Building LinkedIn Carousels with Claude Skills: An Automation Journey

TLDR

Learn how to automate LinkedIn carousel creation using Claude Skills and HTML/CSS, reducing the time from hours in Canva to under 5 minutes with consistent branding.

From Manual Struggles to Automated Success

TLDR: A creator solved the LinkedIn carousel problem by building an automated system that generates branded carousels in under 5 minutes.

For months, a content creator struggled with LinkedIn carousels despite seeing their effectiveness. The problem wasn't motivation but the effort-to-output ratio: 1 hour writing content, 1 hour wrestling with Canva, and 30 minutes fixing alignment and spacing. The mental overhead of wondering "does this look professional?" made carousels feel impossible to implement consistently.

The breakthrough came when Claude Code became the entire newsletter operating system, knowing the creator's voice, performance data, content archive, and audience patterns. This semi-automatic system worked for everything except carousels, which remained a friction point due to design complexity.

The solution involved building a Claude Skill that takes brand guidelines and content inputs to generate HTML/CSS code for carousels. This approach provides reliable outputs with consistent branding, unlike AI image generators that struggle with consistency across multiple slides.

For architects and teams building content automation systems, this demonstrates the importance of choosing the right technology for consistency. Code-based solutions offer more reliable reproducibility than AI-generated images for multi-part content.

Key takeaways:

Automation should solve actual workflow friction points, not just add features
Code-based solutions offer more consistency than AI image generation for multi-part content
Understanding the complete workflow helps identify the right automation approach

Tradeoffs: The creator gains speed and consistency with HTML/CSS automation but must invest time upfront to build the system instead of using off-the-shelf tools.

Link: How I Built LinkedIn Carousels Using Claude Skills in Less Than 5 Minutes

The Three-Approach Journey to Carousel Automation

TLDR: Multiple failed attempts led to the successful HTML/CSS solution after trying PowerPoint builders and AI image generation.

The journey to carousel automation involved three distinct approaches, each with valuable lessons:

PowerPoint Slide Builder: Claude Skills successfully created slides but the output was too plain and lacked creativity. While fast (3-5 seconds per slide), it looked generic and didn't meet brand standards.
AI Image Generation (Nano Banana Pro): This approach produced stunning designs with clean colors, on-brand styling, and sharp text. However, consistency was a major issue - each slide had random icon placements, different spacing, and shifted elements. Attempts to solve this with Glif's editing features worked temporarily but required manual editing of each slide.
HTML/CSS Code Solution: Recognizing that code is more reproducible than AI-generated images, the creator built a Claude Skill that takes brand guidelines and content inputs to generate clean HTML/CSS code. This approach provided exactly what was needed: reliable outputs with good design consistency.

The HTML/CSS approach succeeded because Claude is exceptional at writing these languages, which are essentially layout and styling instructions. Unlike image generation, code is perfectly reproducible, ensuring consistent branding across all carousel slides.

For architects and teams implementing automation, this illustrates the importance of choosing the right technology for the specific consistency requirements of the task.

Key takeaways:

Multiple iterations and failed attempts often precede successful automation
Different technologies excel at different aspects of content creation
Reproducibility is crucial for multi-part content automation

Tradeoffs: The HTML/CSS approach requires more technical setup but provides superior consistency compared to AI image generation methods.

Link: How I Built LinkedIn Carousels Using Claude Skills in Less Than 5 Minutes

The Claude Skill System Architecture

TLDR: A well-designed Claude Skill automates carousel creation through brand configuration and content input processing.

The final Claude Skill system operates through a simple but effective architecture:

Brand Configuration Setup: A one-time 1-minute process where Claude receives brand specifications:
- Brand colors (primary, secondary, accent)
- Typography preferences (headers, body text)
- Logo file
- Profile photo
- Positioning statement This information is stored in a configurable brand file that persists across conversations.
Content Input Options: Two pathways for creating carousels:
- Direct text input: Paste any content (voice notes, Twitter threads, bullet points)
- Newsletter URL: Claude fetches content, analyzes structure, and breaks it into slides
Template Selection: Three design templates to match content style:
- Default: Clean, professional, minimal design
- Bold: Decorative waves, mixed typography, larger text
- Technical: Swiss Brutalist design and geometric accents
Output Generation: Claude generates complete HTML/CSS files that render as carousels, ready for screenshot and LinkedIn upload.

For architects and teams building similar automation systems, this demonstrates the importance of separating configuration from content processing, allowing for reusable systems that maintain brand consistency.

Key takeaways:

Separating configuration from content processing enables reusable automation systems
Template options accommodate different content styles while maintaining consistency
Persistent configuration reduces friction in repeated use

Tradeoffs: The system requires initial setup time but dramatically reduces ongoing content creation effort.

Link: How I Built LinkedIn Carousels Using Claude Skills in Less Than 5 Minutes

Manual Approach for Proof of Concept

TLDR: A manual version of the HTML/CSS approach allows testing the concept before full automation.

For those wanting to validate the HTML/CSS approach before building full automation, a manual process proves the concept:

Setup Brand Guidelines: In Claude, provide brand specifications including colors, fonts, logo, and profile photo
Content Input: Paste content or provide newsletter URLs for Claude to process
Structure Definition: Specify slide structure (Hook, Main content, CTA)
HTML/CSS Generation: Claude creates the code files
Output Processing: Open in browser, screenshot slides, convert to PDF, upload to LinkedIn

This manual approach takes 15-30 minutes initially but can be reduced to 10-15 minutes with practice. It validates whether the HTML/CSS approach works for specific content styles before investing in full automation.

For architects and teams evaluating automation opportunities, this demonstrates the value of manual proof-of-concept before building complex systems.

Key takeaways:

Manual proof-of-concept validates automation concepts before investment
HTML/CSS approach offers consistent results for multi-part content
Time investment decreases significantly after initial learning

Tradeoffs: Manual approach requires more time per carousel but needs no system building investment.

Link: How I Built LinkedIn Carousels Using Claude Skills in Less Than 5 Minutes

Disclaimer

This newsletter summary was automatically generated. The content reflects the views of the original authors and not necessarily those of the generator. Please refer to the original sources for complete information and context.