Ep70: Devnexus Conference Recap + No-LLM Agentic Workflow episode artwork

EPISODE · Mar 13, 2026 · 21 MIN

Ep70: Devnexus Conference Recap + No-LLM Agentic Workflow

from Breaktime Tech Talks · host jmhreif

Hear my recent experience at the Devnexus conference in Atlanta, where I delivered two sessions and connected with so many amazing people! Devnexus session 1: "Agents, Tools, and MCP, Oh My! Next Level AI Concepts for Developers" — a redesigned solo talk breaking down AI building blocks (agents, tool calls, context management, memory, and MCP) so developers can mix and match components for their own stack. Key takeaway: AI systems are much more than just the LLM — developers play a critical role in designing the surrounding architecture. Devnexus session 2: "Supercharging Applications with Java, Graphs, and a Touch of AI" (code repo 1, code repo 2) — a joint session with Erin Schnabel building an LLM-powered role-playing game using Langchain4j, Quarkus, and Neo4j. Multiple approaches: plain LLM chat, prompt engineering, and RAG with Neo4j as the vector/graph store, chunking documents while preserving structure via graph relationships. Our "Three Cs" challenge: Continuity (maintaining storyline), Context (growing context window), and Creativity (keeping the LLM on track without going off the rails). Splitting responsibilities between the LLM and a deterministic engine significantly improved results — a pattern developers should consider for complex AI apps. App redesign with an agentic architecture: dice roll, narration, suggestion, checkpoint, and recap agents — with the last three running concurrently for better performance. Markdown file (in one app) for agentic memory, enabling easy edits, rollbacks, and incremental indexing during live gameplay. Content spotlight: "No Keys, No LLM — Building a Wikidata Definition API with Embabel" — an article showcasing an agentic Java application that uses zero LLM. Embabel (a Java agentic framework) handles planning and execution with structured inputs/outputs, no external or local model required. Could the no-LLM agent pattern see broader adoption, or is it a niche experiment? New episodes will now use platform-agnostic Podfollow links. New blog post on jmhreif.com about Cypher AI procedures.

Episode metadata supplied by the publisher feed · Published Mar 13, 2026

Hear my recent experience at the Devnexus conference in Atlanta, where I delivered two sessions and connected with so many amazing people! Devnexus session 1: "Agents, Tools, and MCP, Oh My! Next Level AI Concepts for Developers" — a redesigned solo talk breaking down AI building blocks (agents, tool calls, context management, memory, and MCP) so developers can mix and match components for their own stack. Key takeaway: AI systems are much more than just the LLM — developers play a critical role in designing the surrounding architecture. Devnexus session 2: "Supercharging Applications with Java, Graphs, and a Touch of AI" (code repo 1, code repo 2) — a joint session with Erin Schnabel building an LLM-powered role-playing game using Langchain4j, Quarkus, and Neo4j. Multiple approaches: plain LLM chat, prompt engineering, and RAG with Neo4j as the vector/graph store, chunking documents while preserving structure via graph relationships. Our "Three Cs" challenge: Continuity (maintaining storyline), Context (growing context window), and Creativity (keeping the LLM on track without going off the rails). Splitting responsibilities between the LLM and a deterministic engine significantly improved results — a pattern developers should consider for complex AI apps. App redesign with an agentic architecture: dice roll, narration, suggestion, checkpoint, and recap agents — with the last three running concurrently for better performance. Markdown file (in one app) for agentic memory, enabling easy edits, rollbacks, and incremental indexing during live gameplay. Content spotlight: "No Keys, No LLM — Building a Wikidata Definition API with Embabel" — an article showcasing an agentic Java application that uses zero LLM. Embabel (a Java agentic framework) handles planning and execution with structured inputs/outputs, no external or local model required. Could the no-LLM agent pattern see broader adoption, or is it a niche experiment? New episodes will now use platform-agnostic Podfollow links. New blog post on jmhreif.com about Cypher AI procedures.

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Ep70: Devnexus Conference Recap + No-LLM Agentic Workflow

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This episode was published on March 13, 2026.

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Hear my recent experience at the Devnexus conference in Atlanta, where I delivered two sessions and connected with so many amazing people! Devnexus session 1: "Agents, Tools, and MCP, Oh My! Next Level AI Concepts for Developers" — a redesigned...

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