We build and document agent systems, MCP tools, and AI pipelines. Open research for thoughtful builders.
Non-Commercial • Open Science • Education
Each area represents an evolving thread of work. Prototypes, diagrams, and notes emerge as side-products of the research, not commercial offerings.
Designing multi-agent architectures that separate reasoning, tools, and evaluation into composable layers. Investigating workflow pattern modeling, intelligent task scheduling, and system interoperability across orchestration platforms.
Pipeline-style systems where text, audio, and visuals flow through generation, annotation, and evaluation stages. Exploring prompt templates, quality assessment protocols, and multi-format production across articles, video scripts, and AI-synthesized audio.
Exploring how prompts, schemas, and meaning-making frameworks shape AI behavior. Research into conversational system architectures, interaction quality metrics, and the interpretive layers between human intent and model output.
Practices for sharing code, artefacts, and research notes in transparent, reproducible ways. Investigating automated data validation, documentation generation, and integration patterns that make research outputs verifiable and extensible.
Live or historical artefacts from the research. These are working systems, sketches, and diagrams - shared as open experiments, not products.
Research artefact · Internal system sketch
A multi-server system using agent cores, note structuring, and citation logging. Handles document generation, entity discovery, and outreach strategy through specialized sub-agents with API-based scheduling.
Note Implements layered reasoning for document analysis and stakeholder mapping.
Research artefact · Internal system sketch
Pipeline-style engine combining generation, annotation, and evaluation across text, audio, and visual formats. From concept to output using agent frameworks, custom prompt templates, and quality assessment protocols.
Note Exposes intermediate steps and evaluation scores, not just final outputs.
Research artefact · Internal system sketch
Visual frameworks for making the interpretive layers of AI systems explicit. Maps conversation quality metrics, satisfaction indicators, and the iterative refinement cycle between human intent and model behavior.
Note Treats prompts as objects to be reasoned about, not just instructions to execute.
Deep dives into agentic systems, creative workflows, and the philosophy of AI.
Unlock the power of Microsoft Copilot agents. This guide details building, licensing, and security best practices to scale enterprise AI while maintaining robust data governance.
As organizations deploy teams of specialized AI agents, they inherit behavioral security risks that traditional tools cannot detect. Here is a practical guide to auditing and hardening multi-agent systems.
AI tool integration was a messy tangle of custom schemas and glue code. Discover how the Model Context Protocol (MCP) revolutionizes this, offering a universal "plug" architecture for effortless, portable AI tool deployment.
Exploring how organizations can build integrated AI ecosystems that transform every aspect of operations through intelligent automation and human-AI collaboration.
Discover insights from Don Allen Stevenson III's new book 'Make A Seat' on leveraging technology, finding opportunities, and building resilience in the digital age.
Essential tips and strategies for generating high-quality content using AI tools and technologies.
A long-form project documenting how we can go from initial ideas to robust, explainable AI systems - with a focus on agents, orchestration, and real-world operations.
The book grows alongside the research. It collects practical patterns, failures, diagrams, and field notes from building AI systems in the wild.
Adaptivearts.ai Research Series
Discover what separates amateur prompting from professional practice. Learn why AI communication is a skill - not luck - and how structured approaches dramatically improve results.
Master the RCT framework (Role, Context, Task) and the Ten Commandments of prompt engineering. Build your first reusable prompt templates.
Try Prompt BuilderBuild a shared prompt library for your organization. Version control, categorization, and team-wide standardization.
Navigate enterprise requirements: prompt injection defense, PII filtering, compliance validation, and audit trails.
Try Injection Detection LabAdapt generic techniques to your industry. Terminology injection, output format design, and domain-specific validation.
Chain-of-thought reasoning, few-shot learning, self-consistency, and prompt optimization. Move from good to great.
Try Few-Shot BuilderExplore unconventional techniques: meta-prompting, creative prompting, and constraint relaxation at the boundaries of what's possible.
Connect prompts to applications. API integration, batch processing, error handling, and building robust AI-powered products.
A structured roadmap: Foundation (weeks 1-4), Scaling (weeks 5-8), Optimization (weeks 9-12). Personal assessment and goal-setting tools.
Try Enterprise FlowWhere is AI heading? Emerging capabilities, career trajectories, and how to stay ahead of a rapidly evolving field.
The protocol that connects AI to tools, data, and actions. Build your first MCP server and understand the architecture of modern AI systems.
Try MCP Server SetupDesign multi-agent systems with memory, task orchestration, and collaborative workflows. The cutting edge of AI engineering.
Adaptivearts.ai shares code, configurations, and research artefacts to promote reproducibility and transparency in AI development.
Over 30 Model Context Protocol servers built and tested across research, memory, content generation, and orchestration domains. Open-source tooling for AI infrastructure.
Content generation pipelines with multi-dimensional review, quality scoring, and entity consistency tracking. All stages are testable and replaceable.
Experiments are explicitly scoped. Capabilities are limited to prevent misuse, and data is handled with strict privacy protocols.
Open to thoughtful dialogue with researchers, practitioners, and organizations exploring similar questions.
Collaboration can range from informal conversations and research discussions to co-designed experiments.