2027
APIs, MCPs & Tooling
APIs remain the connective tissue of software. However, the rise of the Model Context Protocol (MCP) is adding a powerful new dimension. This track covers API design, versioning, developer experience, and how MCP is enabling AI agents to interact with external tools and services.
Cloud-Native Development
Build, deploy, and iterate faster with cloud-native architectures. Sessions dive into microservices, serverless, service mesh, GitOps, and the developer workflows and platform engineering practices that empower teams to ship with confidence on modern cloud infrastructure.
Data Management & Engineering
Explore the pipelines, platforms, and practices behind modern data infrastructure. Sessions cover streaming data, lakehouse architectures, data quality, governance, and how data engineers are adapting their stacks to support AI and ML workloads at scale.
Dev Security & Operations (DevSecOps)
Security is everyone’s job now. This track equips developers and ops engineers with practical techniques for shifting security left, covering SAST/DAST, secrets management, supply chain security, compliance automation, and building secure-by-default development cultures.
Enterprise Development
Enterprise Development Enterprise Development Tackle the unique challenges of software engineering at enterprise scale — from modernizing legacy codebases and navigating complex stakeholder landscapes to API governance, developer experience programs, and the internal platform strategies that make large engineering orgs move faster.
Mobile Development
From native iOS and Android to cross-platform frameworks and progressive web apps, this track covers the full spectrum of modern mobile engineering. Sessions focus on performance, offline-first architecture, mobile AI integration, and the UX patterns that define exceptional mobile experiences.
2027
AI DevWorld Tracks
Agentic AI
Learn about the Agentic AI Ecosystem with autonomous AI agents, multi-agent orchestration, and context engineering. Discover how developers are building agents that plan, reason, and take action, plus the harnesses and frameworks that keep them in control.
AI & ML Engineering
Learn about the engineering disciplines behind production-ready machine learning systems. Topics include model architecture, fine-tuning strategies, evaluation frameworks, and the software engineering practices that separate prototype AI from scalable, production-ready ML.
AI-Augmented Software Development
Explore how AI copilots, code generation, and intelligent tooling are transforming the day-to-day workflows of software engineers. From pair programming with LLMs to AI-assisted testing and debugging, learn how to build faster and smarter.
AI Data Storage, Management & Training
Discover the data technologies and best practices for implementing AI solutions. This track covers RAG architectures, vector databases, synthetic data generation, and the full training and fine-tuning lifecycle.
AI Executive Summit
An exclusive forum for senior technology leaders to engage with the strategic, organizational, and governance implications of AI adoption. Sessions provide forums for candid discussions, peer roundtables, and conversations on how to lead AI transformation at scale.
AI in the Enterprise
Tackle the real-world challenges of deploying AI into production across large organizations, from change management and compliance to integration with legacy systems and measuring ROI. Sessions feature case studies, implementation playbooks, and lessons from teams who’ve done it.
AI Ops, Infrastructure & MCP
Explore the platforms, pipelines, and protocols powering modern AI at scale, including MLOps practices, observability tooling, and the emerging Model Context Protocol (MCP) ecosystem. Gain insight into how top teams build the infrastructure that makes AI reliable and secure in production.
AI Security
Examine the security solutions of AI, including prompt injection, model manipulation, jailbreaking, and supply chain vulnerabilities. Hands-on sessions cover red teaming methodologies, threat modeling for AI systems, and building defenses that hold up under attack.
2027
ProductWorld Tracks
Product Lifecycle: AI Augmentation & Automation
From discovery to launch to iteration, AI is accelerating every phase of the product lifecycle. Explore how teams are using AI for user research synthesis, auto-generated specs, A/B test analysis, and continuous feedback loops that compress time-to-insight.
Product Methodology: Agile, Rapid Prototyping, SCRUM & Beyond
Revisit the methodologies that power modern product development and explore how AI is challenging and extending them. Sessions cover sprint planning with AI assistance, prototype-driven development, and what it means to move even faster without sacrificing quality.
Product Strategy: AI in the Product Roadmap
Learn how leading product teams are identifying AI opportunities, prioritizing AI features, and communicating AI strategy to stakeholders. Sessions cover opportunity sizing, competitive differentiation, and frameworks for integrating smart AI bets into your roadmap.
Product Teams: Leaders, Engineers, Designers & Workflows
Great products emerge from aligned, cross-functional teams. This track explores how PMs, engineers, and designers collaborate in the age of AI-assisted tools and agentic workflows, and how to build the culture and processes that make diverse teams ship great work.
2027
OpsWorld Tracks
AI-Enabled DevOps (AIOps)
Discover how AI applies to the operations function itself. Explore everything from AIOps platforms that predict failures before they happen to intelligent alerting, automated remediation, and ML-driven capacity planning. Sessions blend real-world case studies with hands-on tooling deep dives.
Cloud & AI Computing
Examine the converging worlds of cloud-native architecture and AI compute, including GPU clusters, inference optimization, multi-cloud strategies, and specialized hardware accelerators reshaping what’s possible in modern data centers and hyperscaler environments.
Containers, Kubernetes & AI Architectures
Master the art of distributed systems with sessions spanning container orchestration, multi-cluster Kubernetes strategies, edge computing architectures, and the emerging patterns for workloads that move fluidly between edge devices and cloud environments.
Deploying & Managing AI Workloads
Running AI in production is a discipline of its own. This track covers GPU scheduling, model-serving infrastructure, cost optimization, model-drift monitoring, and the operational patterns teams use to keep AI workloads performant, observable, and cost-effective.
2027
DevExec World Tracks
CTO & Tech Leadership/Strategy
A high-level track designed for CTOs and senior tech leaders to tackle the hard questions: platform bets, build vs. buy decisions, engineering culture at scale, and how to communicate technology strategy to boards and stakeholders.
Emerging Trends & Technology
Stay ahead of the curve with forward-looking sessions on the technologies and paradigms poised to reshape software development in the next 1–3 years. From quantum computing to neuromorphic chips, get an executive-level briefing on what matters.
Technical Teams in the Age of AI
How do you build, structure, and scale engineering teams when AI is reshaping every role? Sessions explore new team topologies, evolving hiring criteria, and how great engineering managers are adapting workflows, culture, and expectations for an AI-augmented workforce.