AI Playbook
for Food & Beverage

You are a chef or menu developer calculating the cost of a recipe.

Recipe data: [PASTE: Ingredient | Purchase unit | Purchase cost | Recipe quantity used | Unit of measure | Yield % (if applicable)]

Calculate:
1. Cost per ingredient as used = (Purchase cost ÷ Purchase unit size) × Recipe quantity ÷ Yield %
2. Total recipe cost = Sum of all ingredient costs as used
3. Cost per portion = Total recipe cost ÷ Number of portions
4. Food cost % = Cost per portion ÷ Menu price × 100
5. Flag any ingredient representing >20% of total recipe cost — these are your cost levers

Output: Recipe cost card. Cost per portion. Food cost % at current menu price. Ingredient cost breakdown. Target menu price if food cost % exceeds [TARGET %].

You are a restaurant manager analyzing menu performance to optimize profitability.

Menu data: [PASTE: Menu item | Category | Menu price | Food cost $ | Contribution margin $ | Number sold (last 30 days) | Total contribution margin]

Classify each item using the menu engineering matrix:
1. Stars — high popularity + high margin: protect and promote these
2. Plowhorses — high popularity + low margin: reduce cost or raise price carefully; don't remove
3. Puzzles — low popularity + high margin: improve visibility, description, or placement
4. Dogs — low popularity + low margin: consider removing or repositioning

For each category:
Stars: ensure prominent menu placement; staff should be trained to sell these
Plowhorses: review recipe for cost reduction opportunities; test a modest price increase
Puzzles: rewrite menu description; move to better placement; add visual; consider bundling
Dogs: remove unless they serve a strategic purpose (dietary need/signature item)

Output: Menu engineering matrix. Item classification. Action recommendation per item. Estimated margin improvement if recommendations are implemented.

You are a chef calculating ingredient yields to improve recipe costing accuracy.

Yield data: [PASTE: Ingredient | As-purchased weight or quantity | Trim loss | Cooking loss | Usable weight or quantity | As-purchased cost per pound/unit]

Calculate:
1. Yield % = Usable weight ÷ As-purchased weight × 100
2. Cost per usable pound = As-purchased cost ÷ Yield %
3. Recipe cost impact — if yield % is lower than assumed in the recipe cost card, the true cost is higher
4. Yield improvement opportunities — any ingredient where trim or cooking loss seems high vs. standard?
5. Portion control implication — if yield varies by skill level, document the standard yield for consistency

Output: Yield analysis table. True cost per usable pound. Variance from assumed yield in recipe cost cards. Yield improvement recommendations.

You are a chef or product developer creating a brief for a new menu item.

Development criteria: [DESCRIBE: Concept (cuisine type/format/occasion), target food cost % or range, target menu price, any operational constraints (kitchen equipment/prep time/skill level), dietary considerations required, any seasonal or sourcing requirements]

Build the development brief:
1. Concept description — flavor profile, inspiration, and how it fits the current menu
2. Ingredient framework — primary protein/starch/vegetable/sauce; sourcing requirements
3. Cost target — at target menu price and food cost %, maximum allowable cost per portion
4. Operational feasibility — can this be prepared consistently during service within acceptable prep time?
5. Menu positioning — which category does it sit in? What does it replace or complement?

Output: New menu item development brief. Cost target calculation. Operational checklist. Testing and rollout timeline.

You are a restaurant manager reviewing menu prices for a periodic price update.

Data: [PASTE: Menu item | Current price | Food cost $ | Food cost % | Contribution margin | Competitor price range | Last price increase date | Customer price sensitivity (high/medium/low)]

Review:
1. Items with food cost % above [TARGET %] — these are candidates for price increase or recipe adjustment
2. Price vs. competition — are any items significantly above or below competitive range?
3. Price sensitivity by item — price-sensitive items (staples/value items) require careful increases; premium items have more tolerance
4. Rounding and psychological pricing — prices should end in .00, .25, .50, .75, or .99 for clean presentation
5. Recommended price changes — specific new prices; calculate impact on food cost % and contribution margin

Output: Menu price review. Recommended new prices. Food cost % before and after. Total contribution margin impact. Phased implementation plan if making multiple changes simultaneously.

You are a food safety manager reviewing allergen information for the menu.

Menu and recipe data: [PASTE: Menu item | Contains: gluten/dairy/eggs/soy/tree nuts/peanuts/fish/shellfish/sesame (yes/no for each) | Any cross-contact risks | Current menu labeling]

Review:
1. Allergen matrix — complete allergen grid for all menu items across all 9 major allergens
2. Cross-contact risks — items that don't contain an allergen but are prepared on shared equipment or surfaces
3. Menu labeling compliance — are all required allergen disclosures present on the menu or available upon request?
4. Staff training — are all front-of-house staff trained to answer allergen questions accurately?
5. Modification capability — for each allergen, which items can be modified to remove it and how?

Output: Allergen matrix. Cross-contact risk list. Menu labeling gaps. Staff training requirements. Modification guide for service staff.

You are a chef planning the seasonal menu update.

Seasonal data: [DESCRIBE: Season, local or regional produce in peak availability, any proteins or specialty items in season, current menu items to retire, target number of new items, budget constraints, any special events or promotions the new menu should support]

Build the seasonal plan:
1. Seasonal ingredient list — ingredients at peak quality and best pricing this season
2. New item concepts — dishes built around seasonal ingredients; flavor profile and format
3. Menu balance — confirm the updated menu maintains balance across categories (protein variety / dietary options / price range)
4. Items to retire — what current menu items are being replaced? Manage customer expectations for popular items.
5. Transition plan — when does the new menu launch? Training timeline for kitchen and front of house?

Output: Seasonal menu plan. New item concepts with ingredient framework. Items being retired. Training and launch timeline.

You are a culinary director standardizing recipes across multiple locations or shifts.

Recipe data: [DESCRIBE: Dish name, current variations in how it is prepared (different chefs/locations preparing differently), intended standard preparation, equipment available at all locations, skill level of staff]

Standardize the recipe:
1. Exact ingredients and quantities — no approximations; use weight measurements not volume for accuracy
2. Step-by-step method — specific techniques, times, and temperatures; nothing left to interpretation
3. Plating specification — portion size, plate placement, garnish
4. Quality standards — what does a correctly prepared dish look, smell, taste, and feel like?
5. Common errors — what goes wrong most often and how to prevent it

Output: Standardized recipe card. Suitable for laminating and posting in the kitchen. Language clear enough for a new cook. Includes quality check points.

You are a bar manager analyzing beverage program performance.

Beverage data: [PASTE: Beverage item | Category (beer/wine/spirits/cocktail/non-alc) | Menu price | Pour cost $ | Pour cost % | Units sold (last 30 days) | Total contribution margin]

Analyze:
1. Pour cost % by category — beer/wine/spirits/cocktails typically have different pour cost benchmarks
2. Best-margin beverages — items generating the highest contribution margin; these should be featured and promoted
3. High-pour-cost items — beverages with pour cost % above category benchmark; renegotiate pricing or reduce pour size
4. Sales mix analysis — is the beverage mix weighted toward high-margin or low-margin items?
5. Upsell opportunities — what beverage upgrades or pairings would improve average beverage spend per cover?

Output: Beverage program analysis. Pour cost by category vs. benchmark. High-margin items to feature. Pour cost reduction opportunities. Upsell recommendations.

You are a product development manager for a food manufacturing or CPG company managing the new product pipeline.

Pipeline data: [PASTE: Product concept | Stage (ideation/development/testing/regulatory/launch) | Target launch date | Target retail price | Estimated COGS | Target gross margin % | Key regulatory requirements | Market opportunity estimate]

Review the pipeline:
1. Pipeline health — number of products at each stage; is there enough volume in early stages to maintain future launches?
2. Financial viability — at target price and COGS, does each product meet margin targets?
3. Critical path items — products with regulatory or supply chain requirements that could delay launch
4. Prioritization — given resource constraints, which products should receive the most development focus?
5. Stage-gate decisions — any products that should be advanced, paused, or killed based on current data?

Output: Pipeline review. Stage-gate decisions. Critical path risks. Resource allocation recommendations. Launch calendar.