Weaviate Podcast
Weaviate Podcast

Founding Weaviate with Bob van Luijt and Etienne Dilocker - Weaviate Podcast #140!

27 July 2026 55:08 Weaviate

Listen to episode

About this episode

Weaviate co-founders Bob van Luijt and Etienne Dilocker return to the Weaviate Podcast to celebrate seven years of building the company, answering questions submitted by the community. The conversation opens with what excites them most in AI right now: Etienne on agentic coding and the "Moore's law" of how long models can sustain autonomous loops, and Bob on world models, new architectures that could slash training energy costs, open source frontier models, and inference on new chips.From there, the discussion dives into taste and the "AI slopification" problem, why AI-generated emails, websites, and decks all look the same, how three job candidates submitted nearly identical AI-built presentations in one week, and why Weaviate runs a dedicated "slop pass" skill over every pull request to strip out phrases like "the smoking gun" and "load-bearing invariant." The human touch, they argue, is now the easiest way to stand out.The Co-Founders then retell their origin story: meeting at a European enterprise company, rewriting a NodeJS prototype in Go, betting on NLP before anyone called it AI, adopting HNSW when it was still a niche paper, and raising a $1.2M seed round from Zeta during COVID. When ChatGPT and the RAG paper hit, Weaviate had a fully working product ready for the wave.Looking forward, Bob breaks down the commoditization playbook that hits every new database category, the same skepticism MongoDB faced, and shares that the number one reason new customers cite for choosing Weaviate is that an LLM recommended it. Etienne makes the case that vector databases are evolving into context engines: context rot is real, stuffing everything into a long context window is inefficient, and retrieval, hybrid search, and structured data all serve one goal, the best possible context. The conversation lands on memory for AI agents, where the hard problem isn't what's worth remembering, but what's worth recalling.

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Weaviate Podcast. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.