We are inviting proposals for the 20th edition of the Great International Developer Summit (GIDS) 2027.
GIDS is one of Asia’s longest-running and most respected conferences for software engineers, architects, tech leads, platform teams, data practitioners, and engineering leaders.
📍 Bengaluru, India
📅 27th–30th April 2027
Build Systems That Endure.
Software is easier to build than ever. It is harder to make endure.
At its core, software engineering is the discipline of managing complexity. Every generation of technology introduces new abstractions, new capabilities, and new sources of complexity. GIDS exists to help engineers build systems that remain understandable, reliable, adaptable, and maintainable as that complexity grows.
AI has changed how software is created, tested, debugged, and shipped. Teams are moving faster, systems are becoming more interconnected, and engineering decisions now carry longer-term consequences.
Speed alone does not create durable systems.
GIDS 2027 focuses on the engineering craft required to build systems that remain reliable, understandable, adaptable, and trustworthy over time.
This is not a general technology event.
GIDS is where engineers discuss how real systems are designed, built, operated, maintained, improved, and evolved under real-world constraints.
🔍 What We Are Looking For
We are interested in sessions grounded in real engineering work across software architecture, backend, frontend, platform, data, AI-augmented engineering, security, reliability, and technical leadership.
- systems designed and operated under real-world constraints
- architecture decisions shaped by scale, complexity, reliability, and long-term maintainability
- backend services, APIs, runtimes, and distributed systems
- frontend systems, experience engineering, performance, and application architecture
- platform engineering, DevOps, CI/CD, and internal developer platforms
- observability, reliability, security, and operational debugging
- data systems, pipelines, integration patterns, and intelligent systems from a software engineering lens
- AI-assisted software engineering, including developer productivity, engineering effectiveness, quality assurance, testing, review practices, and the long-term maintainability of AI-assisted codebases
- developer tooling and productivity systems
- engineering leadership, system ownership, technical decision-making, and organisation-scale trade-offs
- failure modes, redesigns, constraints, and lessons learned from production systems
We are especially interested in talks that discuss trade-offs under real-world constraints: reliability, performance, cost, security, maintainability, scale, team structure, delivery pressure, and long-term evolution.
🎯 Your talk should leave the audience with practical engineering insight they can apply immediately.
What Strong GIDS Talks Usually Include
We value talks that clearly explain:
- what you built
- what problem you were solving
- what constraints shaped your approach
- what trade-offs mattered most
- what worked and what did not
- what changed in practice
- what you would do differently
⚠️ If your talk can be delivered without real engineering experience behind it, it is unlikely to be a fit.
⚠️ Assume the audience already understands the basics. Skip broad introductions and get into the engineering details.
🧭 Focus Areas
🏗️ Architecture & Distributed Systems
How do we design systems that remain clear, reliable, and adaptable as they grow?
This area focuses on architecture decisions, system boundaries, distributed behaviour, and long-term system evolution.
Examples:
- monoliths, modular monoliths, microservices, and self-contained systems
- system boundaries, contracts, coupling, and decomposition
- distributed systems design and operational trade-offs
- consistency, availability, resilience, and failure handling
- architecture evolution in long-lived systems
- patterns for managing technical debt and complexity
- designing systems that teams can understand and evolve safely
⚙️ Platform Engineering & DevOps
How do engineering teams build platforms that make delivery safer, faster, and more consistent?
This area focuses on the systems, workflows, and practices that support modern software delivery.
Examples:
- platform engineering and internal developer platforms
- CI/CD systems, deployment pipelines, and release engineering
- infrastructure as code and environment automation
- developer experience and engineering productivity
- cloud-native operations and platform reliability
- deployment safety, rollback strategies, and progressive delivery
- cost, governance, and operational control in platform systems
🖥️ Backend Engineering & Runtimes
How do backend systems behave under real load, failure, and change?
This area focuses on backend services, APIs, runtimes, and the engineering choices that shape system behaviour in production.
Examples:
- API design, contracts, versioning, and backward compatibility
- service communication patterns and integration design
- runtime performance, concurrency, and resource management
- state management, transactions, and consistency
- resilience, retries, timeouts, and graceful degradation
- backend architecture for scale and maintainability
- lessons from operating backend systems in production
🎨 Front-End & Experience Engineering
How do we build user-facing systems that remain fast, reliable, accessible, and maintainable?
This area focuses on frontend architecture, performance, design systems, and the complexity of real-world user experiences.
Examples:
- frontend architecture and large-scale application structure
- state management, performance, and rendering strategies
- design systems and reusable component models
- accessibility, usability, and resilient user experiences
- frontend observability, debugging, and production diagnostics
- frontend-backend integration and API-driven product experiences
- AI-assisted and AI-augmented user experiences from an engineering lens
📊 Data & Intelligent Systems
How do data systems support products, platforms, and engineering decisions at scale?
This area focuses on data platforms, integration, processing, and intelligent systems from a software engineering perspective.
Examples:
- data pipelines, data platforms, and integration architectures
- real-time and batch processing systems
- storage models, consistency, and data reliability
- data contracts, quality, lineage, and governance
- application-data integration patterns
- intelligent systems built on reliable data foundations
- operating data systems under scale and change
🤖 AI-Assisted Software Engineering
How do intelligent tools change the way software is designed, built, tested, reviewed, maintained, and evolved?
This area focuses on AI as part of the software engineering process rather than AI as a standalone technology domain. We are interested in how engineering teams use intelligent tools and workflows to improve software quality, developer effectiveness, maintainability, and long-term system outcomes while keeping engineering judgment at the centre.
Examples:
- AI-assisted software development workflows
- Developer productivity and engineering effectiveness systems
- Intelligent coding, testing, debugging, review, and documentation workflows
- Human-AI collaboration patterns for software teams
- AI-assisted architecture, design, and implementation practices
- AI-native IDEs, engineering assistants, and development environments
- Quality assurance, verification, and review practices for AI-generated code
- Guardrails, governance, and risk management for AI-assisted development
- Measuring the impact of AI on engineering quality, maintainability, delivery, and developer experience
- Lessons learned from adopting intelligent tools across engineering organisations
🔍 Reliability, Observability & Security
How do systems remain trustworthy under failure, pressure, and attack?
This area focuses on the practices and systems that help teams understand, secure, and operate software in production.
Examples:
- logging, metrics, tracing, and production diagnostics
- incident response, debugging, and post-incident learning
- reliability engineering and resilience practices
- performance engineering and capacity planning
- application security and infrastructure security
- threat modelling, secure design, and risk reduction
- operational practices that build trust over time
🧠 Engineering Leadership & Systems Thinking
How do engineering decisions scale across teams, systems, and organisations?
This area focuses on technical leadership, system ownership, engineering culture, and the organisational realities behind long-lived systems.
Examples:
- technical decision-making under uncertainty
- system ownership and long-term maintainability
- architecture governance without slowing teams down
- scaling engineering practices across teams
- engineering culture, reviews, rituals, and feedback loops
- leading technical change and platform adoption
- balancing delivery pressure with engineering quality
🔎 Cross-Cutting Theme
🧱 Building Systems That Endure
What does it take to build software that remains useful, reliable, and understandable over time?
This is a core theme that spans all focus areas. We are interested in talks that address long-term engineering quality, not just short-term delivery.
Examples:
- maintainability and system evolution
- clarity in architecture and codebases
- responsible use of AI in software engineering
- operational trust and reliability over time
- technical debt, refactoring, and redesign decisions
- systems that can adapt safely as teams and products change
What Is Unlikely To Be Selected
- introductory or beginner-level sessions without deeper engineering insight
- generic technology trend summaries
- product demonstrations without engineering depth
- framework walkthroughs without real-world trade-offs
- marketing or promotional presentations
- high-level leadership talks without technical substance
- AI hype talks without practical software engineering relevance
- sessions that avoid discussing constraints, trade-offs, or real-world behaviour
⚙️ Submission Guidelines
🆕 Original content only
Proposals should be based on work you have directly done or materially contributed to.
🧠 Depth over breadth
We value focused engineering insight over broad conceptual coverage.
🚫 No marketing content
Vendor-neutral talks are strongly preferred. Product-focused talks must contain substantial engineering depth and practical learning.
🧪 Engineering detail matters
Architecture diagrams, implementation details, metrics, debugging workflows, design decisions, and trade-offs are highly encouraged.
💥 Failure and learning matter
We strongly value talks that discuss constraints, operational surprises, redesigns, mistakes, and lessons learned.
🎯 Session Formats
The GIDS 2027 Call for Speakers is accepting the following formats. Using this form, you can submit up to 5 proposals.
- Long Talk: 60-minute Presentation
- Short Talk: 30-minute Presentation
For international speakers:
We recommend submitting 60-minute session proposals and multiple talks. Each proposal is evaluated independently, and submitting more high-quality proposals can improve your chances of selection.
🎤 Speaker Support
Selected International Speakers may receive:
- Travel support of up to US$ 1,500
- 2 nights of accommodation
- Full conference access
Note: International speakers are encouraged to submit multiple 60-minute session proposals.
Selected Inter-state and Local Speakers receive:
Additional Notes
- Speaker support is discretionary and not guaranteed upon acceptance.
- Acceptance decisions are based on the strength and relevance of the submission.
- All reimbursements will be processed post-event upon submission of valid bills and invoices.
- Reimbursements will be limited to the approved support caps stated above.
- If your participation is supported by your employer or organisation, please indicate this in your submission. This helps us allocate limited support to independent practitioners.
- Only the primary speaker is eligible for speaker support unless explicitly approved otherwise.
- A maximum of one co-speaker is allowed per session. Approved co-speakers must purchase a valid conference pass.
- The organisers are not responsible for cancellation, rescheduling, or fare differences arising from changes to travel or accommodation bookings.
⏳ Deadline to Submit: September 30, 2026
If you are building software systems that must hold up under real-world conditions, we would love to hear from you.
Submit below at the earliest and help shape the 20th edition of GIDS.