
Derek Norrbom developed and maintained the AnthusAI/Plexus platform, delivering over 170 features and 47 bug fixes across 16 months. He engineered scalable backend systems for AI-driven scoring, evaluation, and data processing, integrating technologies such as Python, AWS Lambda, and LangChain. Derek’s work included robust CI/CD pipelines, dynamic YAML-based configuration, and secure infrastructure using AWS CDK and Cognito. He improved reliability and observability through asynchronous processing, advanced logging, and comprehensive test automation. By refactoring core workflows and modernizing deployment, Derek enabled reproducible, efficient ML operations and streamlined developer onboarding, demonstrating depth in cloud architecture, API design, and system integration.

February 2026 monthly summary for AnthusAI/Plexus: Focused on stability, compatibility, and test coverage. Delivered substantial dependency updates to LangChain, Tactus, and related libraries to enhance compatibility and performance, and modernized testing workflows with a Makefile, unit and smoke tests for the Lambda function, plus updated test configurations and documentation to improve reliability and developer velocity. These efforts reduce technical debt, accelerate feature delivery, and improve Lambda reliability.
February 2026 monthly summary for AnthusAI/Plexus: Focused on stability, compatibility, and test coverage. Delivered substantial dependency updates to LangChain, Tactus, and related libraries to enhance compatibility and performance, and modernized testing workflows with a Makefile, unit and smoke tests for the Lambda function, plus updated test configurations and documentation to improve reliability and developer velocity. These efforts reduce technical debt, accelerate feature delivery, and improve Lambda reliability.
January 2026: Focused on enabling and hardening TactusScore integration for Plexus (AnthusAI/Plexus). Implemented library dependency, updated tests and mocks to align with Tactus 0.28.0 API changes, and hardened data structures for feedback items. Strengthened PlexusStorageAdapter to gracefully handle missing replay_index, reducing runtime errors. Updated test suite and dependencies, marking affected tests as expected failures where API changes required. These efforts improved integration readiness with TactusScore, stabilized the test suite, and reduced maintenance risk for future API changes.
January 2026: Focused on enabling and hardening TactusScore integration for Plexus (AnthusAI/Plexus). Implemented library dependency, updated tests and mocks to align with Tactus 0.28.0 API changes, and hardened data structures for feedback items. Strengthened PlexusStorageAdapter to gracefully handle missing replay_index, reducing runtime errors. Updated test suite and dependencies, marking affected tests as expected failures where API changes required. These efforts improved integration readiness with TactusScore, stabilized the test suite, and reduced maintenance risk for future API changes.
December 2025 Plexus monthly summary focusing on stability, deployment reliability, testing clarity, and expansion of data-scoring/ML capabilities. Delivered a suite of core stability fixes, scalable deployment pipelines, and tooling enhancements that reduce deployment risk, improve score accuracy, and accelerate release cycles. Demonstrated strong proficiency in Python, AWS (CodeDeploy, Lambda, EC2), CI/CD orchestration, test automation, metadata handling, and ML infra provisioning.
December 2025 Plexus monthly summary focusing on stability, deployment reliability, testing clarity, and expansion of data-scoring/ML capabilities. Delivered a suite of core stability fixes, scalable deployment pipelines, and tooling enhancements that reduce deployment risk, improve score accuracy, and accelerate release cycles. Demonstrated strong proficiency in Python, AWS (CodeDeploy, Lambda, EC2), CI/CD orchestration, test automation, metadata handling, and ML infra provisioning.
Month: 2025-11 — Plexus (AnthusAI/Plexus) delivered a robust set of features, reliability improvements, and deployment enhancements. Key features delivered include deterministic Item ID for item creation, test suite refinements for PLEXUS_APP_URL behavior, metadata sanitization/deserialization refactor in scoring utilities, improved SSM Association handling in the Scoring Worker Stack, and enforcement of a Max Jobs limit in JobProcessor/WorkerManager. Infrastructure and platform improvements across AWS and CI/CD include: region/script updates, new ECR stack for Lambda, migration from SSM to Secrets Manager for Lambda configuration, Docker Hub authentication in the base pipeline, SQS scoring job extractor with parallel processing and deduplication, Lambda fan-out with direct SQS usage and asset-path fixes, Lambda deployment enhancements with versioning and timestamp, Bedrock permissions for LLM invocations, trigger_fanout script enhancements with invocation summaries, and broader CI/CD/workflow refinements. Additional work includes Scoring Lambda and Mac-compatible Process Score Worker, environment/config improvements, and related secret management enhancements.
Month: 2025-11 — Plexus (AnthusAI/Plexus) delivered a robust set of features, reliability improvements, and deployment enhancements. Key features delivered include deterministic Item ID for item creation, test suite refinements for PLEXUS_APP_URL behavior, metadata sanitization/deserialization refactor in scoring utilities, improved SSM Association handling in the Scoring Worker Stack, and enforcement of a Max Jobs limit in JobProcessor/WorkerManager. Infrastructure and platform improvements across AWS and CI/CD include: region/script updates, new ECR stack for Lambda, migration from SSM to Secrets Manager for Lambda configuration, Docker Hub authentication in the base pipeline, SQS scoring job extractor with parallel processing and deduplication, Lambda fan-out with direct SQS usage and asset-path fixes, Lambda deployment enhancements with versioning and timestamp, Bedrock permissions for LLM invocations, trigger_fanout script enhancements with invocation summaries, and broader CI/CD/workflow refinements. Additional work includes Scoring Lambda and Mac-compatible Process Score Worker, environment/config improvements, and related secret management enhancements.
October 2025 monthly summary for AnthusAI/Plexus. Delivered significant business value through resource data optimization, scoring workflow improvements, and robust infrastructure updates that enhance performance, reliability, and scale. Key features delivered focused on data retrieval efficiency, scoring orchestration, and deployment stability, while major bugs were fixed to improve correctness and CI stability. Overall impact includes faster score/status lookups, more resilient asynchronous processing, and a cleaner, scalable deployment pipeline with improved observability. Technologies demonstrated span database indexing strategies, SDK-based data access, LangChain enhancements, containerization, CDK pipelines, SSM management, and comprehensive test infrastructure.
October 2025 monthly summary for AnthusAI/Plexus. Delivered significant business value through resource data optimization, scoring workflow improvements, and robust infrastructure updates that enhance performance, reliability, and scale. Key features delivered focused on data retrieval efficiency, scoring orchestration, and deployment stability, while major bugs were fixed to improve correctness and CI stability. Overall impact includes faster score/status lookups, more resilient asynchronous processing, and a cleaner, scalable deployment pipeline with improved observability. Technologies demonstrated span database indexing strategies, SDK-based data access, LangChain enhancements, containerization, CDK pipelines, SSM management, and comprehensive test infrastructure.
September 2025 focused on delivering business-relevant features for Plexus with reliability improvements across MCP deployments, Cognito authentication integration, and improved maintainability. The work enabled faster onboarding via dynamic tooling registration, robust Cognito-based auth, and more predictable MCP deployments, while also enhancing configuration, automation, and documentation to support scale and security.
September 2025 focused on delivering business-relevant features for Plexus with reliability improvements across MCP deployments, Cognito authentication integration, and improved maintainability. The work enabled faster onboarding via dynamic tooling registration, robust Cognito-based auth, and more predictable MCP deployments, while also enhancing configuration, automation, and documentation to support scale and security.
August 2025 monthly summary for Plexus (AnthusAI/Plexus): Delivered significant business-value improvements across data ingestion, LangChain integration, editor UX, and evaluation tooling. Key outcomes include a GPT-5-ready LangChainUser with enhanced token usage tracking, reasoning support, and improved error handling; a robust YAML highlighting fix in Monaco editor for multiline indicators; data loading and dataset loading options added (update and reload) to improve data freshness and reliability; LangChain integration and dependencies updated to support gpt-oss models and newer token handling; and UI and evaluation utilities refinements that streamline model evaluation and feedback flows. These changes reduce data-to-model cycle times, improve observability, and lower operational risk while expanding architecture capabilities.
August 2025 monthly summary for Plexus (AnthusAI/Plexus): Delivered significant business-value improvements across data ingestion, LangChain integration, editor UX, and evaluation tooling. Key outcomes include a GPT-5-ready LangChainUser with enhanced token usage tracking, reasoning support, and improved error handling; a robust YAML highlighting fix in Monaco editor for multiline indicators; data loading and dataset loading options added (update and reload) to improve data freshness and reliability; LangChain integration and dependencies updated to support gpt-oss models and newer token handling; and UI and evaluation utilities refinements that streamline model evaluation and feedback flows. These changes reduce data-to-model cycle times, improve observability, and lower operational risk while expanding architecture capabilities.
July 2025 monthly summary for AnthusAI/Plexus focused on reliability, observability, and scalable YAML/config workflows across LangGraphScore, classifier outputs, and documentation. Delivered tangible business value through improved output handling, robust state/trace management, refreshed documentation, and enriched classifier feedback with broader test coverage and hygiene improvements.
July 2025 monthly summary for AnthusAI/Plexus focused on reliability, observability, and scalable YAML/config workflows across LangGraphScore, classifier outputs, and documentation. Delivered tangible business value through improved output handling, robust state/trace management, refreshed documentation, and enriched classifier feedback with broader test coverage and hygiene improvements.
June 2025 monthly summary for AnthusAI/Plexus: Delivered notable business-value features and fixes across prediction, scoring, explainability, task tracking, and observability, with a focus on reliability, traceability, and deployability.
June 2025 monthly summary for AnthusAI/Plexus: Delivered notable business-value features and fixes across prediction, scoring, explainability, task tracking, and observability, with a focus on reliability, traceability, and deployability.
May 2025 recap: Major feature and reliability improvements across BERTopic topic analysis, transcript processing, and core Plexus tooling. Implemented OpenAI/LangChain topic representations with dynamic UMAP sizing, per-class visualizations, and async processing; hardened transcript parsing and error handling; strengthened MCP server/wrapper, added new Plexus tools, improved logging and timeout resilience. Launched Plexus FastMCP scaffolding with a new think tool and improved working-directory handling; expanded evaluation/testing framework with detailed mismatch explanations, CSV override loading, and mock Celery tests; fixed reports and upgraded dependencies. Business value: clearer topic insights, faster and safer LLM-driven processing, more stable runtimes, and improved maintainability.
May 2025 recap: Major feature and reliability improvements across BERTopic topic analysis, transcript processing, and core Plexus tooling. Implemented OpenAI/LangChain topic representations with dynamic UMAP sizing, per-class visualizations, and async processing; hardened transcript parsing and error handling; strengthened MCP server/wrapper, added new Plexus tools, improved logging and timeout resilience. Launched Plexus FastMCP scaffolding with a new think tool and improved working-directory handling; expanded evaluation/testing framework with detailed mismatch explanations, CSV override loading, and mock Celery tests; fixed reports and upgraded dependencies. Business value: clearer topic insights, faster and safer LLM-driven processing, more stable runtimes, and improved maintainability.
April 2025 monthly summary for AnthusAI/Plexus. Focused on delivering high-value features, improving data quality, and strengthening developer ergonomics. Key work includes LangGraphScore enhancements with node-level output aliasing and expanded metadata, MCP server integration and tooling, PlexusDashboardClient context management, authentication UX improvements, and targeted documentation updates, alongside a focused stability fix in tests.
April 2025 monthly summary for AnthusAI/Plexus. Focused on delivering high-value features, improving data quality, and strengthening developer ergonomics. Key work includes LangGraphScore enhancements with node-level output aliasing and expanded metadata, MCP server integration and tooling, PlexusDashboardClient context management, authentication UX improvements, and targeted documentation updates, alongside a focused stability fix in tests.
March 2025 focused on delivering robust, shareable evaluation workflows and strengthening security, observability, and maintainability within Plexus. Key features shipped include a configurable Share Links modal with multi-resource-type support and simplified evaluation fetching, plus UI updates for share links; hardened shared evaluations with improved token resolution and error handling, removal of deprecated IAM utilities, and enhanced AppSync permissions logging; migration to manual AWS Signature v4 signing with updated AWS SDK dependencies; enhanced shared evaluations with score results parsing, improved result selection and logging, and corresponding tests; improvements to the Evaluations page including score result selection/logging and Amplify cleanup; introduction of a Never Expire option and improved generation/clipboard handling for share links; LangGraph node results tracking; and general quality fixes and dependency updates. Business value: faster, safer sharing of evaluations; stronger access control and auditing; reduced maintenance via cleanup of legacy tooling; and a scalable foundation for collaboration features across resources.
March 2025 focused on delivering robust, shareable evaluation workflows and strengthening security, observability, and maintainability within Plexus. Key features shipped include a configurable Share Links modal with multi-resource-type support and simplified evaluation fetching, plus UI updates for share links; hardened shared evaluations with improved token resolution and error handling, removal of deprecated IAM utilities, and enhanced AppSync permissions logging; migration to manual AWS Signature v4 signing with updated AWS SDK dependencies; enhanced shared evaluations with score results parsing, improved result selection and logging, and corresponding tests; improvements to the Evaluations page including score result selection/logging and Amplify cleanup; introduction of a Never Expire option and improved generation/clipboard handling for share links; LangGraph node results tracking; and general quality fixes and dependency updates. Business value: faster, safer sharing of evaluations; stronger access control and auditing; reduced maintenance via cleanup of legacy tooling; and a scalable foundation for collaboration features across resources.
February 2025 Plexus monthly summary: Delivered a focused set of backend improvements across evaluation handling, classifier stability, task tracking, and testing infrastructure. Emphasis was placed on reliability, reproducibility, and expanding public evaluation capabilities to extend business value and collaboration with stakeholders.
February 2025 Plexus monthly summary: Delivered a focused set of backend improvements across evaluation handling, classifier stability, task tracking, and testing infrastructure. Emphasis was placed on reliability, reproducibility, and expanding public evaluation capabilities to extend business value and collaboration with stakeholders.
January 2025 (AnthusAI/Plexus) focused on delivering reliability, observability, and data quality improvements across the scoring pipeline, UI, artifacts management, and tooling. Delivered a robust, asynchronous score processing and evaluation metrics pipeline with improved error handling, ordering, and dynamic progress reporting. Strengthened CloudWatch logging with correct AWS region handling, enhanced credential management, and added tests to ensure reliability. Implemented UI enhancements for evaluations management, including delete functionality and improved detail views. Refined MLflow integration to avoid duplicate artifacts and ensure timestamped artifacts for results and reports. Enriched data samples with metadata support and robust JSON handling, and updated dependencies to ensure asyncio SQLAlchemy and NLTK compatibility. These changes improved data quality, traceability, and deployment reliability while boosting developer velocity.
January 2025 (AnthusAI/Plexus) focused on delivering reliability, observability, and data quality improvements across the scoring pipeline, UI, artifacts management, and tooling. Delivered a robust, asynchronous score processing and evaluation metrics pipeline with improved error handling, ordering, and dynamic progress reporting. Strengthened CloudWatch logging with correct AWS region handling, enhanced credential management, and added tests to ensure reliability. Implemented UI enhancements for evaluations management, including delete functionality and improved detail views. Refined MLflow integration to avoid duplicate artifacts and ensure timestamped artifacts for results and reports. Enriched data samples with metadata support and robust JSON handling, and updated dependencies to ensure asyncio SQLAlchemy and NLTK compatibility. These changes improved data quality, traceability, and deployment reliability while boosting developer velocity.
December 2024 monthly update for Plexus at AnthusAI. This month focused on strengthening model explainability, extraction accuracy, and evaluation reliability, delivering business-value features and robust fixes to support governance, trust, and efficiency. Highlights include per-classifier explanation overrides, exact matching for text extraction, asynchronous evaluation and improved dashboards, a new ContextExtractor node for contextual text extraction, and data integrity fixes in training/validation splits and dependency graph initialization.
December 2024 monthly update for Plexus at AnthusAI. This month focused on strengthening model explainability, extraction accuracy, and evaluation reliability, delivering business-value features and robust fixes to support governance, trust, and efficiency. Highlights include per-classifier explanation overrides, exact matching for text extraction, asynchronous evaluation and improved dashboards, a new ContextExtractor node for contextual text extraction, and data integrity fixes in training/validation splits and dependency graph initialization.
November 2024 monthly summary for AnthusAI/Plexus: Delivered four key improvements across scoring, transcripts, classification, and deterministic prompting, focusing on business value through clearer score reporting, improved data quality, and repeatable AI outputs. Highlights include enabling flexible score naming, refined transcript speaker handling with Unknown Speaker normalization, dynamic word-length-based classification, and deterministic prompts with default temperature 0 and single-line support. These changes improve reporting clarity, data integrity for experiments, and reliability of automated decisions.
November 2024 monthly summary for AnthusAI/Plexus: Delivered four key improvements across scoring, transcripts, classification, and deterministic prompting, focusing on business value through clearer score reporting, improved data quality, and repeatable AI outputs. Highlights include enabling flexible score naming, refined transcript speaker handling with Unknown Speaker normalization, dynamic word-length-based classification, and deterministic prompts with default temperature 0 and single-line support. These changes improve reporting clarity, data integrity for experiments, and reliability of automated decisions.
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