dinoudon

AI/LLM engineering: LLMOps, prompt engineering, model integration, AI safety, production AI systems.

Data engineering: pipelines, data quality, data mesh, data lakehouse, ETL/ELT, streaming architecture.

DevSecOps: supply chain security, SBOMs, policy-as-code, zero-trust, security automation.

Green software engineering: sustainability, carbon-aware computing, energy-efficient architecture, eco-friendly development.

AI/LLM engineering: LLMOps, prompt engineering, model integration, AI safety, production AI systems.

Data engineering: pipelines, data quality, data mesh, data lakehouse, ETL/ELT, streaming architecture.

DevSecOps: supply chain security, SBOMs, policy-as-code, zero-trust, security automation.

Green software engineering: sustainability, carbon-aware computing, energy-efficient architecture, eco-friendly development.

Comprehensive competitor analysis and market research. Includes competitive intelligence gathering, SWOT analysis, feature comparison, pricing analysis, and positioning strategy.

Email marketing campaigns with drip sequences, segmentation, automation, and conversion optimization. Includes welcome series, nurture campaigns, re-engagement, and analytics.

Design and optimize conversion funnels for SaaS, e-commerce, and lead generation. Includes funnel mapping, conversion rate optimization (CRO), A/B testing strategy, and analytics setup.

Go-to-market strategy planning for product launches. Includes market segmentation, positioning, pricing strategy, channel selection, launch planning, and growth tactics.

Generate investor-ready pitch decks with proven frameworks (Sequoia, Y Combinator, Airbnb). Includes slide structure, content templates, design guidelines, and storytelling principles for seed to Series A fundraising.

Technical SEO, content strategy, and link building for organic traffic growth. Includes on-page optimization, keyword research, site architecture, Core Web Vitals, and ranking strategies.

Create comprehensive architecture blueprints with C4 diagrams, ADRs (Architecture Decision Records), technology radar, dependency graphs, and deployment topology. Document architectural decisions before implementation.

Measure and improve code quality with cyclomatic complexity, test coverage, code churn, maintainability index, and technical debt tracking. Data-driven quality improvement.