Suraj Sharma

If you learn GTM Engineering, you will never be unemployed again. Stage 1: GTM Data Architecture and Reverse ETL - Learn: Snowflake/BigQuery, Hightouch/Census, identity resolution, API webhooks. - Practice: Build a pipeline that syncs raw Stripe billing data and product usage directly into HubSpot/Salesforce custom objects. - Why: GTM without a single, code-level source of truth is just guessing. Stage 2: Signal and Intent Pipelines - Learn: Website deanonymization (Clearbit), intent data (Bombora), event streaming. - Practice: Build a webhook router that instantly alerts a Slack channel when a target enterprise account visits your pricing page 3 times in one week. - Why: In B2B, timing beats the pitch. You must strike while the intent is hot. Stage 3: AI SDRs and Hyper-Personalization - Learn: Clay, Apollo APIs, LLM data enrichment, web scraping. - Practice: Build an AI agent that scrapes a prospect's recent GitHub commits or podcasts and writes a highly specific, 1:1 cold email. - Why: Generic outbound is dead. AI makes infinite personalization mathematically possible. Stage 4: Product-Led Growth (PLG) Telemetry - Learn: PQL (Product Qualified Lead) scoring, event tracking (Segment/Rudderstack), feature adoption curves. - Practice: Write a script that triggers a high-priority sales alert the second a free-tier user hits a specific "aha moment" API threshold. - Why: The product is your best salesperson. Hand-raisers convert 5x higher than cold outbound. Stage 5…