Codepocalypse Now: LangChain4j vs. Koog
A presentation at IntelliJ IDEA Conf 2026 in in Amsterdam, Netherlands by Viktor Gamov
CODEPOCALYPSE NOW LangChain4j vs JetBrains Koog · Baruch Sadogursky and Viktor Gamov · IntelliJ IDEA Conf 2026
15:00 — Basic AI Proficiency Training (Mandatory) Run by Dana from People Ops. Neither of us is going. X/Bluesky: @gamussa | @jbaruch
PICK YOUR FIGHTER LANGCHAIN4J (Java, langchain4j-agentic 1.20) — @gamussa · KOOG (Kotlin, Koog 1.2) — @jbaruch · Vote in chat: type LC4J or KOOG X/Bluesky: @gamussa | @jbaruch
Who We Are • Viktor Gamov — @gamussa • Baruch Sadogursky — @jbaruch • Slides, code & shownotes: speaking.gamov.io • and jbaru.ch/ideaconf-2026-codepocalypse X/Bluesky: @gamussa | @jbaruch
THE BUILD — 4 ROUNDS 1 DUMB CHATBOT — prompt -> text 2 + TOOLS + MCP — it can act 3 + MEMORY — it remembers 4 + AGENTIC PIPELINE — it self-corrects X/Bluesky: @gamussa | @jbaruch
ROUND 1 — DUMB CHATBOT prompt -> text · ~15s X/Bluesky: @gamussa | @jbaruch
One Factory Call. Is That an Agent? • One factory call. Prompt in -> text out. It answers charmingly and does nothing. Is this an agent? X/Bluesky: @gamussa | @jbaruch
THIS ISN’T AN AGENT. X/Bluesky: @gamussa | @jbaruch
Let’s build a REAL agent — in Java AND Kotlin. X/Bluesky: @gamussa | @jbaruch
WHO’S RIGHT? — VOTE 1 An agent is an INTERFACE the framework implements (LC4J) · or an OBJECT you construct (KOOG)? · Type LC4J or KOOG in chat X/Bluesky: @gamussa | @jbaruch
ROUND 2 — TOOLS + MCP calendar-mcp · organizer-mcp · ~45s X/Bluesky: @gamussa | @jbaruch
It Sent It. It Reused the Excuse. • • A calendar records that you bailed. It does not record the story you told. X/Bluesky: @gamussa | @jbaruch
WHO’S RIGHT? — VOTE 2 Tools: a REGISTRY the agent owns (KOOG) · or a PROVIDER the framework injects (LC4J)? · Type LC4J or KOOG in chat X/Bluesky: @gamussa | @jbaruch
ROUND 3 — MEMORY pre-seeded · same prompt · ~40s X/Bluesky: @gamussa | @jbaruch
Three Burned Flavors. One Fresh One. • • It names the three burned flavors. It picks a fresh one. Koog: LongTermMemory · LangChain4j: ContentRetriever over an embedding store, seven lines, local ONNX model X/Bluesky: @gamussa | @jbaruch
WHO’S RIGHT? — VOTE 3 Memory: an ADVISOR wrapping the conversation · or a PROVIDER the agent declares? · Type LC4J or KOOG in chat X/Bluesky: @gamussa | @jbaruch
ROUND 4 — DOMAIN MODELLING typed subtasks · sliced tools · a critic · ~90s X/Bluesky: @gamussa | @jbaruch
The Pipeline X/Bluesky: @gamussa | @jbaruch
Same Phase, Two Languages KOOG LANGCHAIN4J val deploy by subgraphWithTask< interface Deploy { DeclineRequest, DeclineDeployment>( tools = slices.read + slices.write, llmModel = Gemini3_5Flash, @Agent(outputKey = “deployment”) DeclineDeployment deploy( @V(“declineRequest”) DeclineRequest ) { request -> “Pick the flavor…” } r); } // .toolProvider(slices.readWrite()) X/Bluesky: @gamussa | @jbaruch
Four Tool Axes Axis Tools Reaches read getCalendar, getOrganizerSensitivity nobody write createCalendarEvent Viktor’s calendar user askViktor, pingViktor, awaitApproval Viktor comms sendDecline Dana. Irreversible. deploy gets read + write. Neither user nor comms. verify is the only phase that can ask. X/Bluesky: @gamussa | @jbaruch
The A/B JCLAW_NAIVE=1 ./run.sh context ./run.sh
strips recentlyUsedFlavors + the user # the typed handoff carries the constraint
Mode What happens Time naive stages Family Obligation — burned — critic rejects, refine fixes it ~2m domain-modelled ALREADY_PROFICIENT, approved first pass ~90s X/Bluesky: @gamussa | @jbaruch
“I build AI agents for a living and I am presenting a live conference talk on exactly this topic that afternoon.” It’s true. You are watching it be true. X/Bluesky: @gamussa | @jbaruch
WHO’S RIGHT? — VOTE 4 When your guardrail framework and the model disagree, who wins? · The FRAMEWORK (tool slices decide) or the MODEL (the critic decides)? · Type LC4J or KOOG in chat X/Bluesky: @gamussa | @jbaruch
High Score MAY 2026 25% ————————> 100% SEPT 2026 44% ————-> 77% The lift shrank. Source: [DATA-01] X/Bluesky: @gamussa | @jbaruch x4 x1.75
The Bill with context ######## tokens baseline ################ tokens BASELINE: 2.06x THE TOKENS. FOR THE WORSE ANSWER. Source: [DATA-02] X/Bluesky: @gamussa | @jbaruch
Same Checkpoints. Same App. KOOG LANGCHAIN4J Chatbot AIAgent(…) AiServices.create(…) Tools + MCP McpToolRegistryProvider McpToolProvider Memory LongTermMemory ContentRetriever Typed phases subgraphWithTask<In, Out> @Agent interface method Critic loop subgraphWithVerification loopBuilder().exitCondition(…) Approval node node { awaitApproval } humanInTheLoopBuilder() The send outside the graph outside the graph X/Bluesky: @gamussa | @jbaruch
FINAL VOTE — WHO’S RIGHT? LC4J or KOOG. Last chance. Type it in chat. X/Bluesky: @gamussa | @jbaruch
THE WINNER IS THE JAVA DEVELOPER. X/Bluesky: @gamussa | @jbaruch
Pick the Language You Love • Pick the JVM language you love. The agent era is open. Code + slides -> speaking.gamov.io · jbaru.ch/ideaconf-2026-codepocalypse [QR] X/Bluesky: @gamussa | @jbaruch
15:58 — Basic AI Proficiency Training Declined. Already proficient. X/Bluesky: @gamussa | @jbaruch
CONTINUE? — As always, have a nice day. X/Bluesky: @gamussa | @jbaruch @gamussa · @jbaruch
Which Java framework handles AI better: LangChain4j or Koog? In this live coding showdown, we’ll build a semantic code search application from scratch, putting both frameworks to the test. We’ll cover project setup, using language models, setting up a retrieval-augmented generation workflow, and creating a REST API.
You’ll see how these frameworks handle embedding generation, vector database integration, and real-world development challenges. By the end, the audience decides who wins—based on which framework gets the job done faster, better, and with less hassle (and whether the demo actually works).
This isn’t just a comparison; it’s a live experiment under pressure. Come and see which one comes out on top!
Code
The following code examples from the presentation can be tried out live.
Resources
The following resources were mentioned during the presentation or are useful additional information.
