Social Media Manager

Your strategic social media director who builds engaged audiences and drives business results across all platforms.

What This Agent Does

The Problem: You’re posting content. Maybe consistently, maybe sporadically. But engagement is flat. Follower growth is stagnant. You can’t tell which posts work and which don’t. You’re spending hours creating content that gets 12 likes and disappears.

Social media feels like shouting into the void. You know it should drive business results, but you’re stuck in the content hamster wheel without a clear strategy.

The Solution: Social Media Manager is your senior strategist who creates platform-specific content calendars, analyzes engagement patterns, optimizes posting strategy, researches trends, and coordinates multi-platform campaigns. Think of it as having a social media director who actually understands what drives results.

No more random posting. No more guessing what works. Just data-driven social strategy that builds audience and drives business outcomes.

Quick Start

30-second example - create content calendar:

You: "Create a week of social content for our AI code tool"

social-media-manager: Building multi-platform content calendar...

CONTENT CALENDAR (Week of Jan 20-26)

Theme: "Build Features 10x Faster"
Goal: Drive 500 trial signups
Platforms: Twitter/X, LinkedIn, Dev.to

MONDAY, JAN 20
━━━━━━━━━━━━━━━━━━
Platform: Twitter/X (9:00 AM EST)
Type: Problem/Solution Hook
Content:

You’ve written authentication code 47 times in your career.

Why are you writing it a 48th time?

ClaudeKit builds it in 6 minutes. → Email login → OAuth (Google, GitHub) → 2FA with SMS → Password reset flow

Production-ready. Tested. Documented.

Try it: [link]

Expected: 2,000+ impressions, 80+ clicks

Platform: LinkedIn (10:00 AM EST)
Type: Case Study Snippet
Content:

“We shipped our MVP in 3 days instead of 3 weeks.”

That’s what Sarah Chen, founder of DataFlow, told us after using ClaudeKit.

Here’s what her AI dev team built in 72 hours: → Full authentication system → Stripe payment integration → REST API with validation → Admin dashboard

4 features that would normally take her team 2-3 weeks.

The best part? She didn’t sacrifice quality. Every line of code passed review. All tests green. Zero security issues.

Want to see how she did it?

Read the full case study: [link]

Expected: 5,000+ impressions, 150+ clicks

TUESDAY, JAN 21
━━━━━━━━━━━━━━━━━━
Platform: Twitter/X (8:30 AM EST)
Type: Quick Tip Thread (3 tweets)
Tweet 1:

3 signs you’re wasting dev time on boilerplate:

1. You’ve copied auth code from Stack Overflow more than once this month
2. Your team argues about which payment gateway to use (for the 5th time)
3. Junior devs spend days on features senior devs could build in hours

There’s a better way 🧵

Tweet 2:

Most dev teams spend 60% of time on features that exist in every SaaS product:

• User auth
• Payments
• Email notifications
• Admin panels

That’s not differentiation. That’s overhead.

Tweet 3:

Your AI dev team can build these in minutes:

ClaudeKit ships production-ready code for: → Authentication: 6 min → Stripe integration: 8 min → REST API: 5 min → Email system: 7 min

You focus on what makes your product unique.

Try it: [link]

Expected: 3,500+ impressions, 120+ clicks

Platform: LinkedIn (3:00 PM EST)
Type: Thought Leadership
Content:

[POST TITLE: The End of Boilerplate Development]

I’ve been writing code for 15 years.

In that time, I’ve built authentication systems 34 times. Payment integrations 28 times. REST APIs? Lost count.

Every startup, every side project, every new job - same code, slightly different requirements.

We joke about “reinventing the wheel” but that’s exactly what we do. Daily.

Here’s what changed: AI can now write this code for us.

Not snippets. Not suggestions. Complete, production-ready features.

I tested this last week. My AI teammate built a full auth system in 6 minutes:

• Email & OAuth login
• Password reset flow
• 2FA with SMS
• Session management
• Unit tests (94% coverage)

The code? Cleaner than I would have written.

This isn’t about replacing developers. It’s about freeing us to build what actually matters.

The authentication system isn’t your competitive advantage. Your unique features are.

Let AI handle the boilerplate. You handle the innovation.

What do you think - is this the future of development?

#SoftwareDevelopment #AI #Productivity

Expected: 8,000+ impressions, 200+ clicks

WEDNESDAY, JAN 22
━━━━━━━━━━━━━━━━━━
Platform: Dev.to (Morning publish)
Type: Technical Deep-Dive
Title: "I Let AI Build My Authentication System (Here's What Happened)"
Content: [1,500-word technical tutorial]
→ Step-by-step walkthrough
→ Code examples with explanations
→ Security considerations discussed
→ Performance benchmarks
→ Comparison with manual implementation

Expected: 2,000+ views, 100+ reactions

Platform: Twitter/X (2:00 PM EST)
Type: Social Proof
Content:

1,247 developers shipped code yesterday with ClaudeKit.

Here’s what they built:

🔐 Authentication systems: 412 💳 Payment integrations: 287 📧 Email automation: 334 🚀 REST APIs: 589 📊 Admin dashboards: 156

Zero P0 bugs. Zero security incidents. 100% production-ready.

Your turn: [link]

Expected: 2,500+ impressions, 90+ clicks

THURSDAY, JAN 23
━━━━━━━━━━━━━━━━━━
Platform: Twitter/X (9:00 AM EST)
Type: Comparison Chart (Visual)
Content:

Time to build authentication (2025):

Manual coding: └─ Research OAuth providers: 2 hours └─ Implement email/password: 3 hours └─ Add 2FA: 2 hours └─ Password reset flow: 1 hour └─ Session management: 1 hour └─ Security review: 2 hours └─ Write tests: 2 hours Total: 13 hours (nearly 2 days)

With ClaudeKit: └─ Describe requirements: 1 minute └─ AI builds complete system: 5 minutes └─ Review & deploy: 15 minutes Total: 21 minutes

Choose wisely.

Try it: [link]

[Include visual comparison chart]
Expected: 4,000+ impressions, 150+ clicks

Platform: LinkedIn (11:00 AM EST)
Type: FAQ / Objection Handling
Content:

“But can AI really write production-quality code?”

I was skeptical too.

Here’s what I learned after shipping 12 AI-generated features to production:

Q: Is it secure? A: More than my code. AI follows OWASP guidelines consistently. I don’t always remember to.

Q: Does it have tests? A: Every feature ships with 90%+ test coverage. Mine? Maybe 60% on a good day.

Q: What about edge cases? A: AI considers cases I’d miss. It’s read millions of codebases.

Q: Can I customize it? A: It’s your code. Edit anything. No black box.

Q: What if it makes mistakes? A: It does. Rarely. But so do I. Code review catches both.

The real question: Why waste your time writing code that’s been written a million times before?

Let AI handle the boilerplate. You build what makes your product unique.

Curious? See how it works: [link]

Expected: 6,000+ impressions, 180+ clicks

FRIDAY, JAN 24
━━━━━━━━━━━━━━━━━━
Platform: Twitter/X (8:00 AM EST)
Type: Behind-the-Scenes / Founder Story
Content:

I built my startup’s MVP in 3 days.

Not because I’m a 10x engineer.

Because I stopped writing boilerplate.

Day 1: Auth system (6 min) + Stripe (8 min) Day 2: REST API (5 min) + Email (7 min) Day 3: Admin dashboard + actual unique features

Total: 26 minutes of boilerplate, 3 days of innovation.

That’s the power of AI dev tools.

[link to launch story blog post]

Expected: 3,000+ impressions, 100+ clicks

Platform: LinkedIn (4:00 PM EST)
Type: Weekly Wrap-Up
Content:

Quick wins from the ClaudeKit community this week:

🚀 Sarah shipped her MVP 2 weeks ahead of schedule 💰 Marcus reduced his dev costs by $15K/month ⚡ Jessica’s team velocity increased 3x 🎯 David pivoted his product in 48 hours

The pattern? They all stopped writing boilerplate and focused on what makes their product unique.

What could you build if you freed up 60% of your dev time?

Curious? Join 1,200+ developers already shipping faster: [link]

Have a great weekend! 👋

Expected: 4,000+ impressions, 120+ clicks

CONTENT THEMES:
→ Monday: Problem/solution hook (grab attention)
→ Tuesday: Educational content (provide value)
→ Wednesday: Deep-dive technical (build authority)
→ Thursday: Objection handling (address skepticism)
→ Friday: Social proof + CTA (drive conversions)

POSTING SCHEDULE:
→ Twitter/X: Daily, 8-9 AM EST (highest engagement)
→ LinkedIn: 3-4x per week, 9-11 AM or 3-5 PM EST
→ Dev.to: 1x per week, Wednesday (technical audience online mid-week)

ENGAGEMENT TACTICS:
1. Respond to all comments within 2 hours
2. Quote-tweet relevant conversations about AI/development
3. Share user-generated content (retweet customer wins)
4. Join trending conversations (#100DaysOfCode, #BuildInPublic)
5. DM power users who engage frequently

METRICS TO TRACK:
- Impressions: Target 50K+ per week
- Engagement rate: Target 3-5%
- Profile visits: Target 800+ per week
- Link clicks: Target 600+ per week
- Trial signups from social: Target 100+ per week

Want me to create next week's calendar or adjust this strategy?

Capabilities

1. Multi-Platform Content Creation

Adapt messaging for each platform’s algorithm and audience.

Platform-Specific Best Practices:

Twitter/X:

• First 140 characters are critical (preview text)
• Short, punchy sentences
• No hashtags (hurt reach)
• Threads for storytelling
• Engagement bait: Questions, hot takes, lists

LinkedIn:

• First 2 lines must hook (before “see more”)
• Professional but not corporate
• Data and stories over fluff
• Best times: Weekday mornings (9-11 AM EST)
• Use personal voice, not brand

Instagram:

• Visual-first content
• Stories for behind-the-scenes
• Reels for reach (algorithm favors video)
• Carousel posts for educational content
• Hashtags still work (use 5-10 relevant)

TikTok:

• First 3 seconds decide watch time
• Trending audio boosts reach
• Hook → Value → CTA format
• Caption: Short, direct
• Post 1-3x per day for algorithm

Facebook:

• Community focus over brand
• Longer posts perform well
• Questions drive comments
• Groups > Pages for engagement
• Video gets 5x reach vs text

2. Content Calendar Management

Plan themes, coordinate campaigns, maintain consistency.

Example - Monthly Theme Calendar:

JANUARY THEME: "Ship 10x Faster"
Goal: 200 trial signups
Strategy: Showcase speed + quality

Week 1: Problem awareness (slow dev cycles)
Week 2: Solution education (how AI helps)
Week 3: Social proof (customer stories)
Week 4: Conversion push (limited-time offer)

Week 1 Content Mix:
→ 40% Problem posts ("You've written auth 47 times...")
→ 30% Educational ("3 signs you're wasting dev time...")
→ 20% Social proof ("1,200 devs shipped yesterday...")
→ 10% Direct CTA ("Try it free...")

Platform priorities:
→ Twitter/X: Daily (high volume, high reach)
→ LinkedIn: 3x/week (professional audience)
→ Dev.to: 1x/week (technical deep-dive)
→ Instagram: 2x/week (visual content)

Content types:
→ 50% Original posts
→ 30% Curated/reshared content
→ 20% User-generated content

Coordination with campaigns:
→ Email campaign launches Tuesday (align social)
→ Product launch Jan 15 (ramp up social Week 2-3)
→ Webinar Jan 22 (promote on LinkedIn)

3. Engagement Analysis

Track what works, double down on winners.

Example - Performance Analysis:

LAST 30 DAYS PERFORMANCE:

Top Performing Posts:

1. Twitter Thread: "3 signs you're wasting dev time"
   → 12,400 impressions (+310% vs avg)
   → 487 engagements (3.9% rate)
   → 127 link clicks (10.2% CTR)
   → Why it worked: Problem-focused, relatable, actionable

2. LinkedIn Post: "I built my MVP in 3 days"
   → 18,200 impressions (+425% vs avg)
   → 1,240 reactions (6.8% rate)
   → 89 comments (high engagement)
   → Why it worked: Personal story, specific outcome, credible

3. Dev.to Article: "AI-Generated Auth System Tutorial"
   → 3,800 views
   → 284 reactions
   → 47 bookmarks
   → Why it worked: Technical depth, code examples, useful

Lowest Performing Posts:

1. Twitter: "Check out our new feature"
   → 340 impressions (-91% vs avg)
   → 8 engagements (2.4% rate)
   → Why it failed: Generic, brand-centric, no hook

2. LinkedIn: "We're hiring!"
   → 1,200 impressions (-72% vs avg)
   → 12 reactions (1.0% rate)
   → Why it failed: Self-promotional, not valuable to audience

INSIGHTS:

Content that works:
✓ Personal stories with specific outcomes
✓ Problem-focused hooks
✓ Educational/tutorial content
✓ Data-driven social proof
✓ Behind-the-scenes founder content

Content that flops:
✗ Generic announcements
✗ Brand-centric posts
✗ Vague benefits ("boost productivity")
✗ Hiring posts
✗ "Happy Monday!" fluff

RECOMMENDATIONS:

Double down on:
→ Twitter threads (3x engagement vs single tweets)
→ LinkedIn personal stories (5x reach vs brand posts)
→ Technical tutorials (highest conversion rate)
→ Customer success stories (2x engagement vs features)

Reduce:
→ Generic product announcements
→ Self-promotional content
→ Holiday greeting posts

Optimal posting times (by platform):
→ Twitter: 8-9 AM EST (commute time)
→ LinkedIn: 10-11 AM EST (work break)
→ Dev.to: Wednesday morning (mid-week reading)

Content mix adjustment:
→ Current: 60% product, 30% educational, 10% personal
→ Recommended: 30% product, 40% educational, 30% personal
→ Expected improvement: +40% engagement rate

4. Trend Research

Identify and leverage trending topics.

Example:

TRENDING OPPORTUNITIES (This Week):

1. #AIEngineering trending on Twitter
   → 28K mentions in last 48 hours (+340%)
   → Opportunity: Position ClaudeKit in AI engineering conversation
   → Content angle: "AI isn't replacing developers, it's removing boilerplate"
   → Action: Tweet thread on "The Rise of AI-Assisted Development"

2. "Developer Productivity" rising on LinkedIn
   → 12K posts mentioning productivity this week
   → Opportunity: Share productivity data/case studies
   → Content angle: "How we 3x developer velocity with AI"
   → Action: Detailed post with metrics, customer quotes

3. "Build in Public" community engagement high
   → #BuildInPublic hashtag: 45K uses last 30 days
   → Opportunity: Share our own building journey
   → Content angle: Founder behind-the-scenes development stories
   → Action: Weekly thread: "What we shipped this week"

4. GPT-4 API news cycle
   → OpenAI announcement driving AI dev tool interest
   → Opportunity: Ride the news wave
   → Content angle: "What GPT-4 API means for developers"
   → Action: Expert perspective post (position as thought leader)

5. Y Combinator Demo Day buzz
   → Startup community actively discussing YC companies
   → Opportunity: Connect with founder audience
   → Content angle: "What we learned from YC W24 companies"
   → Action: Insights post for startup founders

HASHTAG PERFORMANCE:

High engagement (use):
✓ #Developer (general, high reach)
✓ #SoftwareDevelopment (professional)
✓ #BuildInPublic (community-focused)
✓ #IndieHacker (startup audience)

Low engagement (avoid):
✗ #AI (too generic, low conversion)
✗ #Technology (too broad)
✗ #Innovation (corporate buzzword)
✗ #FridayFeeling (irrelevant)

COMPETITOR TRENDING CONTENT:

What's working for competitors:
→ GitHub Copilot: Technical tutorial videos (high shares)
→ Vercel: "Built with Vercel" user showcases (social proof)
→ Supabase: Memes + education blend (high engagement)

Gaps we can fill:
→ No competitor doing founder storytelling well
→ Limited technical deep-dives (opportunity for Dev.to)
→ Few case studies with real metrics (we can own this)

RECOMMENDED CONTENT (Next 7 Days):

Monday: Ride #AIEngineering trend with Twitter thread
Tuesday: LinkedIn post on developer productivity (data-driven)
Wednesday: Dev.to technical tutorial (evergreen + trending topic)
Thursday: Behind-the-scenes founder story (Build in Public)
Friday: React to GPT-4 news with expert take

Expected reach: 75K impressions (vs 45K avg week)

5. Cross-Platform Strategy

Coordinate messaging across channels.

Example - Product Launch Campaign:

PRODUCT LAUNCH: New AI Code Review Feature
Launch Date: January 30
Goal: 500 beta signups in 7 days

CROSS-PLATFORM STRATEGY:

Pre-Launch (Days -7 to -1):
→ Twitter: Teaser posts, countdown
→ LinkedIn: Problem awareness content
→ Email: Early access list building
→ Dev.to: Educational content leading to solution

Launch Day (Day 0):
→ Twitter: Announcement thread (8:00 AM EST)
→ LinkedIn: Detailed feature post (9:00 AM EST)
→ Product Hunt: Launch (12:01 AM PST)
→ Email: Send to full list (10:00 AM EST)
→ Dev.to: Technical deep-dive (Morning publish)
→ Hacker News: Submit (2:00 PM EST)

Post-Launch (Days 1-7):
→ Twitter: User testimonials, use cases, tips
→ LinkedIn: Case studies, customer stories
→ Email: Follow-up sequence (5 emails over 7 days)
→ Dev.to: Tutorial series (3 posts)

CONTENT SYNCHRONIZATION:

Core message (all platforms):
"AI code review that catches bugs before deploy"

Platform-specific angles:

Twitter: Speed + Social proof
"1,200 devs caught 247 bugs before production this week.
Zero P0 incidents. Zero 3am pages.
New AI code review now in beta: [link]"

LinkedIn: Professional + Impact
"Last month, production bugs cost us $45K in lost revenue.

This month? $0.

Here's what changed: AI code review that runs before every merge.

It caught bugs I missed:
→ Auth bypass vulnerability
→ Memory leak in checkout
→ SQL injection in user input

Same AI that reviewed 10,000 PRs last week.
Zero false positives. Zero missed critical bugs.

Now in beta. Limited spots: [link]"

Dev.to: Technical + Tutorial
"I Integrated AI Code Review Into CI/CD (Here's How)"
[1,800-word technical walkthrough with code examples]

Email: Direct + Benefit-focused
Subject: "Stop bugs before they hit production"
Preview: "The code review tool that caught 247 bugs last week..."

Product Hunt: Concise + Value prop
"AI code review for your CI/CD pipeline
→ Catches bugs before deploy
→ Zero false positives
→ Integrates with GitHub, GitLab, Bitbucket
Free during beta: [link]"

TIMING COORDINATION:

All platforms launch same day at staggered times:
→ 12:01 AM: Product Hunt (must be first for ranking)
→ 8:00 AM: Twitter (commute time, high visibility)
→ 9:00 AM: LinkedIn (work hours engagement)
→ 10:00 AM: Email (inbox prime time)
→ 11:00 AM: Dev.to (article goes live)
→ 2:00 PM: Hacker News (afternoon tech audience)

ENGAGEMENT RESPONSE PLAN:

Prepared responses for common questions:
Q: "How is this different from GitHub Copilot?"
A: "Copilot writes code. We review it. Complementary tools."

Q: "What languages supported?"
A: "JavaScript, TypeScript, Python, Go, Rust. More coming soon."

Q: "Pricing?"
A: "Free during beta. $29/mo per developer after (launching Q2)."

Q: "False positive rate?"
A: "< 2%. We only flag real bugs, not style preferences."

METRICS TRACKING:

By platform:
→ Twitter: Impressions, clicks, signups
→ LinkedIn: Reach, engagement, profile visits
→ Product Hunt: Upvotes, comments, signups
→ Email: Open rate, click rate, signups
→ Dev.to: Views, reactions, signups

Success criteria:
→ Total reach: 200K+ impressions
→ Total engagement: 5K+ interactions
→ Beta signups: 500+ (primary goal)
→ Product Hunt: Top 5 product of the day
→ Press mentions: 3+ tech blogs

TEAM RESPONSIBILITIES:

Social Media Manager (you):
→ Publish all scheduled content
→ Monitor engagement real-time
→ Respond to comments/questions within 30 min

Founder:
→ Be available for interviews/podcasts
→ Engage in comments on LinkedIn
→ Available for community Q&A

Customer Success:
→ Answer technical questions
→ Share customer success stories
→ Provide beta support

Want me to create the detailed content calendar for this launch?

When to Use Social Media Manager

Perfect for:

• Content calendar creation
• Multi-platform strategy
• Engagement optimization
• Trend research and positioning
• Social campaign coordination
• Audience growth strategy

Not needed for:

• Individual post copywriting (use Copywriter)
• Community management (use Community Manager)
• Paid social ads (use Campaign Manager)
• Long-form content (use Content Creator)

Example Workflows

Workflow 1: Monthly Content Calendar

1. You: "Create January social content calendar"

2. social-media-manager: Strategic planning
   - Defines monthly theme
   - Plans 4-week content arc
   - Creates platform-specific posts
   - Schedules optimal timing
   - Sets engagement tactics

3. Output:
   ✓ 20+ posts across 4 platforms
   ✓ Mix of educational, social proof, CTA
   ✓ Coordinated with email campaigns
   ✓ Engagement metrics targets set

4. You approve calendar

5. Posts scheduled in social media tool

Workflow 2: Engagement Optimization

1. You: "Our LinkedIn engagement is down 40%"

2. social-media-manager: Performance analysis
   - Analyzes last 30 days content
   - Identifies top/bottom performers
   - Finds pattern in successful posts
   - Researches trending topics

3. Output:
   FINDINGS:
   → Generic product posts: -72% reach
   → Personal founder stories: +425% reach

   RECOMMENDATIONS:
   → Shift from brand to personal voice
   → Focus on storytelling over features
   → Post during optimal times (10-11 AM)

4. You adjust content strategy

5. Engagement improves +85% in 2 weeks

Best Practices

1. Platform-Native Content

Bad: Same post on all platforms Good: Adapt content for each platform’s audience and format

Twitter threads ≠ LinkedIn posts ≠ TikTok videos

2. Consistency Over Volume

Bad: Post 5x one week, 0x next week Good: Post 2-3x per week, every week

Algorithms reward consistency.

3. Engage, Don’t Just Broadcast

Bad: Post and disappear Good: Post, then spend 2 hours responding/engaging

Social media is social. Conversations build audience.

Related Agents

• Copywriter - Write high-converting social copy
• Community Manager - Manage Discord/Slack communities
• Campaign Manager - Coordinate multi-channel campaigns

Related Commands

• /social calendar - Generate content calendar
• /social analyze - Analyze engagement performance
• /social trends - Research trending topics

Social media isn’t about posting. It’s about building an audience that drives business results.

Ready to turn social media into a growth channel? Start strategizing.