Hero illustrations and visual assets across five locked style modes. Pick the path that fits your access.
One Custom GPT holds the style rules, banned-styles guardrails, and your reference images. You type a brief; DALL-E renders. ChatGPT Plus, Pro, or Team required (Custom GPTs aren't on the free tier).
Sign in at chatgpt.com. Left sidebar → Explore GPTs → top-right Create. Switch to the Configure tab.
Intelligaia Illustrationimage-tool-instructions.md from the skill folder (~4,200 characters).BL-fed.png, YH-head-fingerprint.png, etc.Top-right Create. Sharing scope: Anyone with the link for the team. Pin to your sidebar for one-click access.
Paste this test brief and confirm the output looks like the FED / GOODNESS / UX / W reference series:
Hero illustration for an upcoming blog post titled "AGENTS" — about the architecture of self-learning AI agents in design. BL mode. 16:9 hero.
A Gem holds the same instructions and references as the ChatGPT Custom GPT. nano-banana (Gemini 2.5 Flash Image) does the generation. Especially strong on the texture-heavy modes (PP halftone, SP cross-hatched, YH atmospheric).
Sign in at gemini.google.com. Left sidebar → Gems → Gem manager → top-right + New Gem.
Intelligaia Illustrationimage-tool-instructions.md content. One source file for both tools.Save → right-click the Gem in the sidebar → Pin to top. One-click access from any Gemini session.
Same test brief as Path 1. Gemini's nano-banana model runs the generation.
Hero illustration for an upcoming blog post titled "AGENTS" — about the architecture of self-learning AI agents in design. BL mode. 16:9 hero.
The full self-learning workflow. Claude runs the skill, asks intake, picks the style mode, drafts the prose prompt, captures corrections. The Custom GPT or the Gem renders the image. Memory grows; first draft gets sharper every run.
You need at least one image-gen tool. Pick whichever you'll use most — or set up both and let the agent route per mode.
Copy the intelligaia-graphics-skill/ folder into ~/.claude/skills/ on your machine. Restart any open Claude Code or Cowork session so the skill is picked up.
cp -r ~/Downloads/intelligaia-graphics-skill ~/.claude/skills/
In any Claude session, ask "list my skills". intelligaia-graphics-skill should appear with its description and triggers.
Type a brief in Claude. The skill loads, asks intake, proposes a style mode, drafts the prompt with three variants. Paste into your GPT or Gem. Generate. Return to Claude with rating and 2–3 bullets of feedback. Memory updates for the next run.
Campaign, capability, partnership, and hire pages in Intelligaia tokens. Hero, value sections, social proof, CTA.
A Custom GPT loaded with the Intelligaia HTML token kit and 6–8 of our best published landing pages. You describe the campaign; the GPT returns a draft page in our tokens — hero, three value sections, proof grid, testimonial, CTA close. ChatGPT Plus, Pro, or Team required.
Sign in at chatgpt.com. Left sidebar → Explore GPTs → top-right Create. Switch to the Configure tab.
Intelligaia Landing PagesSKILL.md for intelligaia-landing-page — page-purpose options (campaign / capability / partnership / hire), structure (hero + 3 value + proof grid + testimonial + CTA), token rules (cream, ink, yellow as accent), banned filler.Top-right Create. Sharing scope: Anyone with the link for the team. Pin to your sidebar for one-click access.
Paste this brief and confirm the GPT returns a structured page in Intelligaia tokens (cream, ink, yellow accent — no lorem ipsum):
Draft a campaign LP for our agentic AI workshop launch. Audience: design directors. Primary CTA: book a discovery call. Proof points: HAX, Atlas, AI-EAM. Standard 6 sections.
Mirror Gem of the GPT. Same Knowledge, same Instructions. Gemini's value here is native long-context — useful when the brief is a 30-page strategy doc or a meeting transcript that needs to become a landing page.
Sign in at gemini.google.com. Left sidebar → Gems → Gem manager → top-right + New Gem.
Intelligaia Landing PagesSKILL.md content as the GPT. One source file, two tools.Save → right-click the Gem in the sidebar → Pin to top. One-click access from any Gemini session.
Pilot with one brief that's longer than 10k tokens — a strategy deck, a meeting transcript. Same starter prompt as the GPT:
Draft a campaign LP for our agentic AI workshop launch. Audience: design directors. Primary CTA: book a discovery call. Proof points: HAX, Atlas, AI-EAM. Standard 6 sections.
The self-learning path. Claude runs the intelligaia-landing-page skill, drafts the page section by section against our gold examples, captures every correction back into memory. GPT or Gem handle any inline image needs; Claude owns structure and copy.
Under ~/.claude/skills/intelligaia-landing-page/. Folder layout:
intelligaia-landing-page/
├── SKILL.md
├── memory/
│ ├── house-style.md hooks that work, CTA verbs, metric strip vs. testimonial
│ ├── glossary.md product names, capability names, banned filler
│ ├── corrections.jsonl starts empty
│ └── ratings.jsonl starts empty
└── examples/
├── gold/
│ ├── lp-2025-platform-launch/ brief.md + final.html
│ ├── lp-2025-partnership/ brief.md + final.html
│ └── lp-2026-hiring/ brief.md + final.html
└── index.md
Use the structure: name, description with trigger phrases ("Make an LP for X", "Draft a landing page", "Hero + sections for [campaign]"), intake questions (page purpose, audience, CTA, proof points, tone, length), output spec (single self-contained HTML, Intelligaia tokens, mobile-responsive, no lorem ipsum), run lifecycle reference, capture rules.
Drop 3–5 best published landing pages into examples/gold/, each with its original brief. Write house-style.md v0 from a 30-min interview with the reviewer — one page, no more. Add the skill to the org repo via commit-skills-to-git so the team gets the same version.
One landing page per week. Capture every correction and rating. Run the first consolidation pass on day seven — update house-style.md from the corrections log. Test prompt:
Draft an LP for our agentic AI workshop launch. Campaign page. Audience: design directors. Primary CTA: book a discovery call. Proof points: HAX, Atlas, AI-EAM. Standard 6 sections.
Drafts in the Intelligaia voice from a topic and optional source material. Hook, tension, POV, evidence, close.
Custom GPT seeded with our voice glossary, banned-filler list, and five reference posts. Drop a topic, a link, or some notes; the GPT returns a draft in our voice plus three title variants and a meta description. ChatGPT Plus, Pro, or Team required.
Sign in at chatgpt.com. Sidebar → Explore GPTs → top-right Create → Configure tab.
Intelligaia Blog PostsSKILL.md for intelligaia-blog-post — voice glossary, structure (hook → tension → POV → 2–4 evidence sections → counter-position → action close), banned filler ("leverage", "seamless", "unlock", "at the end of the day"), output spec (3 title variants + meta description + hero illustration brief).Top-right Create. Sharing: Anyone with the link for the team. Pin to your sidebar.
Paste this brief and confirm the draft hits the voice, structure, and length:
Draft a 1200-word POV post titled "Why agentic design needs a human in the loop." Reader: design directors. Source: notes from our last team retro. CTA: book a consult.
Mirror Gem of the GPT. Same Knowledge, same Instructions. Particularly strong when the source material is a long video, podcast, or meeting transcript — Gemini's long-context ingests those better than the GPT.
Sign in at gemini.google.com. Sidebar → Gems → Gem manager → top-right + New Gem.
Intelligaia Blog PostsSave → right-click in sidebar → Pin to top.
Pilot with one 60-minute podcast transcript → post. If Gemini holds the voice across long source material, this becomes the preferred tool for transcript-driven posts.
Convert this 60-minute podcast transcript into a 1500-word post in our voice. Reader: design directors. CTA: follow the newsletter.
Claude is the strongest writer for the Intelligaia voice. The intelligaia-blog-post skill runs the workflow: intake → voice-aware draft against gold examples → capture every per-paragraph correction. Highest-volume artifact we ship and biggest current time-cost — this is the recommended pilot agent.
Under ~/.claude/skills/intelligaia-blog-post/. Folder layout:
intelligaia-blog-post/
├── SKILL.md
├── memory/
│ ├── house-style.md opening patterns, evidence formats, POV framing
│ ├── glossary.md "agentic AI" vs "AI agents"; banned filler
│ ├── corrections.jsonl starts empty
│ └── ratings.jsonl starts empty
└── examples/
├── gold/
│ ├── post-2025-design-systems/ brief.md + source.md + final.md
│ ├── post-2025-ai-research/ brief.md + source.md + final.md
│ └── post-2026-craft/ brief.md + source.md + final.md
└── index.md
Triggers: "Draft a post about X", "Turn this talk into a post", "Write up our perspective on Y", "Convert these notes into a blog post". Intake: topic + angle, reader, length (short / standard / long), source material, CTA goal. Output: markdown in our voice + 3 title variants + meta description + hero illustration brief + internal link suggestions. Edge cases: refuse to invent claims; refuse to write on a trending topic without an internal POV.
Drop 3 best published posts into examples/gold/ with their original briefs and source material. Write house-style.md v0 and glossary.md from a 30-min interview with the senior writer. Commit via commit-skills-to-git so the team gets the same version.
One post per week. Capture corrections at paragraph granularity. Run the first consolidation pass on day seven — opening patterns and evidence formats converge fast. Test prompt:
Draft a 1200-word POV post titled "Why agentic design needs a human in the loop." Reader: design directors. Source: notes from our last team retro. CTA: book a consult.
Portfolio writeups from project material. Hero, problem, approach in three stages, metrics, testimonial.
Custom GPT with the Intelligaia portfolio HTML template baked into Knowledge. Drop client materials (brief, screenshots, outcome notes); the GPT returns a portfolio-ready draft with NDA-aware outcome phrasing and screenshot crop suggestions. ChatGPT Plus, Pro, or Team required.
Sign in at chatgpt.com. Sidebar → Explore GPTs → top-right Create → Configure tab.
Intelligaia Case StudiesSKILL.md for intelligaia-case-study — portfolio structure (hero + problem + approach in 3 stages + highlight screen + metrics + testimonial + next-engagement CTA), NDA outcome-phrasing rules, client-team crediting patterns, banned claims (never invent metrics, never overclaim).Top-right Create. Sharing: Anyone with the link for the team. Pin to your sidebar.
Pick a project that's already shipped (so you know the right answer) and re-write it. Compare against the actual published version to calibrate. Starter brief:
Case study for [client]. Sector: enterprise SaaS. Problem: scaling design ops across 4 product lines. Approach: shared design system + research ops pod. Outcomes: 3× case study velocity, NDA on revenue impact. Materials: 18 Figma screens + 2 client testimonials + outcome memo.
Mirror Gem of the GPT. Useful when project materials include video walkthroughs, recorded client interviews, or workshop recordings — Gemini's long-context handles those better than the GPT.
Sign in at gemini.google.com. Sidebar → Gems → Gem manager → top-right + New Gem.
Intelligaia Case StudiesSave → right-click in sidebar → Pin to top.
Feed Gemini a 90-min client interview transcript or a workshop recording. It summarizes and structures into a case study draft:
Case study for [client].
Source: attached 90-min client interview transcript +
24 Figma screens.
Sector: federal services.
Apply NDA phrasing — metrics under client review until next month.
Layered on top of the existing ux-case-study skill. We don't rebuild — we add a memory layer. Claude writes the case study; memory captures NDA phrasings, client-team crediting patterns, banned claims. Highest-leverage long-form. Target: 4–6 case studies per quarter, up from 1–2 today.
ux-case-study already produces the Intelligaia portfolio HTML structure (hero + problem + approach + metrics + testimonial). Don't change it.
Layer memory/ and a focused examples/gold/ set onto the existing skill — same pattern as intelligaia-graphics-skill:
ux-case-study/ ← existing skill, unchanged
└── memory/ ← new
├── house-style.md NDA outcome phrasings; client-team crediting; banned claims
├── glossary.md sector terms, role titles, client name handling
├── corrections.jsonl starts empty
└── ratings.jsonl starts empty
└── examples/
├── gold/ ← new
│ ├── cs-2025-hax/ brief.md + materials/ + final.html
│ ├── cs-2025-atlas/ brief.md + materials/ + final.html
│ └── cs-2026-ai-eam/ brief.md + materials/ + final.html
└── index.md
Drop 3–5 best published case studies into examples/gold/ with their source materials. Write house-style.md v0 with Neeraj — NDA phrasings, crediting patterns, banned claims. Neeraj owns review of every promotion to the gold folder. Commit via commit-skills-to-git.
One case study per week. Capture every correction. Neeraj reviews each piece for NDA compliance before promotion. Test prompt:
Case study for [client]. Materials: brief + 18 Figma screens + 2 testimonials + outcome memo. Sector: enterprise SaaS. Use NDA phrasing for revenue impact (under review).