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


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.


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.

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

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

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

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

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

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

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

Conference editors

  • Jagadish K. (Tryft)
  • Ramkrishna Reddy Y (Red Hat)
  • Ranganadh Thata (Mico)
  • Yash Gandhi (OrcaSheets)

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

Hosted by

Jumpstart better data engineering and AI futures