I live between two cities. Bilbao is home — rainy, layered, smart-casual. Malaga is my flat — sunny, linen, espadrilles. And somewhere in between, I’m usually travelling with a capsule bag and a vague plan.
For a long time, getting dressed felt like a small but surprisingly draining decision. Not because I don’t love clothes — I do, deeply — but because “what should I wear today?” is actually four questions at once: What’s the weather? What do I have with me? What am I doing today? What feels right? Every morning, before coffee.
So I built an agent to handle it. I call her Parlamoda.
What it does
Parlamoda handles my daily outfit decision from start to finish. Each morning I ask her one question: “What should I wear today?”
She takes it from there:
- Checks which city I’m in and pulls up the right location profile (Bilbao, Malaga, or traveling)
- Gets the current weather forecast for that location
- Looks at my calendar for any meetings or events and reads their formality level
- Browses my Wardrobe table — filtered by weather suitability, season, and occasion
- Builds a complete outfit: top, bottom or dress, outerwear if needed, shoes, accessories
- Logs the full suggestion into my Outfit Log with a written rationale
- Tags the location so I can look back and see what I wore where
She never suggests a trench coat when I’m in Malaga in August. She knows I have a capsule wardrobe there, not my full closet. She knows Bilbao in October means layers. That context is what makes her actually useful.
What it gives me time to focus on
Mornings. Properly.
That sounds small, but the cognitive load of “what to wear” is real — especially when you split your time across climates and wardrobes. Parlamoda removes a low-value decision from my day and gives me back the mental space for things that actually matter: the work I want to do, the people I’m seeing, the coffee I want to drink slowly.
Over time, she also learns. I rate each outfit and leave feedback after wearing it. That data builds a picture of what I actually reach for versus what sounds good in theory. Eventually, she won’t just suggest — she’ll know.
How it works
Parlamoda runs on demand — I trigger her each morning by asking the question. Here’s what she does, step by step:
- Checks my current location — she reads my Location Profiles page, which holds a profile for Bilbao (primary home, full wardrobe, oceanic climate), Malaga (second home, capsule wardrobe, Mediterranean), and Travelling (minimal bag, versatile pieces). Each profile includes typical temperatures, lifestyle context, and wardrobe availability.
- Checks the weather — she fetches the live forecast for that city and cross-references it against the profile’s typical temp range to calibrate the suggestion.
- Checks the calendar — she identifies any meetings or events for the day and reads their formality level to inform the occasion filter.
- Browses the Wardrobe table — my wardrobe lives in a structured table with columns for category, colour, style, weather suitability, season, occasion, location (Bilbao / Malaga / Travel Bag / Both), photo, label, and designer. She filters by what’s relevant.
- Builds a complete outfit — a top, a bottom or dress, outerwear if the weather calls for it, shoes, and accessories. All picked from what’s actually available at my current location.
- Logs the suggestion — she adds a new row to the Outfit Log table: date, weather summary, temperature, meetings, the full outfit breakdown, a style rationale, and the location tag.
- Explains the choice — a short paragraph covering why this outfit makes sense for the day: the weather, the context, the vibe.
After wearing it, I give it a rating out of 5, and leave any notes. That feedback loop is how Parlamoda gets better over time.
Apps and connectors
- Superhuman Docs — the whole data lives here: the Wardrobe table, the Outfit Log, the Location Profiles page, and the agent instructions
- Superhuman Go — the AI layer that works across all your tools.
- Weather — live forecast fetched at the time of the request based on current location
- Calendar — reads the day’s meetings and events to assess formality and occasion
Parlamoda is built inside Superhuman Docs and runs through Superhuman Go. The whole system lives in a single doc — a Wardrobe table with photos, labels, and location tags; an Outfit Log that auto-fills with each suggestion; and a Location Profiles page that gives Parlamoda her geographic intelligence.
To set it up yourself: duplicate the doc, connect Superhuman Docs, Weather, and your Calendar in Superhuman Go, and paste the ready-to-use agent prompt from the Parlamoda — Superhuman Go Agent Setup. Then ask: “What should I wear today?”
The more you fill in your wardrobe, rate your outfits, and keep your location profiles up to date — the more Parlamoda feels like she actually knows you.
Kaixo! I’m Ainara Bilbao, from beeq — the Superhuman partner in Europe. I split my time between locations, which means I’m constantly switching climates, wardrobes, and headspaces. This is the agent I built to make my mornings a little easier.
