Latest
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AI-native development: How to actually get the most out of your agents
This talk covers spec-driven development as a way to give agents better constraints, large language model (LLM) gateway and routing strategies for managing which model handles which task, test-driven development adapted for an agent-first workflow, and verification practices built for the volume and pace of AI-generated code.
Editor’s picks
Cooking up a culture of continuous learning
Continuous learning is an important part of building a collaborative culture.
Build a productive code review culture
Code reviews can be tense and stressful if done incorrectly. Avoid bikeshedding and set good cultural standards with these nine simple steps.
Trust is the ultimate driver of engineering excellence
How can you improve the level of trust in your teams to bolster performance and encourage an inclusive culture.
New York • September 8 & 9, 2027
Loved LDX3 New York? Pre-sale tickets for 2027 are now available.
Essential reading
How to build an intentional culture
Don’t leave your culture up to chance. Curate your principles and values intentionally to build high-performing, harmonious teams.
On our Culture playlist
Culture, Clarity, Velocity
This session explores how leaders can examine proposed changes and prepare their teams to move from a culture that impedes progress to one that enables strategic change.
Happy teams don’t leave
To retain talent, engineering leaders need to establish an engaging culture within their teams
From hurdles to highways: Crafting a collaborative experimentation ecosystem at GetYourGuide
Discover how GetYourGuide transformed its experimentation platform, navigating challenges to build a streamlined, collaborative, and innovative ecosystem for efficient testing and creativity.
How to build a culture of accountability in your teams
In this panel, we’ll discuss what a culture of accountability actually looks like in practice, and the role of the engineering leader in encouraging a culture of accountability, not blame, in busy developer teams.
Fostering a culture of experimentation in your engineering teams
How can engineering leaders help their reports find joy in their work?
The festival for modern engineering leadership
New York • September 15 & 16, 2026
More about Culture
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Killing a project is every engineering leader’s hardest call
Sometimes you must kill a project before it kills momentum.
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How I got a performance-driven team to care about security
A culture of security testing requires persistence, empathy, and a shared vision of reliability.
Top Culture videos
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How to kill the code review
This talk explores why traditional code review is struggling to keep up with AI-driven development. It introduces a five-layer trust model designed to help engineering teams validate AI-generated code, reduce reliance on manual review, and ship faster without sacrificing quality or control.
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Evaluating AI developer tools without the drama
This talk explores how to turn a divided technical evaluation into a decision everyone can trust. Through a real-world AI code review tool rollout, you’ll learn a practical framework for setting shared criteria, rebuilding developer confidence, and making technical decisions with genuine stakeholder buy-in.
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The accountability gap: Engineering governance for autonomous AI
This session walks through an engineering framework for accountable autonomy: a three-tier trust model that categorizes decisions by blast radius (impact and reversibility), an autonomy budget that meters agent trust with SLOs and revokes it automatically when behavior degrades, and circuit breakers that freeze an agent before a bad pattern becomes an incident.
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One shot at scale: Surviving the Super Bowl signup surge
This talk goes behind the scenes of how Fetch prepared for a massive Super Bowl traffic spike, scaling from around 1 signup per second to a target of 150,000. It explores the engineering decisions, architectural trade-offs, stress testing, and launch-day processes that helped the team manage risk when there was only one chance to get it right.
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The real impact of AI on software engineering
This session presents the key findings from LeadDev’s AI Impact Report 2026 – and the numbers tell a more complicated story than the productivity anecdotes suggest.
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The data canary: How Netflix validates catalog metadata
This talk tells the story of how we built the Data Canary: an automated system that validates data transformations using real production traffic, detects regressions in 2.5–4 minutes, and blocks bad data from publishing, all within a 10-minute window.
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Obsessing over AI is optional
This talk is for overwhelmed engineering leaders and senior ICs who feel quietly guilty about not experimenting with every AI trend.
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Startup made, enterprise grade: Earning trust, scoping tight, and shipping quality with a small team
Small teams are increasingly expected to build for enterprise-scale customers, and AI is changing how they get there. This talk explores how startups can ship enterprise-ready features with lean teams, what’s changed along the way, and how they’re adapting for what comes next.