The AI Readiness gap: Where infrastructure teams are getting AI wrong
Event PAST

The AI Readiness gap: Where infrastructure teams are getting AI wrong

16 July Online

About this event

AI has made developers faster, but it's also made security vulnerabilities appear faster, governance harder, and production incidents more frequent. The 2026 State of Infrastructure Automation report surveys 406 infrastructure teams to find out where AI readiness and platform maturity actually stand.

This session covers the data, the gap between what teams say and what their workflows reveal, and what separates the organizations pulling ahead from those falling behind.

Join Dimitri and learn:
1. How your peers are actually managing AI and governance in production today, what the data says about confidence vs. reality, and where most teams have a blind spot they don't yet know about.
2. A behavioral framework for assessing your own AI readiness across five dimensions: AI integration depth, governance maturity, automation coverage, risk exposure, and platform readiness.
3. What Pioneer organizations did differently before AI arrived, why that discipline is now the single biggest predictor of production stability, and the specific steps still available to close the gap before agentic AI removes the margin for error.

Speaker: Dimitri Vlachos
CMO @ Spacelift
Dimitri is a proven marketing leader with over 20 years of experience in technology. Prior to being the CMO of Spacelift, Dimitri served as CMO at venture-backed technology companies including Brinqa and Devo. He has also held leadership roles in marketing and product at Riverbed Technology, Mazu Networks, and Cisco Systems.

Speaker: Faisal Afzal
Principal, Platform Engineering @ AHEAD
Faisal Afzal is a CNCF and Platform Engineering Ambassador and Principal Technical Consultant Lead at AHEAD specializing in cloud and platform engineering. He organizes Cloud Native LA, co-organizes Cloud Native Days Los Angeles, and volunteers at SCaLE, helping socialize and make cloud-native technologies accessible to the broader community.

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 DevFound.ai. 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.