to be at stake. Render these as cards in a right-hand panel, newest on top, with the old ones dimmed rather than deleted.

Session end: on stop, write the full transcript and all generated cards to ./sessions/YYYY-MM-DD-HHMM.md, then make one final call for a summary with action items appended at the top of that file.

UI: two columns. Left is the live transcript, auto-scrolling, with a pause button. Right is the assistance cards. A header with device picker, session brief field, start/stop, and a visible recording indicator. Dark, dense, no animations.

In scope: local recording, streaming transcript, periodic suggestions, markdown export, session list page that greps past files.

Out of scope: mobile, speaker diarization, calendar or Zoom integration, multi-user, auth, hosted anything. Do not add them.

Ship a README with the loopback setup steps, the exact pip install line, a .env.example, and a blunt note that recording other people may require their consent where the user lives.

$ ábrelo en tu agente (prompt listo, tú das enter) o cópialo crudo

Se puede en parte

Ahorro de referencia: US$156/año si dejas de pagar Hedy.

Quiero que lo armen →
por qué la gente sigue pagando

Because real-time is unforgiving. A post-hoc summarizer can be sloppy and still useful, but a live copilot that lags four seconds or drops audio when you switch apps is worse than nothing, and people pay to not think about that. The mobile side compounds it: background audio on iOS is a permissions and lifecycle minefield that nobody wants to solve for themselves. Add the meeting-type presets and calendar hookups and the subscription is mostly buying tuning you would otherwise do by hand for a month.

qué pierdes

xMobile apps that keep recording reliably when the screen is off, which is where most of these sessions actually happen

xTuned latency: your DIY suggestions arrive a beat late, and a beat late is useless in conversation

xSpeaker diarization and meeting-type presets that shape the assistant for a sales call vs a lecture vs a doctor visit

xCalendar and conferencing integrations that join and label sessions for you

xHosted, searchable history across every session with no laptop babysitting

arte previo · úsalo en vez de construir, si prefieres

Nada que valga la pena señalar. Por eso existe el prompt.

compartir en X ↗"Acabo de reemplazar Hedy ($12.99/mes) con un prompt"
preguntas
¿Puedo vibecodear Hedy?

Parcial. El núcleo de Hedy se arma en un fin de semana con el prompt de esta página, pero hay huecos reales: Mobile apps that keep recording reliably when the screen is off, which is where most of these sessions actually happen, Tuned latency: your DIY suggestions arrive a beat late, and a beat late is useless in conversation. Lee la lista honesta arriba antes de comprometerte.

¿Cuánto cuesta Hedy?

Hedy cuesta unos $12.99/mes (Pro, revisado 2026-08-18), o sea $155.88 al año.

¿Qué pierdo si reemplazo Hedy?

Con honestidad: Mobile apps that keep recording reliably when the screen is off, which is where most of these sessions actually happen; Tuned latency: your DIY suggestions arrive a beat late, and a beat late is useless in conversation; Speaker diarization and meeting-type presets that shape the assistant for a sales call vs a lecture vs a doctor visit; Calendar and conferencing integrations that join and label sessions for you; Hosted, searchable history across every session with no laptop babysitting. Si alguno de esos te sostiene el negocio, sigue pagando.

¿Hay una alternativa open source a Hedy?

No hay una alternativa open source madura que valga señalar. Por eso existe el prompt de esta página.

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