Speak at The Fifth Elephant 2026 Annual Conference

Speak at The Fifth Elephant 2026 Annual Conference
2026-07-17 03:30 - 2026-07-18 12:30 UTC | NIMHANS Convention Centre, Bangalore - https://hasgeek.com/fifthelephant/fifthelephant-2026-call-for-submissions/
# This page is only for submissions for The Fifth Elephant 2026 annual conference
**Dates**
- Conference on Friday, 17 July, at the NIMHANS Convention Centre
- Workshops on Saturday 18 July in Marathalli, Koramangala & Whitefield

**To attend the conference, get an annual membership - https://hasgeek.com/fifthelephant#memberships**

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# How to submit
1. **Submit your abstract**. Your abstract should clearly describe:
* the problem or topic being addressed,
* why it is relevant,
* who the session is intended for, and
* the key takeaways attendees can expect.

2. **Add a link to draft slides within 3–5 days** - after submitting your abstract, add a link to the draft version of your slides within 3–5 days. Draft slides help editors better evaluate the structure, depth, and delivery of the session.
*Submissions without draft slides may not be reviewed or may experience delays in receiving feedback.*

3. **Add a 2-minute elevator pitch video** - introducing your session and demonstrating your speaking style. This helps the editorial team assess presentation clarity and audience engagement.

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# Review timelines and submission deadlines
* Feedback via comments may be shared early for submissions that include slide links.
* Selected speakers will be contacted starting 17 June onwards.
* The final submission deadline is 25 June 2026.
* Not every submission may fit the annual conference schedule in July. Some proposals may be considered for future community sessions, including weekly reviews and monthly meet-ups.

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# Conference tracks
## Track 1: Data Engineering & Infrastructure
**Track editors are looking for submissions that reflect what's actually working (and what isn't) in production data systems, especially as AI workloads reshape infrastructure assumptions.**

### AI-native data systems
- Data engineering for foundational model training and fine-tuning
- Data pipelines for inference and post-training steps
- Data stores and retrieval patterns for GenAI and LLM-based applications
- Memory management and agent-to-agent communication
- Evals, guardrails and observability implemented in production systems

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## Foundations & storage
- Lakehouse and lakebase architectures - what's working in production
- Table format evolution: Iceberg, DuckLake, and how metadata management is changing
- Query engines in the wild - including newer entrants like Apache DataFusion
- In-memory and local databases: when and why they make sense
- Realtime CDC and streaming data patterns

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## Governance, compliance & data quality
- Practical approaches to PII detection, masking and management at scale
- Metadata management strategies that actually hold up in large organisations
- Governance frameworks adapted for AI and LLM pipelines
- Data quality practices in the context of model inputs and outputs

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## Ops, reliability & costs
- Observability practices for data and AI infrastructure
- Agent incident response and SRE patterns for agentic systems
- Cost optimisation strategies for AI infrastructure — compute, storage, egress
- Hardware and compute considerations; sub-architecture patterns for inference and training workloads

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## Orchestration & pipelines
- Production use cases with tools like Airbyte, Fivetran, Dagster, Prefect or Temporal
- Patterns for integrating orchestration with AI and agent workflows
- Migration stories - from legacy pipelines to modern orchestration
- Operational lessons from running pipelines at scale

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## Track 2 - Building and implementing AI tools & agents in production
### Topics for builders
* Building production-ready agent frameworks and tools
* Implementing MCP (Model Context Protocol) servers and clients
* Tool development for specific domains (customer support, operations, data analysis)
* Multi-agent orchestration patterns
* Reliability and monitoring for agentic systems
* Scaling agent-based systems
* Creating reusable agent components and libraries
* Designing tool interfaces for LLM consumption

### Topics for practitioners
* Real-world case studies of agents in production
* ROI and business impact of agentic systems
* Integration patterns for enterprise environments
* Prompt engineering and agent optimization strategies
* Migrating from traditional automation to AI agents
* Operational challenges and solutions
* Agent evaluation and quality assurance
* Team workflows with AI agents

### Cross-cutting topics
* Security and safety in agentic systems
* Human-in-the-loop patterns
* Cost optimization strategies
* Tool choice and framework selection
* Debugging and observability
* Testing strategies for non-deterministic systems

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# Workshop topics
Topics include, but are not limited to:
* MCP server creation with different protocol variations
* Agent frameworks like LangChain and LlamaIndex - which are widely used
* Implementing specific agent patterns (e.g., ReAct, chain-of-thought)
* Tool development tutorials for agentic systems
* Integration exercises with real APIs and services
* Hands-on prompt engineering and optimization techniques

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# Conference editors
* Jagadish K. (Tryft)
* Ramkrishna Reddy Y (Red Hat)
* Ranganadh Thata (Mico)
* Sitaram Shelke (NVIDIA)
* Yash Gandhi (OrcaSheets)

# Consulting editor
* Ravi Balgi (Datanimbus)

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## Got a question? Need help?
📞 Call or text The Fifth Elephant at (91) 7676332020
📧 Email <info@hasgeek.com>
💰 For sponsorship inquiries, email <sales@hasgeek.com>
