Understanding Kakiyo's backend process helps you appreciate how the AI agent creates natural, personalized conversations that feel genuinely human.
The Complete Workflow
Step 1: Initial Prospect Processing
When you provide a prospect list, Kakiyo begins by analyzing each prospect's current connection status with your LinkedIn profile.
Connection check process:
Already connected: AI starts direct conversation immediately
Not connected: AI sends personalized connection request first
This initial assessment determines the conversation starting point for each prospect.
Step 2: Connection Request and Acceptance
For prospects not in your network, the AI sends a connection request and waits for acceptance. Once the invitation is accepted, the real personalization process begins.
No notes strategy: Kakiyo always sends connection requests without notes. Adding notes to LinkedIn invitations significantly reduces acceptance rates because they immediately appear sales-focused and pushy. Clean, note-free invitations feel more natural and professional, leading to higher acceptance rates.
Expected acceptance rates: Normal connection acceptance rates typically range between 30-50%. If your acceptance rates are consistently below 30%, this indicates potential issues with your LinkedIn profile that should be addressed. Refer to LinkedIn profile optimization documentation for guidance on improving your profile's appeal and credibility.
Timing is randomized: The AI waits several hours before taking the next step. This random delay mimics human behavior - real people don't immediately message new connections.
Step 3: Deep Profile Analysis
After connection acceptance, the AI returns to the prospect's profile for comprehensive data collection. This is where the magic of personalization happens.
Information gathered includes:
LinkedIn posts and recent activity
Comments on other posts
Profile description and tagline
Career history and progression
Current role and company details
Skills, endorsements, and recommendations
Any other publicly available information
This scraping process ensures the AI has maximum context for creating personalized messages.
Step 4: Personalized Message Creation
Using the scraped profile data combined with your prompt instructions and offering details, the AI creates a unique first message tailored specifically to that prospect.
Key personalization factors:
Recent LinkedIn posts
Prospect's current role and responsibilities
Recent career changes or achievements
Company context and industry
Personal interests or activities mentioned
Recent posts or engagement patterns
The message feels natural because it's built from real information about the prospect, not generic templates.
Step 5: Natural Response Timing
When prospects reply to messages, the AI doesn't respond immediately. Instead, it waits between 1-8 minutes before generating a response.
Why this timing matters:
Too fast (instant): Appears robotic and automated
Too slow (hours): Prospect loses interest and engagement
Random 1-8 minutes: Mimics natural human response patterns
This randomized timing is crucial for maintaining the human illusion throughout conversations.
Step 6: Intelligent Conversation Management
The AI maintains conversation context and adapts responses based on prospect engagement and previous message history.
Conversation intelligence includes:
Understanding prospect questions and concerns
Handling objections professionally
Maintaining conversation flow and context
Moving toward meeting booking when appropriate
Step 7: Human Intervention Capability
At any point, you can take manual control of conversations while maintaining AI context awareness.
Manual intervention scenarios:
AI remains active: When you send a manual message, the AI acknowledges your input and incorporates it into future responses. If the prospect replies, the AI continues the conversation naturally, building on your manual message.
AI deactivated: You take complete control and handle all responses manually. The AI stops responding until reactivated.
AI reactivated: When you turn the AI back on, it analyzes the entire conversation history, including everything said during manual control, and continues seamlessly.
The Human Behavior Simulation
Every aspect of Kakiyo's operation is designed to replicate authentic human behavior patterns.
Randomization elements:
Connection request timing
Profile analysis delays
Response timing variations
Message length and style variations
Conversation pacing adjustments
Why randomization matters: Predictable, automated patterns are easily detected by platforms and prospects. Random, human-like behavior ensures conversations feel genuine and maintain account safety.
Secure Infrastructure Advantage
No Risky Automation Methods
Unlike other LinkedIn tools, Kakiyo doesn't rely on Chrome extensions or browser console commands that can easily be detected by LinkedIn's security systems.
Why this matters: Many automation tools use methods that create detectable patterns, putting your account at risk of restrictions or bans.
Advanced Behavior Simulation
Kakiyo uses proprietary infrastructure that simulates genuine human interactions on LinkedIn, making operations virtually indistinguishable from manual usage.
Key benefits:
Account safety: Operations appear completely natural to LinkedIn
Long-term reliability: Sustainable approach that adapts to platform changes
Undetectable activity: No digital fingerprints that reveal automation
Superior protection: Built specifically for LinkedIn compliance and safety
This secure infrastructure represents a fundamental advantage over other automation tools, ensuring your account remains safe while scaling your outreach effectively.
Continuous Context Awareness
Throughout the entire process, the AI maintains complete conversation context. Whether you intervene manually or let the AI handle everything, it always understands:
Full conversation history
Prospect's responses and engagement level
Your goals and messaging strategy
Appropriate next steps in the conversation
This context awareness enables seamless transitions between AI and human control while maintaining conversation quality and natural flow.
This sophisticated backend process ensures every conversation feels personal, natural, and genuinely human while operating at scale impossible for manual outreach.