LLM Workflows

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Turn Repetitive Knowledge Work Into Intelligent Automation

Your team spends 70% of their time on tasks that require intelligence but follow patterns: analyzing documents, writing reports, extracting insights, generating content. These require understanding, context, and judgment beyond simple if-then automations. LLM workflows automate this intelligent grunt work, transforming months of manual analysis into minutes of automated processing.

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What Are LLM Workflows?

LLM workflows are intelligent automation systems that combine the reasoning capabilities of Large Language Models with programmatic execution. Unlike traditional automation that breaks with any variation, LLM workflows understand context, adapt to nuance, and handle complexity.

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The 200x Speed Advantage

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LLM Workflows We Build

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Research & Intelligence Automation

Transform how you gather and synthesize information

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Content Generation Pipelines

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Customer Intelligence Systems

Understand customers at scale: Results from Implementation:

• 70% reduction in response time
• 90% accurate triage
• Identified 200% more at-risk accounts
• Prevented $500K in churn

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Quality Assurance Automation

Maintain standards at scale: Marketing Agency QA System

• Reviews all deliverables before client submission
• Checks brand guidelines compliance
• Verifies factual accuracy
• Ensures tone consistency
• Flags potential issues
• Result: 80% fewer client revisions

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Sales Intelligence Workflows

Supercharge your sales team: Proposal Generation System

• Analyzes discovery call transcript
• Pulls relevant case studies
• Customizes messaging for prospect
• Generates pricing options
• Creates personalized proposal
• Time: 30 minutes vs. 2 days

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How LLM Workflows Handle Complexity

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Context Understanding

LLMs understand nuance that breaks traditional automation:

• Sarcasm in customer feedback
• Urgency implied but not stated
• Cultural context in communications
• Technical jargon across industries

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Adaptive Processing

Workflows adjust based on content:

• Different analysis for B2B vs. B2C
• Varying detail levels for executives vs. operators
• Platform-specific content optimization
• Industry-appropriate language

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Error Recovery

Self-healing workflows that handle edge cases:

• Retry with different prompts
• Fall back to alternative models
• Flag uncertain outputs for review
• Learn from corrections

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Real Implementation: Content Intelligence Platform

Look at our Fingers on Pulse implementation that processes thousands of hours of YouTube content:

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Architecture

Channel Discovery → Video Scraping → Transcript Extraction → LLM Analysis → Insight Storage → Trend Detection

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The Magic: Parallel Processing

We process 200 videos simultaneously using advanced parallel processing techniques with retry mechanisms and timeout controls.

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Structured Output Generation

Our system generates structured insights including talking points, categories, summaries, keywords, learnings, and relevance scores from video transcripts.

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Common LLM Workflow Patterns

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Building Robust LLM Workflows

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Handling Scale

• Batch Processing: Process thousands of items in parallel
• Rate Limiting: Respect API limits intelligently
• Caching: Avoid redundant LLM calls
• Queue Management: Prioritize and distribute work

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Ensuring Quality

• Structured Outputs: Use schemas for consistency
• Validation Layers: Verify LLM outputs
• Human-in-the-Loop: Flag uncertain results
• Continuous Monitoring: Track accuracy metrics

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Managing Costs

• Model Selection: Use appropriate models for each task
• Prompt Optimization: Minimize token usage
• Caching Strategy: Store and reuse results
• Batch Operations: Reduce API call overhead

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ROI of LLM Workflows

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Real Client Success Stories

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EdTech Platform: Content Intelligence

• Challenge: Keep curriculum current with industry trends
• Solution: LLM workflow monitoring 800+ YouTube channels
• Result: Content lag reduced from 6 months to same week
• ROI: 200x faster research, 75% time savings

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B2B Agency: Automated Reporting

• Challenge: 10 hours per client for monthly reports
• Solution: LLM workflow generating narratives from data
• Result: Reports in 10 minutes with better insights
• ROI: 60x time reduction, 40% margin improvement

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E-commerce: Review Analysis

• Challenge: 50,000 reviews across 1,000 products
• Solution: LLM workflow extracting insights and trends
• Result: Product improvements identified weekly vs. quarterly
• ROI: 90% faster feedback loop, 25% better products

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Why WithSeismic for LLM Workflows

We’ve been building LLM systems since before ChatGPT. Our production workflows have:

• Processed millions of content pieces
• Generated hundreds of thousands of outputs
• Saved clients thousands of hours
• Created real business value, not demos

We understand the nuances:

• When to use GPT-4 vs. lighter models
• How to handle failures gracefully
• Managing costs at scale
• Ensuring consistent quality
• Building maintainable systems

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The Future of Knowledge Work

LLM workflows eliminate the parts of knowledge work that burn people out. Your team shouldn’t spend time on:

• Reading and summarizing documents
• Extracting data from reports
• Writing routine communications
• Analyzing standard patterns
• Creating derivative content

They should focus on:

• Strategic thinking
• Creative problem solving
• Relationship building
• Innovation
• High-value decisions

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Getting Started with LLM Workflows

Build Your LLM Workflow

Book Doug’s sprint to build intelligent automation that processes in minutes what currently takes weeks. Transform repetitive knowledge work into strategic advantage.