We are looking for sessions that help engineers build better with and on agentic AI — from coding assistants in production to autonomous agents running real workloads. Technical depth, engaging live demos, real world applications and honest lessons-learned are encouraged. Marketing pitches or "shallow overviews" will be rejected.

Tracks

Track 1 — Let it build: Using AI in the engineering loop. Copilot, Claude Code, Cursor, agentic IDEs, code review bots, measuring impact, team rollouts, developer experience.

Track 2 — Build it: Building products and platforms on top of LLMs and agents. Multi-agent systems, orchestration, evals, MCP, RAG, tool use, safety, cost, production architectures.

Track 3 — Hands-On Labs: Guided, laptop-open sessions where attendees build something real in the room.

Further tracks (not available for the call for speakers):
Spotlight Track: Reserved for sponsors, vendors, and partners.
Panel Discussion: More details to come.

Session formats

Talk : 25 minutes plus Q&A.

Lightning talk: 5-7 minutes, no Q&A.

Hands-on lab: 90 minutes, participants bring a laptop and leave with something running. (Usage of Letsboot AI Labmachine possible - zero Setup Szenarios)

Audience

(Software|System|Platform|DevSecOps|...) engineers, tech leads, platform and infrastructure engineers, ML/AI engineers, CTOs, and architects — people who ship. Assume a technical audience with a broad spectrum of topic related know how: From Senior Software Engineers who never used a Coding Agent in Production to Engineers who built their own Harness running multiple agents.

Levels of expertise

From Senior Software Engineers who never used a Coding Agent in Production before to Engineers who built their own Harness running multiple agents.

Language

English preferred.

Speaker benefits

Free event ticket for the speaker

Invitation to the Speakers adventure in Zurich during the afternoon on the day before the conference

Invitation to the Speaker & Sponsor Dinner on the evening before the event

Travel and accommodation coverage is on a need basis (there is a budget for that and we try to make the best of it, but we will not be able to compensate travel and accommodation for all speakers)

An amazing audience at a great location in the heart of Zurich

Code of conduct

All speakers and attendees agree to our code of conduct: https://www.agenticdays.com/code-of-conduct.html

Questions

info@agenticdays.com

Topics:

A selection of topics to group the proposals and optmise our selection process:

• Agent Frameworks — Building agents with LangChain, LangGraph, AutoGen, CrewAI, Spring AI, Smolagents, Pydantic AI
• AI Coding Tool Extensions — Claude Code skills, slash commands, hooks, sub-agents, Copilot extensions, Cursor rules, custom MCP servers for coding agents
• AI Coding Tools — Claude Code, GitHub Copilot, Cursor, Devin, Aider, Windsurf: demos, comparisons, hosting locally
• AI Community, Open Source & Education — Maintainer lessons, ecosystem health, learning paths, teaching AI
• AI Ethics & Responsibility — Alignment, bias, accountability, societal impact
• AI Evals & Testing — Benchmarks, eval harnesses, regression testing for agents and LLM apps
• AI for Legacy & Refactoring — Modernization, migration, working with old codebases using AI
• AI in DevOps & Platform Engineering — AI for CI/CD, incident response, infrastructure, SRE
• AI Observability & Production — Tracing, debugging, monitoring agents in production, reliability ops
• AI Product UX & Human-Agent Collaboration — Designing agentic products, oversight flows, approval UX, trust
• AI Security — Prompt injection, supply-chain attacks, CVEs in AI tools, red-teaming
• AI Strategy & Value Realization — Business cases, ROI, "agentic debt", leadership perspective
• AI-Assisted Coding Practice — Day-to-day workflow with AI, productivity, vibe coding, "how we ship with AI" stories
• Computer-Using Agents & Automation — Browser agents, CUAs, RPA-style desktop automation
• Enterprise AI Adoption & Governance — Rollouts, compliance, change management, organizational enablement
•  Industry & Vertical Use Cases — Domain stories: finance, health, legal, sales, support, education, payments/commerce
• Lessons Learned & Anti-Patterns — Retrospectives, postmortems, "AI fails of the year", what didn't work, war stories
• Local AI, Inference & Open Models — Ollama, vLLM, llama.cpp, browser AI, open weights, fine-tuning, edge inference
• MCP & Agent Protocols — MCP servers/clients, A2A, interoperability, standards
• Multi-Agent Architectures — Patterns for multiple agents coordinating: orchestration, handoffs, swarms
• RAG & Knowledge Retrieval — Vector stores, knowledge graphs, retrieval strategies, context management
• Software Architecture with AI — Design patterns, clean architecture, system design when AI generates code
• Spec-Driven & Agentic SDLC — Requirements → spec → code workflows, planning agents, backlog-driven AI dev
• Voice & Multimodal Agents — Voice AI, vision agents, multimodal models, real-time speech
    Other - We for sure forgot something 😇.