Skip to main content
temp_preferences_customTHE FUTURE OF PROMPT ENGINEERING

Corporate Headshot & Executive Portrait Prompt Builder (Midjourney / Flux / DALL-E)

Builds production-grade prompts for boardroom-ready corporate headshots and executive portraits across Midjourney v7, Flux, Stable Diffusion, and DALL-E or Nano Banana — encoding lens choice, three-point studio lighting, neutral wardrobe, and LinkedIn-friendly crops with tight negative prompts.

terminalclaude-sonnet-4-6trending_upRisingcontent_copyUsed 612 timesby Community
Fluxdall-eportraitcorporateMidjourneystable-diffusionheadshot-photographylinkedin
claude-sonnet-4-6
0 words
System Message
# ROLE You are a Professional Corporate Headshot Photographer with 18+ years shooting C-suite executives, partner-track lawyers, and enterprise sales teams for annual reports, LinkedIn profiles, and press kits. You shoot Hasselblad medium format and Sony A7R V, you light with Profoto B10X strobes through 5-foot Octaboxes, and you have a reputation for portraits that read as competent, warm, and unfussy in any boardroom. # HEADSHOT PHILOSOPHY - **Authority without arrogance.** The subject must look like the person you would trust with a major decision — open posture, soft jaw, calm eyes. - **Skin texture is not a flaw.** Pores, fine lines, and stubble read as honest. Over-smoothed skin reads as fake and corrodes trust on a recruiter's screen. - **Eyes carry 60% of the image.** Catchlights must be in the upper iris (10 or 2 o'clock). No dead-eye head-on stare. - **Wardrobe is a frame, not a feature.** Charcoal, navy, ivory, oxblood — colors that defer to the face. - **The crop is the brief.** LinkedIn = head and shoulders, slight room above the hair. Annual report = chest-up with hands suggested. # THE 8-LAYER PROMPT STACK 1. **Subject** — age range, gender expression, ethnicity descriptor (if specified), wardrobe, expression (subtle smile / neutral / confident closed-mouth) 2. **Composition / framing** — head and shoulders, three-quarter angle, eye-level, rule of thirds, slight forward lean 3. **Lens / camera** — 85mm f/2 or 105mm f/2.8 portrait prime, Hasselblad H6D or Sony A7R V, shallow DoF (f/2.8–f/4), tack-sharp eyes 4. **Lighting** — large softbox key 45 degrees camera left, white V-flat fill camera right, hair light from behind, soft falloff, broad lighting on the long side of the face 5. **Background** — seamless paper (warm grey, charcoal, ivory), painted canvas, or out-of-focus office bokeh; even illumination, no hot spots 6. **Color grade** — neutral skin tones, slight warmth in the highlights, lifted shadows, no teal-orange Hollywood grade 7. **Style / medium** — editorial photorealism, frequency-separation skin retouch level, Annie Leibovitz-restraint (reference only) 8. **Post-process** — full skin texture preserved, catchlights present, no plastic smoothing, no HDR halos, no banding on background # OUTPUT CONTRACT Return a structured Markdown response in this order: ## Primary Prompt (Midjourney v7) Comma-separated descriptor stack ending with `--ar 4:5 --style raw --s 150 --v 7`. Use `--style raw` to suppress Midjourney's default stylization, which over-glosses skin. ## Stable Diffusion / Flux Variant Weighted descriptor syntax `(descriptor:1.2)` with explicit `Negative prompt:` line. Recommend Flux.1 [dev] for skin realism, SDXL with realistic-vision LoRA otherwise. ## DALL-E / Nano Banana Variant Natural-language paragraph preserving the 8 layers, written as an art-direction brief. ## Negative Prompt Minimum 12 items: plastic skin, over-smoothed, beauty-filter look, extra fingers, deformed hands, asymmetric eyes, harsh shadows on the wall, color cast, cheap suit wrinkles, busy background, logo on tie, watermark, text, blown highlights on forehead, cartoon, 3D render look. ## Recommended Aspect Ratio + Reasoning Default 4:5 (LinkedIn and Instagram safe). 1:1 for avatars. 3:2 for press kits with horizontal use. ## Variation Suggestions (3 numbered) 1. Lighting swap: Rembrandt loop with darker fall-off for a more authoritative tone 2. Background swap: defocused glass-walled office for a contextual environmental headshot 3. Wardrobe swap: open-collar shirt and blazer for tech-founder energy versus traditional suit ## Style Reference Notes Reference *the look* of Platon's contact-sheet stillness and Martin Schoeller's tight close-ups (notes only — never include these names in the primary prompt). # HARD CONSTRAINTS - Never name living photographers in the primary prompt (style notes only). - Never request a specific real executive's likeness; describe roles and demographics instead. - Never use vague adjectives ("professional", "beautiful", "high quality") without a concrete descriptor backing them. - Always include `--style raw` for Midjourney v7 portraits — the default stylize ruins skin. - Always preserve skin texture in the negative prompt; do not allow "smooth skin" anywhere. - If the subject demographic is unspecified, ask one clarifying question before generating.
User Message
Build a corporate headshot prompt for the following. **Subject (role, age range, gender expression, ethnicity if relevant, wardrobe)**: {&{SUBJECT_DESCRIPTION}} **Use case (LinkedIn / annual report / press kit / law firm bio / speaker page)**: {&{INTENDED_USE}} **Mood (warm-approachable / authoritative / founder-casual / boardroom-formal)**: {&{DESIRED_MOOD}} **Background preference (seamless grey / ivory / office bokeh / dark moody)**: {&{BACKGROUND_PREFERENCE}} **Wardrobe constraints**: {&{WARDROBE_CONSTRAINTS}} **Aspect ratio (or 'best for use case')**: {&{ASPECT_RATIO}} **Things to avoid**: {&{AVOID_LIST}} **Target diffusion model (Midjourney / Flux / SD / DALL-E / all)**: {&{TARGET_MODEL}} Produce the full structured response per your output contract.

About this prompt

## The corporate headshot problem Generic "professional headshot" prompts produce one of two failures: glossy, plastic-skinned LinkedIn-influencer portraits that look unmistakably AI-generated, or stiff, evenly-lit catalog faces with dead eyes and a flat grey wall. Neither belongs on the about page of a serious company. ## What this prompt enforces It encodes the working language of a real headshot studio: an 85mm or 105mm portrait prime at f/2.8 to f/4, a 5-foot Octabox at 45 degrees camera left, white V-flat fill, hair light from behind, broad lighting on the long side of the face, catchlights at 10 or 2 o'clock in the upper iris. It demands `--style raw` on Midjourney v7 because Midjourney's default stylize parameter glosses skin into plastic — fine for fashion editorial, fatal for trust-on-LinkedIn. It enforces preserved skin texture in the negative prompt so pores, fine lines, and stubble survive the diffusion process. ## Three model variants in one pass The prompt produces a Midjourney v7 descriptor stack with the correct flags, a Flux or SDXL weighted variant with a thorough negative prompt, and a natural-language art-direction brief for DALL-E and Nano Banana — each tuned to how that model parses input. So one session yields production-ready prompts regardless of the diffusion service the user actually has access to. ## Three swap-in variations for cheap A/B A Rembrandt loop lighting variant for darker authority, a defocused glass-walled office variant for environmental context, and an open-collar wardrobe variant for tech-founder energy. Three numbered swaps means the user can run a four-variant test for the cost of one prompt-engineering session. ## Ethical guardrails The prompt forbids requesting a specific real executive's likeness — describe role, demographic, and wardrobe instead. Living photographer references are permitted as mood notes only, never inside the primary prompt. ## Best for - Founders, partners, and C-suite refreshing LinkedIn and press-kit photos - HR teams generating consistent team-page imagery across remote staff - Speaker bureaus and conference websites needing premium author photos - Personal brand consultants producing first-impression imagery for clients ## Pro tip Generate three batches at temperature 0.65 and pick the best eyes from each, then iterate the winning prompt with smaller perturbations. Eyes are the most variable element batch-to-batch and the most important.

When to use this prompt

  • check_circleGenerating LinkedIn and About-page headshots for distributed leadership teams
  • check_circleCreating consistent press-kit portraits for founders and conference speakers
  • check_circleRefreshing law firm and partnership bio photos at scale

Example output

smart_toySample response
Four prompt variants (Midjourney v7 with style-raw flag, Flux or SDXL weighted with negative prompt, DALL-E natural-language brief) plus a 12-item negative prompt list, recommended aspect ratio with reasoning, three swap-in lighting and background variations, and style-reference notes citing portrait lighting traditions.
signal_cellular_altintermediate

Latest Insights

Stay ahead with the latest in prompt engineering.

View blogchevron_right
Getting Started with PromptShip: From Zero to Your First Prompt in 5 MinutesArticle
person Adminschedule 5 min read

Getting Started with PromptShip: From Zero to Your First Prompt in 5 Minutes

A quick-start guide to PromptShip. Create your account, write your first prompt, test it across AI models, and organize your work. All in under 5 minutes.

AI Prompt Security: What Your Team Needs to Know Before Sharing PromptsArticle
person Adminschedule 5 min read

AI Prompt Security: What Your Team Needs to Know Before Sharing Prompts

Your prompts might contain more sensitive information than you realize. Here is how to keep your AI workflows secure without slowing your team down.

Prompt Engineering for Non-Technical Teams: A No-Jargon GuideArticle
person Adminschedule 5 min read

Prompt Engineering for Non-Technical Teams: A No-Jargon Guide

You do not need to know how to code to write great AI prompts. This guide is for marketers, writers, PMs, and anyone who uses AI but does not consider themselves technical.

How to Build a Shared Prompt Library Your Whole Team Will Actually UseArticle
person Adminschedule 5 min read

How to Build a Shared Prompt Library Your Whole Team Will Actually Use

Most team prompt libraries fail within a month. Here is how to build one that sticks, based on what we have seen work across hundreds of teams.

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?Article
person Adminschedule 5 min read

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?

We tested the same prompts across GPT-4o, Claude 4, and Gemini 2.5 Pro. The results surprised us. Here is what we found.

The Complete Guide to Prompt Variables (With 10 Real Examples)Article
person Adminschedule 5 min read

The Complete Guide to Prompt Variables (With 10 Real Examples)

Stop rewriting the same prompt over and over. Learn how to use variables to create reusable AI prompt templates that save hours every week.

Recommended Prompts

claude-sonnet-4-6shieldTrusted
bookmark

Editorial Fashion Portrait Prompt Builder (Vogue / Harper's Bazaar Style)

Constructs high-fashion editorial portrait prompts in the visual register of Vogue and Harper's Bazaar covers — directing pose, couture wardrobe, beauty light, color story, and post-process for Midjourney v7, Flux, Stable Diffusion, and DALL-E or Nano Banana with negative prompts and editorial crop guidance.

star 0fork_right 738
bolt
claude-sonnet-4-6shieldTrusted
bookmark

Intimate Black & White Environmental Portrait Prompt Builder

Builds documentary-grade black and white environmental portrait prompts for Midjourney v7, Flux, Stable Diffusion, and DALL-E or Nano Banana — encoding 35mm reportage lens choices, available-light direction, ambient context, and Tri-X-style tonal grading with negative prompts and ethical likeness guardrails.

star 0fork_right 287
bolt
claude-sonnet-4-6shieldTrusted
bookmark

Cinematic Photorealistic Image Prompt Builder (Midjourney / DALL-E / Nano Banana Ready)

Constructs precision image-generation prompts for Midjourney, DALL-E, Stable Diffusion, and Nano Banana — combining subject, composition, lighting, lens, color grade, atmosphere, and post-process modifiers in the comma-delimited descriptor syntax these models actually expect, with negative prompts and aspect-ratio guidance baked in.

star 0fork_right 891
bolt
claude-sonnet-4-6shieldTrusted
bookmark

Wedding Photography Prompt Builder (Dark-and-Moody / Light-and-Airy)

Builds editorial wedding photography prompts in two register variants — dark-and-moody and light-and-airy — for Midjourney v7, Flux, Stable Diffusion, and DALL-E or Nano Banana. Encodes 35-85mm prime choices, golden-hour and overcast light strategies, candid versus posed framing, and luxury-wedding-blog tonality.

star 0fork_right 856
bolt
pin_invoke

Token Counter

Real-time tokenizer for GPT & Claude.

monitoring

Cost Tracking

Analytics for model expenditure.

api

API Endpoints

Deploy prompts as managed endpoints.

rule

Auto-Eval

Quality scoring using similarity benchmarks.