Official Pre-Order Release
RECRUITED
The Inbound Recruitment Blueprint: Make Recruiters Come to You
The Core Promise: Transform from an invisible job seeker sending hundreds of resumes into a
sought-after professional that recruiters actively chase — in 6 to 12 months.
📊 The Cold Reality of the 2026 Job Market
619,000+
Tech Layoffs Worldwide Since 2023 (Q1 2026 Worst Quarter Since 2024)
80%
Of Jobs Are Never Publicly Posted (The Hidden Job Market)
25–30%
Of Public Listings Are “Ghost Jobs” With No Hiring Intent
8 Offers
In 8 Months Received by Author Using Inbound Strategy
💡 The Author’s Proof: Why This System Works
While thousands of professionals were receiving rejection emails, Thomas Cherickal received 8 job offers in 8 months. The secret was not spamming resumes or lying on LinkedIn — it was building public proof of expertise, deploying privacy-first AI tools, and mastering inbound recruitment so that employers reached out first.
❌ The Dead-End Way
Sending 500+ resumes into ATS black holes, optimizing buzzwords with generic AI, getting zero responses or ghosted after Round 1.
✅ The Inbound Blueprint
Public proof of expertise, continuous technical thought leadership, active personal branding on LinkedIn, and mastering Google Antigravity & NotebookLM.
📖 Complete Table of Contents (~355 Pages)
PART 1: THE NEW REALITY FOR LANDING A JOB
Pages 1–31
Chapter 1: The Great Disruption
Pages 2–9
619K+ tech layoffs, AI-driven restructuring (Oracle ~30K, Amazon ~16K, Meta ~8K, MSFT ~8.75K), Boris Cherny’s 100% AI-generated code workflow, and Anthropic’s 70-90% AI codebase data.
Chapter 2: The Hidden Job Market
Pages 10–20
Why 80% of jobs are filled via referral networks, 25-30% ghost job listings, employer hiring costs, and the 5-step LinkedIn networking sequence without cold DM spam.
Chapter 3: AI — Threat and Opportunity
Pages 21–31
The Learner’s Mindset (7 commitments), author’s personal pivot story (Developer → SEO/GEO → AI Consultant), and salary roadmaps across 24 technical & creative roles.
PART 2: AI TOOLS YOU NEED TO KNOW
Pages 32–131
Chapter 4: Google Antigravity
Pages 33–45
The Agent-First IDE from Google. Editor vs Manager View, Agent Skills, MCP protocol integration, asynchronous feedback loops, and 9 production-grade prompt templates.
Chapter 5: NotebookLM
Pages 46–67
Google’s grounded 2M context AI notebook. Audio Overviews (Join Mode), citation verification, 10 career workflows, Studio outputs (Video, Infographics, PPTX), and Gemini app integration.
Chapter 6: Perplexity.ai & Git / GitHub
Pages 68–81
Real-time intelligence engine, Model Council, Perplexity Computer, Comet Browser, combined with GitHub profile README standards and public proof systems.
Chapter 7: Google AI Studio
Pages 82–96
Designing custom prompts, system instructions, temperature tuning, and rapid prototyping using Gemini 2.5 Flash & Pro models.
Chapter 8: Claude Pro
Pages 97–111
Claude Opus 4.7 & Sonnet 4.6, Artifacts workspace, extended thinking mode, and complex reasoning for technical writing & code design.
Chapter 9: Powerful Workflows with All AI Tools Together
Pages 112–131
Orchestrating multi-tool pipelines (Perplexity → NotebookLM → AI Studio → Antigravity) for complete career acceleration automation.
PART 3: BUILDING YOUR FOUNDATION
Pages 132–161
Chapter 10: Personal Brand Architecture
Pages 132–139
Defining your niche, value proposition, content pillars, and public proof assets.
Chapter 11: LinkedIn Mastery
Pages 140–147
Profile overhaul, headline optimization, 2-3x weekly posting cadence, and engagement loops.
Chapter 12: Essential AI Skills
Pages 148–154
Prompt engineering, context management, and AI-assisted problem solving.
Chapter 13: Advanced AI Applications
Pages 155–161
Custom workflow creation, API integrations, and personal knowledge management.
PART 4: ROLE BLUEPRINTS — TECHNOLOGY & ENGINEERING
Pages 162–191
Chapter 14: Top-Paying Roles — AI/ML, Cloud & Cybersecurity
Pages 162–169
Strategies for AI/ML ($150K–$900K TC), Cloud Architecture ($140K–$250K), and Cybersecurity Engineers ($125K–$220K+).
Chapter 15: Top-Paying Roles — Data Science, DevOps & Full-Stack
Pages 170–176
Optimizing Data Science ($150K–$225K), DevOps ($130K–$195K), and Full-Stack Vibe-Coding workflows.
Chapter 16: AI Mastery — Product, Solutions & Data
Pages 177–184
Blueprints for AI Product Managers ($115K–$300K), Solutions Architects, and Data Engineers.
Chapter 17: AI-Native Roles — UX/UI, Eng Management & Prompt Engineering
Pages 185–191
UX/UI design, Engineering Managers ($187K–$287K), and Prompt/LLM Engineers ($110K–$350K+).
PART 5: ROLE BLUEPRINTS — WRITERS, CREATIVES & OPS
Pages 192–221
Chapter 18: The Writer — Content, Technical & Book Author
Pages 192–199
AI-augmented content strategy, documentation sites, and publishing books.
Chapter 19: The AI Creative — Graphic Designer, Artist & Musician
Pages 200–207
Generative visual arts, Suno/Udio music production, and design A/B testing.
Chapter 20: The AI Professional — Project Management, Sales & Marketing
Pages 208–214
Automated sales intelligence, PM risk evaluation, and dynamic marketing segmentation.
Chapter 21: AI Strategy & Ops — Operations, Customer Success & Consultant
Pages 215–221
Enterprise AI consulting, churn prediction, and workflow automation.
PART 6: EXECUTION
Pages 222–255
Chapter 22: The 6-Month Roadmap
Pages 222–232
Step-by-step month-by-month execution plan for brand building and inbound attraction.
Chapter 23: Daily LinkedIn Practice
Pages 233–239
Daily routines, post formats, engagement techniques, and analytics tracking.
Chapter 24: Technical Skill Development
Pages 240–245
Building working demos, open-source contributions, and public repositories.
Chapter 25: Authentic Networking
Pages 246–251
Building genuine industry relationships without cold-calling or job-begging.
Chapter 26: Conclusion: The Choice Is Yours
Pages 252–255
Taking complete ownership of your career trajectory in an AI-first world.
PART 7: AI AGENT ORCHESTRATORS
Pages 288–327
Chapter 27: OpenClaw — The Local-First Autonomous Agent Runtime
Pages 288–297
Deploying local autonomous agent runtimes for privacy-preserving automation.
Chapter 28: Hermes Agent — The Self-Learning Autonomous Agent
Pages 298–307
Self-improving agentic workflows, memory retention, and tool calling.
Chapter 29: OpenFang — The Enterprise Multi-Agent Framework
Pages 308–317
Orchestrating enterprise worker fleets with supervisor agents and MCP protocols.
Chapter 30: How AI Agent Workers Change Work for Everyone
Pages 318–327
The future of employment, hybrid agent-human workforces, and strategic adaptation.
APPENDICES A–E
Pages 256–345
Appendix A: Quick-Start Checklist
Pages 256–261 · Resource guide and immediate action steps.
Appendix B: AI Career Acceleration Toolkit
Pages 262–273 · Prompts, templates, and scripts.
Appendix C: AI Tools Cheat Sheets
Pages 274–275 · Quick reference for Antigravity, NotebookLM, Claude.
Appendix D: Common Errors & Fixes
Pages 276–287 · Troubleshooting agentic & prompt workflows.
Appendix E: Running LLMs Locally — Private AI Infrastructure
Pages 328–345 · Complete setup guide for Ollama, LM Studio, llama.cpp, Qwen, and Gemma models on consumer hardware.
🎯 Who This Book Is For
This book is for professionals ready to take full responsibility for their career and willing to work hard over a 6 to 12 month period. By adopting the 7 commitments of the Learner’s Mindset, you will unlock your true potential:
I am ready to approach all new tools open to all new ideas.
I will take responsibility for my skill levels and my career.
I will practice my skills with AI and learn by doing every single day.
I will build public proof of expertise that recruiters can verify.
I will master local LLMs and agentic workflows before my competitors.
I will commit to a 6–12 month disciplined inbound recruitment strategy.
Pre-Order RECRUITED on Patreon
Support the release on Patreon to receive early access chapters, exclusive AI prompt playbooks, and direct access to author Q&A sessions.
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