Food Logging

Food logging turns intention into a measurable plan so your watch-fed calorie targets and coaching stay grounded in what you actually ate.

01Quick start

Food logging works when the record is consistent.

1. Grant Apple Health write permission for the nutrition categories you want Fuel to track
2. Pick one primary capture method for most meals for the next 7 days, then use it repeatedly
3. Verify serving size and protein before saving, since those errors move the day the most
4. Treat repeats as templates so the week is easier to compare and coaching stays specific

02What Fuel logs

Fuel treats a log entry as structured nutrition data that can power daily targets, weekly reviews, and Apple Health summaries.

Macros and energy

Calories, protein, carbohydrate, and fat stay front and center because they drive the daily plan and the weekly coaching context.

Micronutrients and performance signals

Micronutrients, water, and caffeine are first-class fields so hydration, recovery, and dietary quality show up alongside macros instead of being hidden in notes.

03Fast ways to log

Fuel is built around low-friction logging paths that still produce structured data.

Across photo, text, and scanning, the workflow is similar. Fuel turns messy real-world inputs into structured nutrition fields, then you confirm the draft so the Apple Health record stays consistent.

The draft is usually close enough that verification takes seconds. Edits happen when the input is low quality or ambiguous, such as a blurry photo, a partial label, or a description that does not include portion size.

If something is off, treat that as a normal part of logging. A short feedback pass is how you get accuracy without turning the log into manual data entry.

04The fastest logging path

The fastest path depends on what you already know before opening the logger.

Food Library is the non-AI lookup path for known foods. Smart Recall exact mode is also local when it brings forward a previous meal without edits. Use AI when the input needs interpretation, such as a plate photo, a rough meal description, or a Smart Recall request that changes yesterday's meal.

Photo logging

Photo logging works best when you capture the full plate and any packaging or labels that matter, then confirm the result so the data stays consistent across days.

Fuel can read mixed plates, sides, sauces, and drinks. If a nutrition label is present in the frame, it can anchor serving size and macro totals instead of guessing.

Food scanning

Food scanning is the fastest path for packaged foods with clear labels, since the entry is easier to verify and easier to repeat. Use Food Scanning when the meal has a barcode or label that should anchor the record.

Scanning is not limited to perfect barcode shots. If you capture the nutrition panel or front of package, Fuel can extract serving size, macros, and many micronutrients, then you can correct any mismatch before saving.

Restaurant choices

If you have not ordered yet and want help choosing from a menu, use Eat Out from the Calories detail view on Today. Eat Out scans the menu and shows which option fits your remaining calories and macros best.

This is a planning tool, not just a logging tool. Use it before the meal when the real question is what to order.

Text logging

Text logging is the fastest path when you already know the meal and want an accurate result without opening a database.

You can start vague and refine. If the first pass misses an ingredient, uses the wrong cut, or gets portion size wrong, give feedback in plain language and re-run the draft before you confirm it.

Wrist quick-log

Wrist quick-log is designed for repeated meals and post-workout routines where the only requirement is speed and an immediate undo.

Use Watch Companion to learn what the watch workflow can capture and when to switch back to iPhone for higher precision.

Food Library

Food Library is the fastest path for known items, grocery products, and restaurant menu rows. Search more than 225,000 offline rows, browse by grocery brand or category, and log without waiting on AI.

Use Food Library when you know exactly what you ate and want speed over AI interpretation.

Smart Recall

Smart Recall is the fastest path when the meal already exists in yesterday's log. Exact phrases such as "breakfast from yesterday" or "same dinner again" prepare the prior meal locally. Edited phrases such as "copy yesterday dinner but no rice" use AI only for the adjustment after Fuel selects the source meal.

Use Smart Recall when repetition is the real shortcut.

05How logging connects to targets and coaching

Food logs are not isolated entries. They are inputs to the plan.

Daily guidance

Your day view uses logged intake together with Apple Watch energy to keep remaining calories and macro budgets honest.

Weekly review

Weekly coaching uses the full log stream to spot patterns that matter in real schedules, including under fueling on high activity days, inconsistent protein distribution, and hydration drift.

06Making logs accurate without overthinking

Fuel favors consistency over perfection. Aim for stable portions, use simple serving rules for repeated meals, and treat corrections as normal so the plan stays reliable.

When AI proposes an entry that is close but wrong, give feedback and regenerate the draft before you confirm it. The highest value corrections are the ones that move energy and protein, such as portion size and missed ingredients.

1. That portion was about double.
2. Add cooking oil and the sauce.
3. Use the nutrition label in the photo for macros and serving size.
4. That was skim milk, not whole milk.