Debugging Is Invariant Discovery: What One Kafka Session Taught Us About AI Agents
Table of Contents The shape of the sessionWhat the agent got rightWhat it got wrong, and why it matters for Java teamsThe agent's only sensor was the developerThe Java lesson: write the invariant down where a test can see itWhat ...
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From Spec-Driven Development to Living Specifications in Java Projects
Table of Contents The Promise of Spec-Driven DevelopmentWhat We Learned by Putting It into PracticeWhen the Specification Is Not the Source of TruthSBCE: Bringing the Specification Closer to the CodeSDD4J: Adapting to Multiple Architectures in Java ProjectsThere Is No Silver …
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Did Your AI Agent Ever Run a Debugger? One JVM Bug, Two Agent Runs
Table of Contents The method under testA checklist you can apply with any agentJava developers reach for the debugger without thinking about it. Set a breakpoint, run the failing test, look at the variables, then decide what to change. Most …
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Introducing BoxLang AI Explorer: A Local Catalog for Every AI Pattern
Table of Contents What It IsWhat’s CoveredTry It Live, Run It LocalQuick StartBring Your Own ProviderRunning a Sample DirectlyExplore, Fork, Contribute Learning a new AI API usually means jumping between scattered documentation pages, guessing at imports, and copy-pasting code that …
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Build Secure AI Chat Applications with BoxLang, RAG, Ollama, and Amazon Bedrock with Dan Card
Table of Contents Build Secure AI Chat Applications with BoxLang, RAG, Ollama, and Amazon BedrockGo Beyond a Basic AI ChatbotWhat You Will LearnBuild with More Control Over Your AI StackWho Should Attend?Prerequisites and Workshop SupportGet Your Early Bird Ticket and …
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Why Spring Teams Don’t Need a Second Runtime for AI Agents
Table of Contents What agents actually need in productionWhat Spring already gives youBUILD: Create agent teamsGOVERN: Budget, approvals, permissions, checkpointsOPERATE: Observe, recover and run safelyRetry that understands costOperational sovereigntyOne stack, one runtimeGetting started A JVM-native runtime for building, governing and …
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Context Is Code: A Tour of APM and AgentRC
Table of Contents 1. The problem: agent context drifts2. The idea: what if agent context had a package.json?3. The 3 strong guaranteesPortable by manifestSecure by defaultGoverned by policy4. What an APM package can contain5. The five commands you’ll actually use6. …
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Tiberius: A Security Testing Framework for LLM Applications in Java
Table of Contents 1. The Problem2. What Tiberius Does2.1 Fixture-Based Regression Testing2.2 Guardrail Validation Against Real Attack Data2.3. Probabilistic Security Contracts2.4. Bias Testing2.5. Model Fingerprinting3. Attack Coverage3.1 Buff Mutations4. Integration5. The Case for Shared Attack Datasets6. Security Testing as a …
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BoxLang AI 3.2.0 — Image Generation, Web Search, Fluent Audio, Agent Registry & MCP Observability
BoxLang AI 3.2.0 is here, and it’s a landmark release. We’re shipping five major features: image generation, web search, a fluent audio builder API, a centralized agent registry, and deep MCP observability along with a suite of analytics improvements and …
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Free Webinar: Making AI useful for Java developers in Real Applications with BoxLang!
Table of Contents Making AI Useful in Real ApplicationsWhat This Webinar Is AboutWhat You’ll LearnJoin the Ortus Community AI is everywhere right now, but for many development teams, the biggest question is no longer “What is AI?” it’s “How do …