Welcome to Homebase AI - A weekly newsletter where we share our interviews with founders & leaders building next-gen AI companies and curate interesting news, insights & trends in the AI space for our community members.

What’s on tap today:

• Podcast

• Our interview with Dor Vardi

• 3 AI Jobs You Can’t Miss

• What's trending in AI this week

• Community Update

• How Homebase Helps You

🎙️ This Week’s Interview

Listen on Spotify | Apple Podcasts 
Watch on YouTube

AI Founder Story

From “spray & pray” to signals that sell

Quick Background

Dor Vardi is the founder of Samplead, a trigger-based outbound platform that hunts for real, person-level buying signals then turns them into conversations that convert. He’s a founder-led seller who did ~1,000 discovery calls before writing code, built ARR the hard way, and believes outbound isn’t dead, just misused.

The 1% Reply Era (and why blunt force fails)

Open rates are noisy, reply rates are sinking, and blasting more inboxes just burns brand equity. Dor argues the math of volume breaks first, and reputations break right after.

The Trigger That Changes Everything

Instead of account-level “intent,” Samplead looks for personal signals: podcasts a prospect just appeared on, GitHub activity, a panel they spoke at yesterday—then writes context that only makes sense for that person.

If there’s no meaningful signal, it waits. Quality beats quantity, every time.

Key Achievements & Insights:

1. The Problem Today →

   Reply rates cratered; mass automation trained prospects to ignore us. Founders see 1% as “normal,” but that’s the symptom of volume-first playbooks.

2. The Breakthrough →

   Move from assumptions to signals. Treat every prospect as a separate case, and only contact when there’s a time-sensitive, person-specific reason.

3. The Proof Story →

   Facing platform limits (e.g., LinkedIn caps), Dor’s team rebuilt motion to get old results with 80% fewer messages by ranking prospects on ICP fit + recency/rarity of signals.

4. The Big Example →

   “Joined a giant LinkedIn group” is weak; “appeared on yesterday’s podcast about your niche” is strong. The smaller the audience for that event, the higher the reply odds.

Why It Matters (vision line)

Outbound survives by sounding human again. Trigger-based outreach + credible personas (founder/exec) + restraint beats an army of AI inboxes every day.

Watch the full interview below! 👇

Samplead at a Glance

Trigger-based outbound to “find the right 20 today,” not spam 2,000; personal signals across social, content, and code; precision-targeted messaging; and workflows built for founder-led selling. Dor’s public posts echo the same mantra:

Signals > Assumptions, Quality > Volume.

The Ultimate Lesson

Sell Before You Scale

Dor focused on traction over funding, did hundreds of calls, and let real conversations tune the product.

Play Long-Game Content

Consistent founder content + podcasts + conferences build an inbound flywheel that compounds—then outbound works like a scalpel, not a sledgehammer.

Outreach That Actually Works | Dor Vardi’s Trigger Loop — Read the full interview →

JOIN THE AI REVOLUTION
AI JOBS YOU CAN’T MISS!

💼 Analytics Engineer @ Anduril

📍Irvine, United States | $146,000–$194,000 (US base)

Anduril builds AI-powered defense systems, Lattice OS fuses thousands of data streams into real-time 3D command & control to counter UAS and other threats.

They’re hiring an analytics engineer to design robust data systems and ship mission-critical insights for the Air Defense team.

You’ll:

• Architect low-latency ingestion, transformations, and reusable data models powering operational workflows and decision-making.

• Partner with engineering & field ops to quantify system performance (incl. classified/isolated envs), build dashboards, and drive root-cause analyses.

• Deliver secure, scalable analytics (Python/SQL, orchestration, cloud/IaC) with strong documentation, enablement, and occasional on-site deployment.

Ideal for: 6+ yrs analytics/data eng; Python/SQL; Airflow/Dagster/Flyte; cloud + DevOps; US Person able to obtain DoD Secret.

🔗 Apply Now →

💼 AI PM-in-Residence @ Lovable

📍United States (Remote) | Competitive

Lovable helps anyone from solo builders to Fortune 100 teams turn ideas into production software, fast.

They’re hiring an AI PM-in-Residence to advise execs and ship AI-native proofs that transform how teams ideate, prototype, and launch.

You’ll:

• Run executive discovery/workshops to identify high-leverage AI use cases and operating-model shifts.

• Design and deliver AI-native prototypes and internal tools, bridging strategy and engineering.

• Establish iteration loops and impact metrics (e.g., time-to-prototype, decision velocity) to scale wins across orgs.

Ideal for: 7–10+ yrs PM/tech consulting pros with executive presence and technical fluency who thrive in ambiguity.

🔗 Apply Now →

💼 Head of Data @ n8n

📍Berlin, Germany (Remote) | 💰 Competitive

n8n helps teams orchestrate AI-powered workflows, blending code + no-code so companies automate faster, smarter, and at scale.

They’re hiring their first Head of Data to define strategy, stack, and culture and turn data into a core growth and decision engine.

You’ll:

• Build a modern data platform (e.g., BigQuery, dbt, BI) with trusted models, metrics, and dashboards for Product, Revenue, and Ops.

• Lead and grow a lean data team; embed data into planning and execution across Product, Eng, Sales, Marketing, Finance, and Leadership.

• Own governance, quality, privacy/compliance, and enable self-serve analytics, expanding into advanced analytics/AI use cases.

Ideal for: 8+ yrs data leaders with modern stack chops (BigQuery/dbt/Looker/Metabase), PLG/SaaS experience, and a player-coach mindset who can translate insights into action.

🔗 Apply Now →

TRENDS
What's trending in AI

OCRmyPDF

• Key Player: Open‑source CLI utility that adds an OCR text layer to scanned PDFs, supports multi‑language recognition via Tesseract, and defaults to compliant PDF/A output for archiving.

• Market Value: Interest signals show 5.4K monthly searches with +6000% growth over the past two years on category trend lists.

• Adoption: “Battle‑tested on millions of PDFs,” scales to thousands of pages, and ships in container images for straightforward deployment across environments.

• Recent Developments: Actively maintained with recent PyPI releases (v16.11.1 in October 2025), featuring rotate, deskew, image optimization, multi‑core processing, and validated PDF/A output.

Growth: Search demand sits at 5.4K/month with +6000% growth, signaling breakout awareness and expanding document‑workflow use cases rather than a niche spike. Placement among fast‑rising technology topics indicates sustained multi‑month momentum alongside other automation and AI infrastructure tools.

Why It Matters: Teams can unlock legacy scans for search, compliance, and internal knowledge retrieval while keeping data on‑prem and private, since the tool runs locally and “keeps your private data private”. Out‑of‑the‑box PDF/A, language packs, and a robust CLI reduce integration friction for batch pipelines and regulated archives across global languages.

The Big Picture: Organizations are accelerating batch OCR of large PDF corpora to power downstream text mining, topic modeling, and analytics, making high‑quality OCR a foundational step for modern AI and data workflows. Open‑source, local‑first automation that preserves privacy and scales via the command line is increasingly favored for control, cost efficiency, and reliability in production environments.

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