https://mrmanna.github.io/ Complete public archive — preprints, articles, books, frameworks, code, and demos from Mahmudur R Manna. Enterprise AI, decision-driven software engineering, agent-native knowledge modelling. en mrmanna@github.io (Mahmudur R Manna) mrmanna@github.io (Mahmudur R Manna) Sun, 27 Apr 2026 00:00:00 GMT https://mrmanna.github.io/assets/favicon.svg https://mrmanna.github.io/ https://doi.org/10.5281/zenodo.19782389 zenodo.19782389 Sun, 26 Apr 2026 07:15:37 GMT Mahmudur R Manna Preprint Knowledge Engineering AI Agents Proposes that knowledge engineering for agents requires boundary analysis — defining where a thing starts, ends, relates, and what its purpose is — as the first modelling step, before lifecycle or state work begins. A knowledgebase composed of Active Things gives an agent an entry point into a case rather than forcing reconstruction from disconnected records and documents. Seven structural features (Start, End, States, Transitions, Events, Relations, Purpose) constitute the Identity Index of any Active Thing. Evidence is bounded to one anchor domain plus two transfer proof-of-concepts; not industrially validated. Article: https://huggingface.co/blog/mrmanna/active-knowledge-modelling-methodology — Book: https://www.amazon.com/dp/B0GY4XMMN1 — Mirror: https://www.researchgate.net/publication/404203082 https://cloudoffice.io/ai-reviews-of-the-book-the-world-of-0509f5fda49e https://cloudoffice.io/ai-reviews-of-the-book-the-world-of-0509f5fda49e Wed, 22 Apr 2026 00:00:00 GMT Mahmudur R Manna Note AI Agents Two AI reviewers — Gemini Pro and ChatGPT Pro — were given The World of Active Things with a structured prompt and asked for an independent critical assessment. Both prompts and full model responses are published verbatim, including the parts that were critical or uncertain. The point is transparency about how AI reads a technical argument, not endorsement of a positive verdict. Book: https://www.amazon.com/dp/B0GY4XMMN1 https://pub.towardsai.net/ai-state-machine-106387406c5a https://pub.towardsai.net/ai-state-machine-106387406c5a Sat, 18 Apr 2026 15:01:01 GMT Mahmudur R Manna Article AI Engineering Towards AI Toy agents demo well because they execute single tasks on forgiving inputs with no need to recover. Production agents face three harder requirements: recover from partial failures, hand off to other agents or humans with continuity, and remain observable under monitoring. The article argues all three converge on the same structural gap: an agent with no explicit model of its own state and lifecycle cannot do any of them reliably. State machines are not an architectural preference — they are the precondition. https://ai.gopubby.com/the-missing-middle-of-enterprise-ai-b135381bbb39 https://ai.gopubby.com/the-missing-middle-of-enterprise-ai-b135381bbb39 Wed, 15 Apr 2026 16:35:45 GMT Mahmudur R Manna Article Enterprise AI AI Advances Enterprise AI deployments tend to stall between the strategy deck and the working system — not because the model is wrong and not because the infrastructure is missing, but because the middle layer is never built. That middle layer must do three things: preserve decisions explicitly so they survive team and context change; enforce contracts so agent behaviour stays within intended bounds; and assemble context deliberately so the model operates on the right slice of the world rather than an unfiltered retrieval dump. https://mrmanna.medium.com/if-you-know-mcp-but-not-tools-this-is-for-you-f193e156abbd https://mrmanna.medium.com/if-you-know-mcp-but-not-tools-this-is-for-you-f193e156abbd Wed, 01 Apr 2026 00:00:00 GMT Mahmudur R Manna Article AI Engineering Medium MCP is a protocol — a standard way for a system to address an LLM through a defined structure — not synonymous with "MCP server". A tool has two distinct halves: the schema (what the model sees: name, description, parameters, required fields) and the command (what the runtime executes). The model sees no code — only the contract. Opens with a concrete bug: one missing required field in a tool schema caused a cascading night of parser failures, and the fix was not a better prompt but a correctly specified contract. https://huggingface.co/blog/mrmanna/push https://huggingface.co/blog/mrmanna/push Sat, 14 Mar 2026 07:08:48 GMT Mahmudur R Manna Essay Hugging Face A reflective essay on writing, coding, and publishing real frameworks before the surrounding language is ready. Three retrospective sections: DDSE — that AI-assisted software delivery requires structured decision records throughout the SDLC; ACM — that agent governance must be designed in as typed contracts and replayable ledgers before deployment; and CEF — that context is part of the engineering foundation, not a retrieval utility around it. https://www.amazon.com/dp/B0GY4XMMN1 amazon.B0GY4XMMN1 Sun, 01 Feb 2026 00:00:00 GMT Mahmudur R Manna Book Knowledge Engineering AI Agents 81 pages. The monograph behind AKMM. Argues knowledge becomes meaningful only when you first ask: what belongs to this thing as this thing? That is boundary. Then: how does it begin, move, relate, and end within that boundary? That is lifecycle. Develops seven structural features — Start, End, States, Transitions, Events, Relations, Purpose — and the Identity Index as the minimum through which a thing becomes operable knowledge rather than a record cluster. #99 in Data Modeling and Design. Kindle: https://www.amazon.com/dp/B0GX2VP8RS — DOI: https://doi.org/10.5281/zenodo.19782389 https://www.amazon.com/there-seasons-Mahmudur-Rahman-Manna-ebook/dp/B0DVJ73Z9J amazon.B0DVJ73Z9J Sun, 01 Feb 2025 00:00:00 GMT Mahmudur R Manna Book Philosophy Psychology 43 pages. Introduces the PEPPA framework (Peace as Purpose, Emotional Intelligence, Proactivity, Patience, Acceptance) — integrating entropy, inertia, and equilibrium from physics with Stoic and Frankl-inspired principles for human resolve. Models mental resilience through three physics metaphors: entropy (sustained effort without renewal degrades capability), inertia (initiating change requires activation energy beyond intention alone), and equilibrium (performance requires balance between challenge and recovery). DOI: https://doi.org/10.5281/zenodo.13843668 https://www.amazon.com/ELIAS-Meaning-Mahmudur-Rahman-Manna/dp/B0DFV75SG7 amazon.B0DFV75SG7 Thu, 01 Aug 2024 00:00:00 GMT Mahmudur R Manna Book Philosophy Psychology 100 pages. A novella-style dialogue where a researcher studies toxic workplace behaviours alongside Elias Thorn — covering distrust, scarcity mindset, and the search for purpose. Integrates Stoic self-regulation and Viktor Frankl's will-to-meaning with workplace behavioural dynamics. Reviewed by Gabriel Santos for Readers' Favorite. #2,372 in Behavioural Psychology on Amazon. https://www.amazon.com/Enterprise-AI-Strategic-Blueprint-Purple/dp/B0D5RKHXMY amazon.B0D5RKHXMY Wed, 01 May 2024 00:00:00 GMT Mahmudur R Manna Book Enterprise AI Strategy 181 pages. Introduces the Enterprise AI Transformation Framework (EAITF): decision-domain profiling, Principal Component Analysis, and an AI Effectiveness Index with a Python walkthrough. Rated 3.8/5 across 5 reviews. Leanpub: https://leanpub.com/enterpriseaiforpurplepeople — DOI: https://doi.org/10.5281/zenodo.11422132 https://leanpub.com/esgdata https://leanpub.com/esgdata Mon, 01 Jan 2024 00:00:00 GMT Mahmudur R Manna Book ESG Data A hands-on reference for professionals, policymakers, and investors: environmental, social, and governance metrics with Python calculation examples and global case studies including India and Bangladesh. Companion series on Medium covers metrics, calculation, and reporting in three parts: https://mrmanna.medium.com/esg-data-explained-a-comprehensive-guide-to-metrics-calculation-and-reporting-part-i-ba5479e527ce https://huggingface.co/blog/mrmanna/active-knowledge-modelling-methodology https://huggingface.co/blog/mrmanna/active-knowledge-modelling-methodology Sat, 25 Apr 2026 00:00:00 GMT Mahmudur R Manna Framework Knowledge Engineering AI Agents Active Knowledge Modelling Methodology — models a knowledgebase as a world of Active Things with explicit boundary, lifecycle, identity, lived memory, canonical events, and purpose, so AI agents can operate on the case rather than reconstruct it. Bounded methodology evidence (one anchor, two transfer PoCs); not an industry standard. DOI: https://doi.org/10.5281/zenodo.19782389 — Book: https://www.amazon.com/dp/B0GY4XMMN1 https://ddse-foundation.github.io/ https://ddse-foundation.github.io/ Tue, 01 Jul 2025 00:00:00 GMT Mahmudur R Manna Framework Software Engineering DDSE Foundation An SDLC where significant technical decisions are captured and governed as first-class artefacts — Architectural Decision Record (ADR), Engineering Decision Record (EDR), Incident Decision Record (IDR), Technology Decision Map (TDM), and Master Decision Document (MDD) — so AI-assisted development stays inside human authority and preserves architectural intent. Humans retain authority; the AI uses decision records as context, not discretion. DOI: https://doi.org/10.5281/zenodo.16462014 — GitHub: https://github.com/ddse-foundation/ddse-foundation https://doi.org/10.5281/zenodo.17278997 zenodo.17278997 Wed, 01 Oct 2025 00:00:00 GMT Mahmudur R Manna Framework AI Agents DDSE Foundation A spec-first contract layer for agentic systems: typed contracts, deterministic execution, and a replayable decision memory so agents can be reasoned about, not just observed. Where most agent frameworks treat goals, plans, and tools as prompt constructs, ACM defines them as typed artefacts with explicit lifecycle states, guard conditions, capability maps, and a replayable ledger. Ships a TypeScript reference runtime under the DDSE Foundation. GitHub: https://github.com/ddse-foundation/acm — Docs: https://ddse-foundation.github.io/acm/ — Article: https://huggingface.co/blog/mrmanna/agentic-contract-model https://github.com/ddse-foundation/cef https://github.com/ddse-foundation/cef Thu, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Framework AI Engineering DDSE Foundation An ORM-style framework for LLM context: relationship-aware context assembly over knowledge models with graph and vector persistence. Moves beyond retrieval by modelling knowledge as typed entities with relationships, lifecycle, and semantic distance. Marked as a research edition; not enterprise-hardened. Docs: https://ddse-foundation.github.io/cef/ — Article: https://huggingface.co/blog/mrmanna/ddse-cef-orm https://doi.org/10.5281/zenodo.11422132 zenodo.11422132 Wed, 01 May 2024 00:00:00 GMT Mahmudur R Manna Framework Enterprise AI Strategy The framework behind Enterprise AI: Strategic Blueprint for Purple People. Covers decision-domain inventory and profiling, and an AI Effectiveness Index derived through PCA over scored decision domains. Provides a structured method for enterprises to identify where AI intervention will have the highest measurable impact. Book: https://www.amazon.com/Enterprise-AI-Strategic-Blueprint-Purple/dp/B0D5RKHXMY — Leanpub: https://leanpub.com/enterpriseaiforpurplepeople https://doi.org/10.5281/zenodo.15031473 zenodo.15031473 Sat, 01 Mar 2025 00:00:00 GMT Mahmudur R Manna Preprint Knowledge Engineering AI Agents A hybrid architecture for closing gaps in structured knowledge: a symbolic knowledge graph identifies where conceptual connective tissue is missing, GPT is queried incrementally to propose bridge concepts, and the proposed chain is validated and reintegrated into the graph. The cycle iterates until the gap narrows below a threshold. Frames the problem as one of convergence, not generation — the LLM fills specific holes rather than generating freeform explanations. https://doi.org/10.5281/zenodo.13887022 zenodo.13887022 Tue, 01 Oct 2024 00:00:00 GMT Mahmudur R Manna Preprint Philosophy AI Engineering Applies Descartes' four rules — decompose, order, enumerate, review — as a reasoning discipline imposed on GPT. The central question is whether a Cartesian audit structure produces more reliable, less confabulated responses on complex reasoning tasks than open-ended prompting. A methodological experiment in structured epistemic discipline applied to large language models. https://doi.org/10.5281/zenodo.13843668 zenodo.13843668 Sun, 01 Sep 2024 00:00:00 GMT Mahmudur R Manna Preprint Philosophy Psychology The DOI-backed preprint behind There Are Seasons of the Mind. Models human mental resilience through three physics metaphors: entropy (sustained effort without renewal degrades capability), inertia (initiating change requires activation energy beyond intention alone), and equilibrium (performance requires balance between challenge and recovery). Integrated with Stoic self-regulation and Viktor Frankl's will-to-meaning as practical counterweights to each physical force. Book: https://www.amazon.com/there-seasons-Mahmudur-Rahman-Manna-ebook/dp/B0DVJ73Z9J https://doi.org/10.5281/zenodo.13324186 zenodo.13324186 Thu, 01 Aug 2024 00:00:00 GMT Mahmudur R Manna Preprint Philosophy Governance Argues that the engagement-maximising design of current social platforms is not technologically inevitable — it is a deliberate architectural choice. Proposes an alternative set of design principles oriented toward transparency, contribution, and civic participation that could redirect the same attention infrastructure toward measurably better social outcomes, without requiring platform replacement. https://doi.org/10.5281/zenodo.13310258 zenodo.13310258 Fri, 02 Aug 2024 00:00:00 GMT Mahmudur R Manna Preprint Philosophy Work Distinguishes between activity (visible motion through tools, meetings, and status updates) and productive work (directed effort that moves a stated goal forward). Examines the structural conditions — notification design, meeting culture, tooling overhead, and fragmented context — that make high-activity, low-output environments self-reinforcing, and why individual willpower is an insufficient corrective. https://doi.org/10.5281/zenodo.13308576 zenodo.13308576 Fri, 01 Aug 2024 00:00:00 GMT Mahmudur R Manna Preprint Governance Work The "single neck to choke" management model concentrates accountability at one person as a mechanism of control. This paper argues the model is structurally incompatible with networked, cross-functional work — and with Gen Z's expectation of distributed ownership — because it optimises for blame assignment over problem resolution, damages trust faster than it creates accountability, and collapses under the ambiguity of modern product delivery. https://doi.org/10.5281/zenodo.11784521 zenodo.11784521 Sat, 01 Jun 2024 00:00:00 GMT Mahmudur R Manna Preprint Software Engineering AI Engineering A practical mapping of ML integration patterns for enterprise engineers working with existing Java/microservice systems. Covers sidecar inference, async event-driven ML triggers, API bridge patterns, and the deployment lifecycle differences between ML models and conventional software artefacts. Addresses the common failure mode of treating an ML model as a library call rather than as a separately versioned, separately deployed runtime. https://github.com/ddse-foundation/acm https://github.com/ddse-foundation/acm Wed, 01 Oct 2025 00:00:00 GMT Mahmudur R Manna Code AI Agents TypeScript Agentic Contract Model — spec-first contract layer for agentic systems. Defines goals, plans, and tools as typed artefacts with explicit lifecycle states, guard conditions, capability maps, and a replayable decision ledger. Ships a TypeScript reference runtime. Agent behaviour can be inspected and replayed, not just observed after the fact. Docs: https://ddse-foundation.github.io/acm/ https://github.com/ddse-foundation/cef https://github.com/ddse-foundation/cef Thu, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Code AI Engineering Java Context Engineering Framework — an ORM-style layer for LLM context assembly. Combines graph and vector persistence, relationship navigation, parser systems, and LLM integration so that context is assembled deliberately rather than retrieved as a flat embedding result. Research edition; not enterprise-hardened. Docs: https://ddse-foundation.github.io/cef/ https://github.com/ddse-foundation/ddse-foundation https://github.com/ddse-foundation/ddse-foundation Tue, 01 Jul 2025 00:00:00 GMT Mahmudur R Manna Code Software Engineering Python DDSE implementation templates, decision record formats, and worked examples for teams adopting Decision-Driven Software Engineering. Covers ADR, EDR, IDR, TDM, and MDD artefact types with guidance on how each fits into an AI-assisted development workflow where humans retain authority. Foundation site: https://ddse-foundation.github.io/ https://github.com/mrmanna/cockpit https://github.com/mrmanna/cockpit Mon, 01 Jan 2018 00:00:00 GMT Mahmudur R Manna Code Software Architecture Java Java PWA and microservice development platform from the CloudOffice digital workplace work. Architecture: Netty 4 HTTP/2 API gateway routing to Jersey microservices, bck2brwsr-compiled browser-side SPA shell, gadget SDK for composable UI modules, SASS/JSON theme and layout builder. Article: https://mrmanna.medium.com/cloudoffice-cockpit-framework-a1111f466eff https://github.com/kareegor/mmfb https://github.com/kareegor/mmfb Fri, 01 Jan 2021 00:00:00 GMT Mahmudur R Manna Code Software Architecture Java Multi micro-frontends and backends — cloud-agnostic microservice ecosystem. Stack: Spring Boot, Traefik, Keycloak, Consul, Kafka, Angular microfrontends, Prometheus and Grafana. Central constraint is portability: runs on a developer machine, Docker Swarm, and any Kubernetes provider without environment-specific changes. Article: https://mrmanna.medium.com/cloud-agnostic-microfrontends-and-microservices-architecture-fcf53feb815f https://github.com/mrmanna/agnosticmlflow https://github.com/mrmanna/agnosticmlflow Wed, 01 Jan 2025 00:00:00 GMT Mahmudur R Manna Code AI Engineering Python Cloud-agnostic ML pipelines using Apache Beam with an Apache Flink runner on Minikube and MinIO as object storage. The same pipeline code runs locally and can target any cloud-hosted Beam runner without vendor lock-in. Companion to the nine-part cloud-agnostic platforms article series. Article: https://ai.gopubby.com/i-spent-a-week-building-the-foundation-for-cloud-agnostic-ml-pipelines-heres-everything-you-f147bfb75ad0 https://www.youtube.com/watch?v=voF6x1aV_z4 https://www.youtube.com/watch?v=voF6x1aV_z4 Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo AI Agents 41:15. End-to-end run of the agent stack — orchestration, tools, memory. Demonstrates Capability OS with the Omni Agent pattern: how the agent selects tools, manages memory across turns, and routes sub-tasks. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=0IzQgqFSdvo https://www.youtube.com/watch?v=0IzQgqFSdvo Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo Software Engineering 4:46. Decision-driven software engineering applied on a small concrete case. Shows the decision record artefacts (ADR, EDR) in use and how they structure the AI-assisted development workflow. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=kidJABlhHk8 https://www.youtube.com/watch?v=kidJABlhHk8 Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo Knowledge Engineering 3:23. Visual companion to the agent-architecture paper on dynamic neuro-symbolic knowledge gap bridging. Paper: https://doi.org/10.5281/zenodo.15031473. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=kX5SykY0OhM https://www.youtube.com/watch?v=kX5SykY0OhM Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo AI Engineering 2:59. Demonstration of a parallel deep research pipeline using DeepSeek R1 — multiple research threads running concurrently, results aggregated into a structured report. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=TDFDKpYzgSE https://www.youtube.com/watch?v=TDFDKpYzgSE Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo AI Agents 9:15. First session of the multi-agent chatroom build — agents communicating in a shared room, routing messages to the appropriate specialist. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=GlKbS05ZWp0 https://www.youtube.com/watch?v=GlKbS05ZWp0 Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo AI Agents 8:19. Week 2 of the multi-agent chatroom — extended capabilities, persistent state between sessions, and improved routing logic. Hosted on YouTube under @PurpleThinkers. https://www.youtube.com/watch?v=jK3gvQnYr8U https://www.youtube.com/watch?v=jK3gvQnYr8U Mon, 01 Jan 2026 00:00:00 GMT Mahmudur R Manna Demo AI Agents 0:53. Short walkthrough of the Agentic Contract Model coder loop — how the agent picks up a task, executes against a contract, and commits the result. Silent. Hosted on YouTube under @PurpleThinkers.