Developer builds self-improving LinkedIn content system with Claude skills

A developer shared their experience building a self-improving LinkedIn content system using Claude skills instead of traditional prompt templates. The system consists of two interconnected skills that create a feedback loop for continuous improvement.
The two-skill architecture
The first skill is a LinkedIn writing skill that contains the developer's voice patterns, hook structures, post frameworks, and reference examples pulled from their own writing. This ensures Claude writes content that sounds like the developer rather than generic AI output.
The second skill is a performance enhancement skill with five components:
- Data Store: Logs raw post metrics after every post
- Pattern Engine: Identifies what's driving engagement across hook type, structure, topic, and format
- Active Rules: The current playbook that updates based on data analysis
- Inspiration Hooks: A bank of proven angles to pull from
- Evolution Log: Tracks every rule change so the system remembers what it tried and what worked
How the system works
The two skills communicate with each other: the writing skill follows the active rules, while the performance skill updates those rules based on real data. This creates a feedback loop where the system learns from actual performance metrics and adapts its approach.
Results and insights
In one week, the system generated 3 posts that achieved a combined 110K impressions, with one post reaching 56,000 impressions on its own. The content attracted inbound interest from a B2B SaaS startup founder and an AI security agent startup founder without any advertising or outreach.
The developer noted that while the numbers aren't solely attributable to the skill system, the consistency shifted from "some posts do well, most don't" to "most posts do well, and I understand why." They describe the system as "structured feedback" similar to what content teams do—tracking, analyzing, and adapting—but automated through Claude.
The key insight is moving beyond copy-pasting prompts to building skills that contain your voice, can process data, and evolve over time based on performance.
📖 Read the full source: r/ClaudeAI
👀 See Also

Vibe Coding a $20k/Year Enterprise Logistics Platform with Claude and Superpowers
TRMNL replaced ShipHero with Claude and Superpowers in under a month, building a custom fulfillment system with UPS, FedEx, DHL, and USPS integrations for $100 in tokens.

Lessons from Running an AI Business with OpenClaw: Day 14 Insights
After 14 days using OpenClaw to build a business, an AI agent shares insights on implementing effective heartbeats, sub-agent structuring, and system resource management.

OpenClaw User Switches to RunLobster for Managed Infrastructure
A developer spent 4 months troubleshooting OpenClaw issues including agent stalling, config breaks, and unpredictable API costs before switching to RunLobster. The same models and framework worked reliably with multi-step task completion and faster integrations.

OpenClaw Creates 90% of Video Using AI Models for $69.5
A Reddit user created a video where OpenClaw handled 90% of the process, including topic selection, character generation, storyboarding, and video segment generation using GPT-5, VEO3.1 fast, and Nano Banana Pro models, with a total AI cost of $69.5.