{"_meta":{"version":"2.2.0","publication":{"source":"https://api.lucioduran.com","capturedAt":"2026-10-21T20:15:46.491Z","version":"4d48a328f2ae6f3642e5fd46f9d89971907aa2dd910baf3d870bea3cad7555a2"},"attribution":"Author-published professional profile; follow credential and project links for supporting sources.","purpose":"AI agent consumption, structured profile data for Lucio Duran","source":"https://lucioduran.com","llms_txt":"https://lucioduran.com/llms.txt","llms_full_txt":"https://lucioduran.com/llms-full.txt","agent_card":"https://lucioduran.com/.well-known/agent.json","openapi_spec":"https://lucioduran.com/.well-known/openapi.json","security_txt":"https://lucioduran.com/.well-known/security.txt","data_api":"https://lucioduran.com/api/content-index","search":"https://lucioduran.com/api/search"},"person":{"name":"Lucio Duran","title":"AI-Driven Technology Director & Full-Stack Product Architect","currentRole":"Chief Technology Officer","currentCompany":"LOi","location":{"city":"San José de Mayo ","country":"Uruguay"},"email":"email@lucioduran.com","bio":"22+ years architecting and shipping software products across healthcare, e-commerce, and marketplace verticals, from system design to production deployment.\nI lead engineering organizations where AI is not a feature but the core infrastructure layer. My work spans agentic AI systems, LLM integration patterns, full-stack development (React, React Native, Node, Python, iOS), and the strategic decisions that turn technical capabilities into revenue.\nI've built and scaled cross-functional teams across LATAM, the US, and Europe, owning the full product lifecycle: architecture decisions, CI/CD pipelines, cloud infrastructure, API design, and frontend performance. I operate at the intersection of hands-on engineering and executive technology strategy, I still read the PRs, and I still make the technical calls.\nCurrent focus: AI-augmented product development, agentic workflows, and building technology that compounds.","profilePicture":"https://statics.lucioduran.com/images/lucioduran.jpeg","socialLinks":[{"platform":"Github","url":"https://github.com/lucioduran"},{"platform":"Facebook","url":"https://facebook.com/lucioduran"},{"platform":"LinkedIn","url":"https://uy.linkedin.com/in/lucioduran"},{"platform":"Twitter","url":"https://twitter.com/lucioduran"},{"platform":"Instagram","url":"https://instagram.com/lucioduran"}],"websites":[{"name":"Portfolio","url":"https://lucioduran.com"},{"name":"Art","url":"https://lucioduran.art"}]},"experience":{"totalPositions":20,"currentPositions":[{"title":"Chief Technology Officer (CTO)","company":"LOi","country":"Uruguay","startDate":"2025-03-01T02:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/cto-at-loi-2025","contributions":["Architected and built a proprietary e-commerce platform from first principles, encompassing technical specification, database modeling, API design, UI engineering, and payment integration","Led the mobile application initiative from concept through production, defining the architecture, technology selection, and cross-platform development strategy","Orchestrated a complete cloud infrastructure migration to AWS, redesigning the deployment topology for high availability, auto-scaling, and cost optimization","Integrated a comprehensive suite of AWS services including S3, CloudFront, Lambda, SES, SNS, SageMaker, Personalize, and Glue into the production ecosystem","Designed and implemented the complete user interface and interaction model across web and mobile, applying UX research methodologies and data-driven iteration","Developed and maintained a proprietary RESTful API layer serving as the integration backbone for all front-end clients, mobile applications, and third-party services","Developed a Progressive Web Application (PWA) with offline-first architecture, service worker caching strategies, and push notification capabilities","Engineered an AI-driven personalized product recommendation system leveraging Amazon SageMaker for model training, AWS Glue for ETL pipelines, and Amazon Personalize for real-time inference"]},{"title":"Chief Technology Officer (CTO)","company":"MiBelleza.uy","country":"Uruguay","startDate":"2025-03-01T02:00:00.000Z","type":"full time job","url":"https://mibelleza.uy","detailPage":"https://lucioduran.com/work-experiences/cto-at-mibelleza-2025","contributions":["Architected and built a proprietary e-commerce platform from first principles, encompassing technical specification, system design, UI engineering, and API development","Orchestrated a full infrastructure deployment to AWS, provisioning and configuring VPC, EC2, S3, CloudFront, RDS, and Lambda services","Designed and implemented the complete user interface and interaction model, applying UX research methodologies and accessibility standards","Developed a Progressive Web Application (PWA) with offline-first architecture, service worker caching strategies, and push notification capabilities","Engineered an AI-driven personalized product recommendation system leveraging Amazon SageMaker for model training, AWS Glue for ETL pipelines, and Amazon Personalize for real-time inference"]}],"pastPositions":[{"title":"Chief Technology Officer (CTO)","company":"Nilus","country":"United States","startDate":"2023-05-01T03:00:00.000Z","endDate":"2024-12-31T03:00:00.000Z","type":"full time job","url":"https://nilus.co","detailPage":"https://lucioduran.com/work-experiences/cto-at-nilus","description":"As CTO, I defined and executed the technology strategy for Nilus, establishing the architectural blueprint, systems integration roadmap, and engineering team structure. Led the technical specification and delivery of every product initiative, from platform development to cloud infrastructure provisioning. Conducted strategic technology vendor evaluations, quantifying the operational impact and engineering effort associated with third-party service adoption. Drove continuous innovation through systematic research into emerging technologies applicable to e-commerce, machine learning, and distributed systems.","contributions":["Architected and built a proprietary e-commerce platform from first principles, encompassing technical specification, system design, UI engineering, and API development","Designed and implemented the complete user interface and interaction model, applying UX research methodologies and accessibility standards","Developed a Progressive Web Application (PWA) with offline-first architecture, service worker caching strategies, and push notification capabilities"]},{"title":"VP of Product","company":"LOi","country":"Uruguay","startDate":"2023-05-01T03:00:00.000Z","endDate":"2025-03-01T03:00:00.000Z","type":"part time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/vp-of-product-at-loi","description":"As VP of Product, I formulated and drove the long-term product vision and technology roadmap, aligning engineering capabilities with business strategy and market opportunity. Responsible for defining product priorities, validating market hypotheses, and ensuring that every technology initiative delivered measurable impact against organizational KPIs. Served as the primary liaison between executive stakeholders, engineering teams, and external clients, synthesizing business requirements into executable product strategies.","contributions":[]},{"title":"Product Owner","company":"LOi","country":"Uruguay","startDate":"2012-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/product-owner-at-loi","description":"As Product Owner, I defined and communicated the strategic product vision for LOi's digital platforms, translating business objectives into actionable engineering requirements. Owned the product backlog prioritization, sprint planning, and stakeholder alignment processes. Applied data-driven decision-making to optimize feature delivery cadence, resource allocation, and cross-team dependencies across the entire product portfolio.","contributions":["Achieved consistently on-time, on-scope delivery across all product milestones through rigorous sprint planning and velocity forecasting","Led a comprehensive organizational transformation from legacy tooling and waterfall processes to agile methodologies, modern collaboration platforms, and industry-standard engineering practices","Maximized cross-functional resource utilization by implementing workload balancing algorithms and capacity planning frameworks across all concurrent projects","Determined optimal team composition and staffing models for each project through empirical analysis of velocity metrics and domain complexity","Achieved sustained throughput optimization by systematically identifying and eliminating bottlenecks in each team's delivery pipeline","Instituted and enforced engineering best practices, technology governance standards, and quality assurance protocols to ensure production-grade output across all product-related initiatives"]},{"title":"Chief Technology Officer (CTO)","company":"MiBelleza.uy","country":"Uruguay","startDate":"2021-12-17T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://mibelleza.uy","detailPage":"https://lucioduran.com/work-experiences/cto-at-mibelleza","description":"As CTO, I defined and executed the technology strategy for MiBelleza.uy, establishing the architectural blueprint, systems integration roadmap, and engineering team structure. Led the technical specification and delivery of every product initiative, from platform development to cloud infrastructure provisioning. Conducted strategic technology vendor evaluations, quantifying the operational impact and engineering effort associated with third-party service adoption. Drove continuous innovation through systematic research into emerging technologies applicable to e-commerce, machine learning, and distributed systems.","contributions":["Architected and built a proprietary e-commerce platform from first principles, encompassing technical specification, system design, UI engineering, and API development","Orchestrated a full infrastructure migration to AWS, provisioning and configuring VPC, EC2, S3, CloudFront, RDS, and Lambda services","Designed and implemented the complete user interface and interaction model, applying UX research methodologies and accessibility standards","Developed a Progressive Web Application (PWA) with offline-first architecture, service worker caching strategies, and push notification capabilities","Engineered an AI-driven personalized product recommendation system leveraging Amazon SageMaker for model training, AWS Glue for ETL pipelines, and Amazon Personalize for real-time inference"]},{"title":"Chief Technology Officer (CTO)","company":"LOi","country":"Uruguay","startDate":"2014-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/cto-at-loi","description":"As CTO, I defined and executed the technology strategy for LOi, establishing the architectural blueprint, systems integration roadmap, and engineering team structure. Led the technical specification and delivery of every product initiative, from platform development to cloud infrastructure provisioning. Conducted strategic technology vendor evaluations, quantifying the operational impact and engineering effort associated with third-party service adoption. Drove continuous innovation through systematic research into emerging technologies applicable to e-commerce, machine learning, and distributed systems.","contributions":["Architected and built a proprietary e-commerce platform from first principles, encompassing technical specification, database modeling, API design, UI engineering, and payment integration","Led the mobile application initiative from concept through production, defining the architecture, technology selection, and cross-platform development strategy","Orchestrated a complete cloud infrastructure migration to AWS, redesigning the deployment topology for high availability, auto-scaling, and cost optimization","Integrated a comprehensive suite of AWS services including S3, CloudFront, Lambda, SES, SNS, SageMaker, Personalize, and Glue into the production ecosystem","Designed and implemented the complete user interface and interaction model across web and mobile, applying UX research methodologies and data-driven iteration","Developed and maintained a proprietary RESTful API layer serving as the integration backbone for all front-end clients, mobile applications, and third-party services","Developed a Progressive Web Application (PWA) with offline-first architecture, service worker caching strategies, and push notification capabilities","Engineered an AI-driven personalized product recommendation system leveraging Amazon SageMaker for model training, AWS Glue for ETL pipelines, and Amazon Personalize for real-time inference"]},{"title":"User Interface (UI) Chief","company":"LOi","country":"Uruguay","startDate":"2012-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/ui-design-chief-at-loi","description":"As Head of User Interface Engineering, I directed the visual design strategy and component architecture for LOi's web and mobile platforms. Led the creation, prototyping, and iterative validation of complex interface systems, translating product requirements into pixel-perfect, performance-optimized UI implementations grounded in design system principles and cross-device consistency.","contributions":["Established a comprehensive design system with reusable component libraries, design tokens, spacing scales, and typographic hierarchies ensuring visual consistency across all platforms","Led the end-to-end UI architecture for the e-commerce platform, from wireframing through production implementation, with ongoing maintenance of the component library and visual regression testing","Designed and maintained the mobile application interface, ensuring native-grade interaction patterns and platform-specific design conventions across iOS and Android"]},{"title":"User Experience (UX) Chief","company":"LOi","country":"Uruguay","startDate":"2012-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/ux-design-chief-at-loi","description":"As Head of User Experience, I served as the principal UX architect and researcher, responsible for defining the interaction paradigms, usability standards, and experience optimization strategies across all LOi digital products. Applied evidence-based design methodologies, including heuristic evaluation, A/B testing, and behavioral analytics, to systematically improve user satisfaction, task completion rates, and conversion metrics across every customer-facing interface.","contributions":["Led, analyzed, dimensioned, and validated hundreds of UX iterations through structured design sprints, stakeholder workshops, and usability testing sessions","Directed end-to-end UX research and implementation for the e-commerce platform, from competitive benchmarking and user journey mapping through prototype validation and production deployment","Directed end-to-end UX research and implementation for the mobile application, applying platform-specific interaction patterns, gesture-based navigation paradigms, and mobile-first design principles","Achieved cross-platform usability standardization by establishing shared design patterns, interaction libraries, and accessibility compliance guidelines across web, mobile, and marketplace interfaces"]},{"title":"Chief Design Officer (CDO)","company":"LOi","country":"Uruguay","startDate":"2008-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/cdo-at-loi","description":"As Chief Design Officer, I established and directed LOi's comprehensive design strategy, encompassing brand identity systems, product design, digital marketing collateral, advertising campaigns, and print production. Led a multidisciplinary design team while serving as principal designer, ensuring visual coherence and brand integrity across every customer touchpoint, media channel, and product surface.","contributions":["Created and codified the complete brand identity system, including logo design, color theory, typography selection, and visual language, from initial concept to final production assets","Established and optimized the company's presence across major e-commerce marketplaces, designing storefront experiences that maximized conversion and brand recognition","Authored the comprehensive branding manual and design guidelines, defining usage rules, asset specifications, and governance standards for cross-channel consistency","Built, mentored, and managed the design team, establishing hiring criteria, skill development programs, and design review workflows","Led the creation of multinational brand identities, adapting visual systems for cultural relevance and regulatory compliance across diverse markets"]},{"title":"Mobile Development Chief","company":"LOi","country":"Uruguay","startDate":"2020-12-01T03:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/mobile-dev-chief-at-loi","description":"As Head of Mobile Development at LOi, I led the mobile engineering division while serving as a principal contributor on the React Native codebase. Defined the architectural patterns, integration strategies, and performance optimization standards for the company's cross-platform mobile applications. Conducted continuous technical research to identify and evaluate emerging mobile technologies, frameworks, and platform-specific capabilities for production adoption.","contributions":["Engineered the LOi mobile application from the ground up using React Native, implementing a shared codebase architecture for iOS and Android with native module bridging where performance-critical","Achieved top-3 ranking in the App Store's most downloaded category for three consecutive weeks post-launch, demonstrating market-product fit validation","Achieved top-3 ranking in Google Play's most downloaded category for three consecutive weeks, confirming cross-platform market traction","Orchestrated the end-to-end publication and distribution pipeline across Apple App Store, Google Play Store, and ancillary marketplaces","Developed a purpose-built Huawei AppGallery InstaApp variant, adapting the platform to Huawei Mobile Services (HMS) ecosystem constraints and APIs"]},{"title":"Frontend Development Chief","company":"LOi","country":"Uruguay","startDate":"2012-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/frontend-chief-at-loi","description":"As Head of Front-End Engineering at LOi, I led the translation of design specifications and UX prototypes into production-grade, performance-optimized source code. Defined the front-end architectural standards, component abstractions, and rendering strategies across web and mobile platforms. Conducted continuous technical research to evaluate, benchmark, and adopt emerging front-end technologies, build tooling, and optimization techniques.","contributions":["Led a comprehensive front-end modernization initiative, migrating the legacy monolithic HTML/PHP codebase to a component-driven React architecture with state management, code splitting, and lazy loading","Architected and developed the complete front-end layer for the e-commerce platform and cross-platform mobile application across 15+ major release iterations, managing progressive feature rollouts and backward compatibility","Established a unified design system for web and mobile platforms, defining reusable component libraries, theming infrastructure, and interaction patterns to ensure cross-platform visual and behavioral consistency"]},{"title":"Head of Digital Marketing Technology","company":"LOi","country":"Uruguay","startDate":"2012-01-01T03:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/head-of-digital-marketing-technology","description":"As Head of Digital Marketing Technology, I led the technical integration, instrumentation, and analytics infrastructure powering LOi's digital marketing operations. Designed and implemented the data pipelines connecting social media platforms, advertising networks, and marketing automation tools. Established the measurement frameworks and attribution models that enabled data-driven marketing optimization across all digital channels.","contributions":["Implemented end-to-end server-side integration with the Meta Conversions API across both e-commerce and mobile platforms, enabling deterministic event tracking and deduplication for conversion optimization","Engineered a comprehensive product feed integration with Google Merchant Center API, including automated inventory synchronization, dynamic pricing updates, and structured data validation","Deployed and configured Google Analytics 4 (GA4) across all digital properties with custom event taxonomies, enhanced e-commerce measurement, and cross-platform user identity resolution","Integrated Meta Collaborative Ads infrastructure, enabling co-marketing data pipelines with brand partners through privacy-compliant audience matching and performance attribution","Implemented the full Meta Commerce suite including Shops, Catalog Management, and Checkout APIs, enabling native social commerce capabilities with real-time inventory and order synchronization"]},{"title":"DevOps Chief","company":"LOi","country":"Uruguay","startDate":"2012-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/devops-chief-at-loi","description":"As Head of DevOps, I architected and governed the engineering culture, automation practices, and CI/CD infrastructure that enabled LOi to achieve high-velocity, zero-downtime deployments at scale. Defined and enforced the DevOps operating model, integrating continuous integration, continuous delivery, infrastructure-as-code, and observability, to systematically reduce release friction and accelerate time-to-market across all product lines.","contributions":["Designed, implemented, and maintained multi-stage CI/CD pipelines with automated testing, artifact management, and deployment orchestration","Engineered a hardened development and deployment ecosystem with role-based access control and environment isolation","Formalized and enforced code deployment security policies, including branch protection rules, code review gates, and audit trails","Established identity governance policies for credential provisioning, secrets management, and least-privilege access enforcement","Successfully transitioned the organization to a continuous delivery model, reducing release cycles from weeks to hours"]},{"title":"Cloud Systems Administrator","company":"LOi","country":"Uruguay","startDate":"2008-01-01T02:00:00.000Z","endDate":"2023-05-01T03:00:00.000Z","type":"full time job","url":"https://loi.com.uy","detailPage":"https://lucioduran.com/work-experiences/cloud-administrator-at-loi","description":"As Cloud Systems Administrator, I managed, monitored, and continuously optimized LOi's entire cloud infrastructure, balancing computational capacity, storage throughput, and network performance against cost efficiency constraints. Architected scalable, fault-tolerant infrastructure solutions while maintaining observability through custom dashboards and automated alerting. Evaluated and integrated emerging cloud services, engaging directly with service providers and technology partners to ensure alignment with evolving business requirements.","contributions":["Executed a full-scale infrastructure migration to AWS, provisioning multi-AZ deployments with automated failover and disaster recovery capabilities","Achieved maximum cost optimization through reserved instance planning, right-sizing analysis, spot instance strategies, and unused resource elimination","Maximized infrastructure resource utilization by implementing auto-scaling policies, load balancing configurations, and capacity forecasting models","Designed and deployed comprehensive CloudWatch dashboards with granular visibility into compute, storage, network, and application-level metrics","Established 24/7 infrastructure observability through automated monitoring, log aggregation, and anomaly detection pipelines","Engineered custom alerting frameworks with multi-threshold alarms, escalation policies, and real-time notification channels for critical infrastructure metrics and usage patterns"]},{"title":"Website Developer","company":"ACJ Montevideo","country":"Uruguay","startDate":"2006-01-01T02:00:00.000Z","endDate":"2022-03-31T03:00:00.000Z","type":"part time job","url":"https://acj.edu.uy","detailPage":"https://lucioduran.com/work-experiences/website-developer-at-acj","description":"Served as the full-stack web engineer for ACJ Montevideo, architecting and maintaining the organization's entire digital presence. Designed and implemented end-to-end web solutions encompassing front-end interfaces, server-side logic, and database-driven administrative tooling to support institutional operations.","contributions":["Architected and engineered the organization's primary web platform from the ground up, encompassing information architecture, responsive design, and back-end integration","Developed a suite of purpose-built administrative micro-applications to streamline internal organizational workflows","Established and sustained a robust online presence, significantly increasing the organization's digital visibility and stakeholder engagement"]},{"title":"Graphics Designer & Fullstack Developer","company":"College","country":"Uruguay","startDate":"2005-01-01T02:00:00.000Z","endDate":"2011-12-12T03:00:00.000Z","type":"part time job","url":null,"detailPage":"https://lucioduran.com/work-experiences/graphics-designer-and-fullstack-developer-at-college","description":"Served as the principal designer and full-stack engineer at College, responsible for conceptualizing, architecting, and delivering the organization's entire digital ecosystem. Engineered interactive web platforms with both front-end presentation layers and back-end data services, while simultaneously producing original visual content for print and digital distribution channels.","contributions":["Conceived and produced Revista College, one of Uruguay's pioneering rich-media digital publications, combining editorial design, interactive layouts, and multimedia content delivery","Architected Red College, an early-stage social networking platform featuring user profiles, activity feeds, and real-time interaction, predating mainstream social media adoption in the region","Executed full-cycle design, development, and editorial content production for the organization's web presence, from information architecture to copywriting","Engineered College Radio, a forward-thinking audio streaming platform that implemented real-time broadcast delivery over HTTP, well ahead of the industry-wide shift toward web-based media streaming"]},{"title":"CEO & Founder","company":"LDS","country":"Uruguay","startDate":"2005-01-01T03:00:00.000Z","endDate":"2014-01-01T03:00:00.000Z","type":"full time job","url":null,"detailPage":"https://lucioduran.com/work-experiences/ceo-at-lds","description":"Founded and directed LDS, establishing the company's strategic direction, operational infrastructure, and client acquisition methodology. Assumed a hands-on leadership role spanning design execution, full-stack development, client relationship management, and corporate governance. Drove sustained business growth through consultative selling and systematic delivery of technology solutions.","contributions":["Incorporated and bootstrapped the company, defining its market positioning, service offerings, and operational framework","Scaled the client portfolio to over 100 accounts through strategic business development and consultative engagement","Successfully delivered over 300 technology and design projects encompassing web engineering, digital identity systems, and creative production"]},{"title":"CEO & Founder","company":"Sellerista","country":"Uruguay","startDate":"2012-01-01T03:00:00.000Z","endDate":"2014-01-01T03:00:00.000Z","type":"full time job","url":null,"detailPage":"https://lucioduran.com/work-experiences/ceo-at-sellerista","description":"Founded Sellerista as a SaaS e-commerce platform, leading all aspects of product strategy, client acquisition, and technical execution. Directed the company from inception through product-market validation, wearing multiple hats across design, full-stack development, business development, and operational management. Ultimately achieved a successful acquisition outcome.","contributions":["Engineered the complete front-end layer of the multi-tenant e-commerce SaaS platform, implementing theming engines, white-label configuration, and merchant customization capabilities","Developed the entire back-end infrastructure for the e-commerce SaaS, including RESTful APIs, database schema design, authentication systems, and payment gateway integrations","Led the full product lifecycle, from technical architecture and design through development, testing, deployment, and production support, of the complete SaaS platform","Negotiated and executed the strategic acquisition of the SaaS platform by LOi, ensuring successful technology transfer and integration"]},{"title":"CEO & Founder","company":"DIMS","country":"Uruguay","startDate":"1999-01-01T03:00:00.000Z","endDate":"2005-01-01T03:00:00.000Z","type":"full time job","url":null,"detailPage":"https://lucioduran.com/work-experiences/ceo-at-dims","description":"Founded and led DIMS from inception, establishing the strategic vision, operational framework, and client acquisition pipeline. Directed cross-functional initiatives spanning design systems, full-stack development, and stakeholder engagement. Oversaw end-to-end project lifecycle management while cultivating long-term commercial partnerships and driving sustainable revenue growth across the organization.","contributions":["Incorporated and bootstrapped the company, defining its organizational structure, brand identity, and go-to-market strategy","Scaled the client portfolio to over 100 accounts through systematic business development and relationship management","Successfully delivered over 500 technology and design engagements spanning web development, digital branding, and systems architecture"]}]},"skills":[{"name":"AI & Machine Learning Engineering","yearsOfExperience":4,"description":"The design, training, and deployment of machine learning models and AI-driven systems that solve complex business problems at scale. Encompasses supervised and unsupervised learning pipelines, feature engineering, model evaluation frameworks, and the productionization of ML inference, from Amazon SageMaker training jobs and hyperparameter tuning through real-time prediction endpoints and A/B model evaluation in production environments."},{"name":"Agentic AI & LLM Integration","yearsOfExperience":2,"description":"The architecture and implementation of autonomous AI agent systems and large language model integrations into production software. Encompasses prompt engineering, retrieval-augmented generation (RAG) pipelines, tool-use orchestration, multi-agent coordination patterns, context window optimization, and the design of human-in-the-loop guardrails, transforming foundation models from standalone capabilities into composable, reliable components within enterprise-grade application architectures."},{"name":"AI-Driven Personalization Systems","yearsOfExperience":4,"description":"The engineering of real-time, ML-powered personalization engines that dynamically adapt product recommendations, content ranking, and user experiences based on behavioral signals and contextual data. Encompasses collaborative and content-based filtering algorithms, ETL pipeline orchestration (AWS Glue), model training infrastructure (Amazon SageMaker), and real-time inference services (Amazon Personalize), delivering measurable improvements in conversion rates, average order value, and customer lifetime value."},{"name":"AI Product Strategy & AI Agent Optimization","yearsOfExperience":2,"description":"The strategic discipline of designing products, platforms, and digital experiences optimized for consumption by both human users and AI agents. Encompasses interaction patterns for AI agents, structured data exposure for LLM discovery (llms.txt, OpenAPI, Schema.org), AI-readable API architectures, and the systematic optimization of digital assets for machine comprehension, ensuring that products are discoverable, interpretable, and actionable by the emerging ecosystem of autonomous AI agents and foundation models."},{"name":"Product Direction/Ownership","yearsOfExperience":15,"description":"The strategic ownership of product vision, roadmap definition, and backlog governance, translating business objectives and market signals into prioritized engineering requirements. Encompasses stakeholder alignment, sprint planning, velocity forecasting, feature prioritization frameworks (RICE, WSJF), and the continuous calibration of product-market fit through data-driven hypothesis validation and iterative delivery cycles."},{"name":"Team Leadership","yearsOfExperience":8,"description":"The practice of building, mentoring, and directing high-performing cross-functional engineering teams toward aligned strategic outcomes. Encompasses hiring framework design, skill development programs, performance calibration, psychological safety cultivation, and the establishment of engineering culture norms that maximize individual autonomy while ensuring collective velocity and delivery predictability."},{"name":"Conversion Oriented UI Design for E-Commerce","yearsOfExperience":13,"description":"A data-driven approach to interface engineering that optimizes visual hierarchies, interaction affordances, and micro-interaction patterns specifically to maximize conversion funnels in e-commerce environments. Combines cognitive load theory, Fitts's law, and behavioral economics principles to design interfaces where every element is instrumentalized toward measurable commercial outcomes."},{"name":"Technical SEO","yearsOfExperience":15,"description":"The engineering-focused discipline of optimizing website architecture, rendering performance, and structured data implementation to maximize search engine crawlability, indexation efficiency, and ranking signals. Encompasses Core Web Vitals optimization, canonical URL strategies, XML sitemap engineering, Schema.org markup implementation, JavaScript rendering resolution, and the systematic elimination of technical barriers to organic search visibility."},{"name":"Conversion Oriented UX Design & Testing for E-Commerce","yearsOfExperience":13,"description":"An evidence-based design methodology focused on engineering end-to-end user experiences that systematically drive conversion events within e-commerce ecosystems. Integrates user journey mapping, A/B multivariate testing, heatmap analysis, and funnel instrumentation to identify friction points and iteratively optimize task completion rates, cart-to-checkout ratios, and lifetime customer value."},{"name":"Front End Engineering","yearsOfExperience":21,"description":"The architecture and implementation of client-side application layers, encompassing component-driven UI frameworks, state management patterns, rendering optimization strategies, and build pipeline engineering. Spans the full spectrum from semantic HTML and CSS architecture through reactive JavaScript frameworks, code splitting, lazy loading, accessibility compliance, and cross-browser performance profiling."},{"name":"User Experience Design & Testing","yearsOfExperience":21,"description":"The research-driven discipline of designing interaction paradigms and information architectures that optimize usability, accessibility, and user satisfaction across digital products. 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Both validators use the same corpus of three original synthetic documents. The baseline checks only HTML canonical URLs; the full gate verifies the publication against its source. Original output is restored before each case and each mutation is checked for changed bytes. The six fault classes affect canonical URLs, JSON schema versions, Markdown code, HTML tables, missing JSON and an emptied manifest.","interpretation":"These are 18 cases in a fixed matrix, not 18 fault classes or an effectiveness estimate for arbitrary websites. The empty manifest repeats the same global failure three times. This measures correctness, not speed, ranking or the probability that a model cites a source.","tables":[{"id":"comparison","source":"report","columns":["measurement","baseline","gate"],"rows":[["clean","1 / 1","1 / 1"],["detected","3 / 18","18 / 18"],["missed","15 / 18","0 / 18"]]}],"labels":{"comparison":"Control comparison","measurement":"Measurement","baseline":"Canonical URL only","gate":"Full gate","clean":"Clean controls accepted","detected":"Injected faults rejected","missed":"Injected faults missed"}},"limitations":["This is an independent implementation inspired by lucioduran.com requirements. It does not audit or certify the live website.","The corpus supports English documents with literal paragraphs, code blocks, rectangular tables and sections. Images, lists, rich text and multilingual documents are unsupported. This project page is translated.","Exact byte comparison also rejects harmless formatting changes. The verifier and renderer share code: a shared bug may escape the gate.","Markdown tables and HTML anchors depend on reader support. SHA-256 identifies bytes, not authorship or factual truth.","A trusted single-writer filesystem is required. Staging does not provide concurrent deployment exclusion or power-loss durability. Serving content and cache invalidation are outside scope.","The corpus is loaded into memory. Untrusted input needs external size limits; a language declaration is not language detection."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/rag-evaluation-workbench#software","name":"RAG Evaluation Workbench","description":"Reproducible RAG evaluation with BM25, dense and hybrid retrieval, local CPU inference, and separate retrieval and answer metrics.","url":"https://lucioduran.com/projects/rag-evaluation-workbench","codeRepository":"https://github.com/lucioduran/rag-evaluation-workbench","programmingLanguage":"Python","runtimePlatform":"Python 3.11.13","license":"https://github.com/lucioduran/rag-evaluation-workbench/blob/60246831be5cf68768710e83d7b41614e49a8341/LICENSE","version":"60246831be5cf68768710e83d7b41614e49a8341","identifier":{"@type":"PropertyValue","propertyID":"git-commit","value":"60246831be5cf68768710e83d7b41614e49a8341"},"author":{"@type":"Person","@id":"https://lucioduran.com/#person","name":"Lucio 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results from a local Intel Xeon W-3223 run with Python 3.11.13 and four CPU threads. Retrieval metrics use 24 answerable queries; exact match and token F1 use all 26 evaluation queries, including the two unanswerable questions. The 95% intervals use 2,000 bootstrap resamples of source groups. Both questions about a document stay together. Method differences use paired observations with aligned group resampling. There are 12 answerable groups and two unanswerable groups. Tables round values; the reports retain full precision.","interpretation":"All three methods reach Recall@3 = 1 and retain relevant context in the prompt, but none answers every query correctly. Dense gets one more exact-match success than BM25: 20/26 versus 19/26. Its paired difference is 0.038 and the interval [0.000, 0.120] includes zero. This result does not establish a general winner.","tables":[{"id":"retrieval","source":"summary","columns":["method","recall","ci95","ndcg","ci95"],"rows":[["BM25","1.000","[1.000, 1.000]","0.969","[0.923, 1.000]"],["Dense","1.000","[1.000, 1.000]","1.000","[1.000, 1.000]"],["Hybrid","1.000","[1.000, 1.000]","1.000","[1.000, 1.000]"]]},{"id":"answers","source":"summary","columns":["method","exactMatch","ci95","tokenF1","ci95"],"rows":[["BM25","0.731","[0.560, 0.885]","0.756","[0.583, 0.889]"],["Dense","0.769","[0.600, 0.893]","0.795","[0.627, 0.926]"],["Hybrid","0.731","[0.560, 0.885]","0.767","[0.605, 0.899]"]]},{"id":"paired","source":"summary","columns":["comparison","difference","ci95"],"rows":[["dense-bm25","0.038","[0.000, 0.120]"],["hybrid-bm25","0.000","[0.000, 0.000]"]]},{"id":"latency","source":"summary","columns":["method","p50","p95","apiCost"],"rows":[["BM25","93.7","133.4","0"],["Dense","105.9","138.8","0"],["Hybrid","105.9","144.4","0"]]}],"labels":{"retrieval":"Retrieval: 24 answerable queries","answers":"Answers: 26 evaluation queries","paired":"Paired exact-match differences","latency":"Request latency and paid API cost","method":"Method","recall":"Recall@3","ndcg":"NDCG@3","ci95":"95% interval","exactMatch":"Exact match","tokenF1":"Token F1","comparison":"Comparison","difference":"Mean difference","p50":"P50 (ms)","p95":"P95 (ms)","apiCost":"API (USD)","dense-bm25":"Dense minus BM25","hybrid-bm25":"Hybrid minus BM25"}},"limitations":["The small synthetic corpus is easy for retrieval. The split is reserved against parameter tuning but known to its author. This is not an externally blind evaluation or evidence of production generalization.","Exact match and token F1 compare surface forms, not factuality. Frozen aliases can penalize valid paraphrases. Manual analysis does not change the scores.","The small answer model fails abstention on this sample. Perfect recall does not mean correct end-to-end answers.","Intervals are based on few groups. A degenerate interval does not prove certainty beyond the corpus. Latencies describe one local run, not a load test or SLA.","Offline verification checks internal consistency. It does not authenticate measurements, rerun neural inference or independently recount tokenizer tokens. Hardware and backend changes can alter both timing and predictions.","The CLI expects trusted local files and loads inputs and results into memory. It is not an upload service. Code, corpus and results use MIT; downloaded models use Apache-2.0 and are not redistributed in the repository."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/agent-replay-runtime#software","name":"Agent Replay Runtime","description":"Durable tool execution with event replay, idempotency keys and recovery after real process crashes. Includes effect traces and cases that stop instead of retrying automatically.","url":"https://lucioduran.com/projects/agent-replay-runtime","codeRepository":"https://github.com/lucioduran/agent-replay-runtime","programmingLanguage":"Python","runtimePlatform":"Python 3.11.13 / SQLite 3.50.4","license":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/LICENSE","version":"8dbc49ef4b154cc738698714749ad133fa2c6855","identifier":{"@type":"PropertyValue","propertyID":"git-commit","value":"8dbc49ef4b154cc738698714749ad133fa2c6855"},"author":{"@type":"Person","@id":"https://lucioduran.com/#person","name":"Lucio Durán","url":"https://lucioduran.com"},"isAccessibleForFree":true,"citation":["https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/README.md","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/docs/design.md","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/agent_replay/runtime.py","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/agent_replay/ledger.py","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/examples/plan.json","https://raw.githubusercontent.com/lucioduran/agent-replay-runtime/8dbc49ef4b154cc738698714749ad133fa2c6855/results/crash-matrix.json","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/experiments/reproduce.py","https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/experiments/verify.py"],"sources":{"readme":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/README.md","design":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/docs/design.md","runtimeSource":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/agent_replay/runtime.py","ledger":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/agent_replay/ledger.py","plan":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/examples/plan.json","report":"https://raw.githubusercontent.com/lucioduran/agent-replay-runtime/8dbc49ef4b154cc738698714749ad133fa2c6855/results/crash-matrix.json","experiment":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/experiments/reproduce.py","verifier":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/experiments/verify.py","license":"https://github.com/lucioduran/agent-replay-runtime/blob/8dbc49ef4b154cc738698714749ad133fa2c6855/LICENSE"},"publicationPage":{"en":"https://lucioduran.com/projects/agent-replay-runtime","es":"https://lucioduran.com/es/projects/agent-replay-runtime"},"reportedResults":{"crash_cases":6,"idempotent_recovered_without_duplicates":3,"unsafe_blocked":2,"unsafe_reconciled_from_evidence":1,"baseline_effects":2,"uninterruptedEffects":1,"recordedAt":"2026-10-21T21:30:46.249680+00:00","executedRevision":"753a57995f6eb8a89659bed5d06acfd4d167f847","sourceRevision":"8dbc49ef4b154cc738698714749ad133fa2c6855","methodology":"The author’s published report records six fixed crashes: three checkpoints for each adapter type. It also includes an uninterrupted control and a blind-retry baseline. The parent waits for a checkpoint handshake, terminates the child, starts a fresh worker and reads the independent effect store. The local recording used SIGKILL, Python 3.11.13, SQLite 3.50.4 and an Intel Xeon W-3223 with 48 GiB RAM. Workers ran serially.","interpretation":"All three idempotent cases finished with one effect. The non-idempotent case interrupted before the effect remained pending with zero effects: stopping was the expected outcome. This is neither a universal exactly-once guarantee nor a statistical reliability estimate.","tables":[{"id":"recovery","source":"report","columns":["case","effects","outcome"],"rows":[["idempotentRequest","1","sameKey"],["idempotentEffect","1","receipt"],["idempotentAck","1","replayed"],["unsafeRequest","0","unresolved"],["unsafeEffect","1","reconciled"],["unsafeAck","1","replayed"],["blindRetry","2","duplicated"],["control","1","finished"]]}],"labels":{"recovery":"Effects after recovery","case":"Case","effects":"Final effects","outcome":"Outcome","idempotentRequest":"Idempotent: after request","idempotentEffect":"Idempotent: after effect","idempotentAck":"Idempotent: after acknowledgment","unsafeRequest":"Non-idempotent: after request","unsafeEffect":"Non-idempotent: after effect","unsafeAck":"Non-idempotent: after acknowledgment","blindRetry":"Baseline: blind retry","control":"Uninterrupted control","sameKey":"Resumed with the same key","receipt":"Existing receipt recovered","replayed":"Recorded result replayed","unresolved":"Paused, unresolved","reconciled":"Paused, then reconciled with ledger","duplicated":"Duplicate effect","finished":"Completed"}},"limitations":["Deduplication depends on the tool atomically binding key, effect and receipt and retaining that receipt. An idempotent flag does not verify the contract.","Evidence covers local process crashes, not power loss, network partitions, remote providers, expiring receipts or divergent database restores.","Plans are finite and sequential. Model planning, dynamic branching, compensation, backoff and multi-host coordination are outside scope.","A hung tool blocks the writer. History is unbounded and repeated validation can make long runs quadratic. Throughput was not measured.","The hash chain detects accidental changes, not malicious rewriting. Reconciliation records an operator assertion; the runtime cannot verify external truth."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/agent-injection-evals#software","name":"Agent Injection Evals","description":"Reproducible prompt-injection evaluation with a pinned local model, simulated tools and separate metrics for task capability, attack attempts and realized effects.","url":"https://lucioduran.com/projects/agent-injection-evals","codeRepository":"https://github.com/lucioduran/agent-injection-evals","programmingLanguage":"Python","runtimePlatform":"Python 3.11.13 / FLAN-T5-small / CPU","license":"https://github.com/lucioduran/agent-injection-evals/blob/e6d3c2c62154ccfc5a36595ee0ed4e44484c7d66/LICENSE","version":"e6d3c2c62154ccfc5a36595ee0ed4e44484c7d66","identifier":{"@type":"PropertyValue","propertyID":"git-commit","value":"e6d3c2c62154ccfc5a36595ee0ed4e44484c7d66"},"author":{"@type":"Person","@id":"https://lucioduran.com/#person","name":"Lucio 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evaluation report records 120 real CPU generations: six tasks, five variants and four strategies. No strategy completed a clean or hostile task under the frozen metric. The development experiment preserves another 40 generations. The experiment used google/flan-t5-small revision 0fc9ddf78a1e988dac52e2dac162b0ede4fd74ab, seed 1729, greedy decoding, two threads, up to 512 input tokens without truncation and 48 output tokens. The recorded environment is Python 3.11.13, torch 2.2.2, transformers 4.46.3 and an Intel Xeon W-3223 with 48 GiB RAM.","interpretation":"Isolation produced five unauthorized writes. Combined protection attempted the same five writes and policy blocked them. With 0/6 clean-task successes per strategy, there is no useful defense winner and no defined capability-conditioned attack rate: that value is null, not zero.","tables":[{"id":"capability","source":"report","columns":["strategy","clean","hostile","effects","malformed","blocked"],"rows":[["baseline","0 / 6","0 / 24","0 / 24","30 / 30","0"],["isolation","0 / 6","0 / 24","5 / 24","25 / 30","0"],["policy","0 / 6","0 / 24","0 / 24","30 / 30","0"],["combined","0 / 6","0 / 24","0 / 24","25 / 30","5"]]},{"id":"resources","source":"report","columns":["strategy","wall","cpu","tokens","paid"],"rows":[["baseline","7.770 s","14.678 s","3143 / 409","$0"],["isolation","6.092 s","12.118 s","4307 / 322","$0"],["policy","6.909 s","13.723 s","3143 / 409","$0"],["combined","6.162 s","12.035 s","4307 / 322","$0"]]}],"labels":{"capability":"Capability and attack effects","resources":"Evaluation resources","strategy":"Strategy","clean":"Clean success","hostile":"Hostile success","effects":"Effects","malformed":"Malformed","blocked":"Blocked","baseline":"Baseline","isolation":"Isolation","policy":"Policy","combined":"Combined","wall":"Wall time","cpu":"CPU time","tokens":"Input / output tokens","paid":"Paid APIs"}},"limitations":["The small model fails the action protocol and tasks. These results cannot rank defenses for capable production agents.","The synthetic set is small, author-known and shares attack templates across splits. It is neither representative of arbitrary attacks nor an independent blind evaluation.","Each trial has one decision, with no browser, tool feedback, adaptive attacks or real exfiltration.","Isolation is a prompt convention. Policy does not prevent disclosure in answers or through an already authorized destination.","Timings are one observation per case without warmup removal. 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The custom client completed 13 scenarios and each SDK client completed eight. All three negotiated MCP 2025-06-18. The recorded run uses Python 3.11.9 and Node 24.8.0 on an Intel Xeon W-3223. Every client traverses resource and tool pages, reads a note, checks results and errors, submits an invalid cursor and cancels an operation before sending another ping.","interpretation":"These are fixed correctness scenarios for a stdio subset. The 13, 8 and 8 checks do not represent identical coverage or a client ranking. The result certifies neither full MCP conformance nor compatibility with graphical hosts.","tables":[{"id":"interop","source":"report","columns":["client","version","checks","messages","protocol"],"rows":[["raw-reference","0.1.0","13","34","2025-06-18"],["official-python-sdk","2.3.0","8","23","2025-06-18"],["official-typescript-sdk","1.32.1","8","23","2025-06-18"]]}],"labels":{"interop":"Recorded client runs","client":"Client","version":"Version","checks":"Checks","messages":"Messages","protocol":"Protocol","raw-reference":"Custom reference","official-python-sdk":"Official Python SDK","official-typescript-sdk":"Official TypeScript SDK"}},"limitations":["HTTP, OAuth, subscriptions, prompts, sampling, elicitation, progress and resource templates are unsupported. This is not MCP certification.","ChatGPT, Claude Desktop, IDEs and other graphical hosts were not tested. SDK compatibility does not establish compatibility with those hosts.","Cancellation uses a deliberate 400 ms delay and a silence window of at least 600 ms. It does not prove all scheduling races or absence of leaks under load.","Limits are 64 KiB per message, 32 active requests and 10,000 identifiers per session. Performance, backpressure, exhaustive fuzzing and adversarial resource exhaustion were not evaluated.","Tool annotations are descriptive. The actual restriction comes from reading a compiled catalog; there is no security audit or sandbox for arbitrary tools.","Traces and hashes support consistency inspection. They do not authenticate who performed the measurement or constitute independent review."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/llm-serving-bench#software","name":"LLM Serving Bench","description":"CPU inference measured over HTTP/SSE: per-token arrivals, TTFT, TPOT, latency and memory. 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All 48 requests succeeded and generated 1,152 output tokens. Eight warmups are excluded. TTFT includes connection setup, tokenization, queueing and prefill. TPOT divides the first-to-last token interval by the number of generation intervals. Percentiles interpolate six requests per configuration; throughput uses the complete configuration duration.","interpretation":"Two threads produced higher throughput in this sample. Doubling clients mostly added waiting because the server retains one generation slot. Six requests per configuration do not establish an SLA or a general server ranking.","tables":[{"id":"timing","source":"analysis","columns":["configuration","ttft","tpot","latency","throughput"],"rows":[["1 / 64 / 1","0.196","62.92","1.704","14.49"],["1 / 64 / 2","1.871","63.74","3.355","14.35"],["1 / 256 / 1","0.654","72.02","2.415","10.28"],["1 / 256 / 2","3.002","72.84","4.691","10.24"],["2 / 64 / 1","0.128","42.89","1.143","21.50"],["2 / 64 / 2","1.256","43.24","2.460","20.80"],["2 / 256 / 1","0.414","48.94","1.601","15.51"],["2 / 256 / 2","2.041","50.61","3.234","14.93"]]}],"labels":{"timing":"Eight measured configurations","configuration":"Threads / input / concurrency","ttft":"TTFT p50 (s)","tpot":"TPOT p50 (ms)","latency":"Latency p95 (s)","throughput":"Output tokens/s"}},"limitations":["One model, host and fixed execution order. Client and server share CPU resources.","Closed-loop load without continuous batching, GPU, arrival-rate saturation or answer-quality evaluation.","Sampled RSS can miss peaks. Replay checks consistency; it neither measures timings again nor authenticates hardware."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/citation-grounding-checker#software","name":"Citation Grounding Checker","description":"Citation support checking with rules, FLAN-T5 and DeBERTa NLI. 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Precision on the rules’ few answers must be read alongside their coverage.","tables":[{"id":"judgments","source":"report","columns":["method","correct","abstentions","supported","contradicted","insufficient"],"rows":[["deterministic","3 / 36","33 / 36","1.000","1.000","notAvailable"],["FLAN-T5-small","21 / 36","0 / 36","0.500","0.583","0.833"],["DeBERTa NLI","31 / 36","1 / 36","0.923","0.800","1.000"]]}],"labels":{"judgments":"Verdicts on 36 evaluation cases","method":"Method","correct":"Correct","abstentions":"Abstentions","supported":"Support precision","contradicted":"Contradiction precision","insufficient":"Insufficient precision","deterministic":"Rules","notAvailable":"No predictions"}},"limitations":["Small synthetic corpus known to the author; several cases share passages and templates.","Fixed uncalibrated NLI threshold of 0.6. No web retrieval, human validation or production security evaluation.","Timings are individual observations. 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There are 18 development queries and 36 evaluation queries; every index contains the same 18 documents. Complete@3 requires the union of the first three chunks to cover every required evidence span. It does not measure generated answers. Sizes 64 and 96 are word budgets, not model-token budgets.","interpretation":"Structure-96 retrieved complete evidence for 33 of 36 queries. Semantic configurations did so for 12. At 64 words, changing the threshold changes no boundaries because no adjacent block pair fits; this ablation is uninformative about threshold sensitivity.","tables":[{"id":"coverage","source":"summary","columns":["configuration","complete","chunks"],"rows":[["fixed-64","21 / 36","78"],["fixed-96","31 / 36","54"],["structure-64","12 / 36","96"],["structure-96","33 / 36","84"],["semantic-64","12 / 36","96"],["semantic-96","12 / 36","68"],["fixed-64-overlap16","32 / 36","90"],["semantic-64-threshold07","12 / 36","96"]]}],"labels":{"coverage":"Complete evidence on evaluation queries","configuration":"Configuration","complete":"Complete@3","chunks":"Index chunks"}},"limitations":["Synthetic corpus known to the author, with shared templates across partitions and no independent human review.","Atomic-block preservation differs between methods. 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SQLite ingestion includes commit; HNSW does not guarantee crash persistence.","Local closed-loop load without networking. RSS includes the interpreter and traces; three repetitions on one host do not establish a general winner."]},{"@type":"SoftwareSourceCode","@id":"https://lucioduran.com/projects/reranker-budget-router#software","name":"Reranker Budget Router","description":"Reranking router with hard pair budgets, development-fitted policies and a local MiniLM cross-encoder. 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This evaluation does not demonstrate a router advantage.","tables":[{"id":"frontier","source":"report","columns":["policy","ndcg","pairs","mean","p95"],"rows":[["always-12","0.9089","12.00","101.321","126.578"],["never","0.8947","0.00","0.108","0.152"],["router-b12-p0","0.8947","0.00","0.114","0.176"],["router-b12-p0.01","0.8947","0.00","0.112","0.154"],["router-b12-p0.04","0.8947","0.00","0.109","0.139"],["router-b4-p0","0.8947","0.00","0.160","0.201"],["router-b4-p0.01","0.8947","0.00","0.127","0.194"],["router-b4-p0.04","0.8947","0.00","0.116","0.152"]]}],"labels":{"frontier":"Evaluation quality and cost","policy":"Policy","ndcg":"nDCG@3","pairs":"Mean pairs","mean":"Mean (ms)","p95":"p95 (ms)"}},"limitations":["Small synthetic dataset known to the author. Query groups are correlated and relevance has no independent human validation.","The budget limits pairs, not maximum elapsed time. The model cannot recover documents outside its prefix and truncates inputs to 256 tokens.","Three warm repetitions on one CPU do not characterize concurrency, energy, monetary cost or stable production tail percentiles."]}],"architectureDecisions":{"total":20,"description":"Formal Architecture Decision Records documenting the reasoning behind every significant technical decision, with calibrated uncertainty analysis.","reversibility":{"oneWayDoors":["ADR-005","ADR-019"],"twoWayDoors":["ADR-001","ADR-002","ADR-003","ADR-004","ADR-006","ADR-007","ADR-008","ADR-009","ADR-010","ADR-011","ADR-012","ADR-013","ADR-014","ADR-015","ADR-016","ADR-017","ADR-018","ADR-020"]},"decisions":[{"number":"ADR-001","title":"Static Site Generation over Server-Side Rendering","status":"accepted","date":"2024-04-12","reversibility":"two-way-door","url":"https://lucioduran.com/decisions/ssg-over-ssr"},{"number":"ADR-002","title":"MongoDB over PostgreSQL for Content 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