Why this is hard to keep track of

  • Portion counting is fiddly enough that people quietly round it up
  • Memory is unreliable here in one direction only, and it's always upward
  • Vegetables in a sauce or a stir-fry are real and rarely get counted
  • Five-a-day counters spend the evening telling you you're behind

Worth recording

  • Whether the meal had vegetables, and roughly which
  • Which meals never do — usually breakfast and usually lunch
  • Weekday against weekend, which is often the entire story
  • Whether it was cooked at home or bought, which predicts most of it

Cadence

Part of the meal sentence. Nothing extra to do

What progress looks like

A truthful count of how many of your meals actually contain vegetables, and the specific meals and days where they never do.

In practice

Say it once, or photograph it

The entries most worth having are the ones made at the exact moment nobody wants to fill in a form. A sentence — typed, dictated, or replaced entirely by a photo of the plate — is a much lower bar, and it carries the context a calorie field would have thrown away.

Eating More Vegetables Chat

Meal deal sandwich and crisps for lunch at my desk again. Dinner was a stir fry with a lot of veg in it.

Called 4 tools

  • log_meal(items: ["sandwich", "crisps"], meal: "lunch", setting: "desk")
  • log_meal(items: ["stir fry", "peppers", "broccoli"], meal: "dinner")
  • find_pattern(group_by: "meal", tag: "vegetables")
  • compare_periods(group_by: "cooked_at_home")

Logged. Over four weeks, dinner includes vegetables on 22 of 28 days, lunch on six, breakfast on none. Bought lunches carry them on two of 17; lunches made at home, four of six.

Every figure here was counted from entries you made. The model chose which tools to call — it doesn't score the meal, estimate calories from a photo, or decide what any of it says about you.

And then ask

The question the log can answer

Months of entries hold real answers to the things you've been guessing at, and reading them properly has always meant a spreadsheet and a free evening — which is exactly what nobody has.

Ask in plain language. The answers come back with the counts behind them, including when those counts are too thin to mean anything yet — which is the more useful answer far more often than people expect.

Asking about the pattern Chat

Where am I actually losing this — is it the whole week or just work days?

Called 3 tools

  • get_history(topic: "more-vegetables", window: "6m")
  • find_pattern(group_by: "context")
  • compare_periods(metric: "entries")

Work lunches, almost entirely. Weekend meals include vegetables in 71% of entries and weekday dinners in 79% — both fine. Weekday lunches sit at 21%, and 17 of your 20 weekday lunches were bought rather than made. That single meal is most of the gap in your whole log.

Counts and averages over your own entries, nothing more. Where the data is confounded or too thin, the answer says so instead of rounding it into a conclusion.

What it does

Set up around eating more vegetables

The same mechanics as everything else here, pointed at what actually matters for this one.

A sentence or a photo per meal

No database lookup and no calorie box. The log that gets kept beats the log that was more precise for eleven days.

Trends, not days

Weight moves a couple of kilos on water alone. Everything here is read as a weekly trend, because the daily number is mostly noise and reads as failure on a perfectly good week.

What the good weeks had in common

The useful question isn't what you ate on Tuesday, it's what was different about the months that went somewhere. That's a query against your own record, and it's the one worth asking.

Your goal, not one we set

We don't calculate a target for you. Any number an app produces here is a population average wearing your name, and it will be wrong by enough to matter.

A bad week is a data point

Nothing resets and nothing is undone. A week off is information about what makes a week hard, which is considerably more useful than a broken chain.

Exportable from day one

Everything you've logged, photos included, out in a file you can take to a dietitian, a GP, or somewhere else entirely.

The reason a lot of people start

Something to actually bring to the appointment

You get fifteen minutes, and the first question is always some version of "so what does a normal week look like?" — which nobody on earth can answer accurately from memory.

What this gives you: An honest baseline instead of the optimistic one everyone gives verbally, which is where most dietary advice starts from the wrong place.

  • Export the date range you were asked about, as a file you can print
  • Photos alongside the entries, which say more than any description
  • Counts and timings rather than an impression of the worst week
  • Nothing shared anywhere unless you choose to share it

What it won't do

  • Score a meal, or sort food into good and bad
  • Estimate calories from a photo and present the guess as a number
  • Set you a calorie target, a macro target, or a weight
  • Run a streak you can break, or tell you that you've fallen behind
  • Comment on your body. The photos here are of food
  • Diagnose anything, or suggest that a pattern is a diagnosis

It's a notebook that can do arithmetic and answer questions about itself. Deciding what any of it means is a job for you and the people advising you.

Early access

Start with what you're already trying to hold in your head

Tell us what you've been trying to keep track of and we'll set it up with you — recording the thing that's actually useful, at a cadence that survives a bad week.

  • Founding accounts lock their price for life
  • No card, no trial clock, no notification designed to make you feel behind
  • Export everything you've logged, photos included, whenever you want

No card required. Unsubscribe any time.

Keep the record without it becoming another job

Founding pricing is locked for accounts opened during early access.

Founding accounts lock their price for life. No card required.