Tech Stack
Tools & Technology
A deliberately curated set of tools that amplify output across finance, legal practice, and software development.
Tools in Stack
Software Tracks
AI Tools
Years Building
AI tools that multiply output
These aren’t experimental toys—they’re production infrastructure. Each AI tool is deeply integrated into the daily workflow, handling everything from code generation to legal research synthesis.
Vercel V0
UI Generation & Prototyping
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GitHub Copilot
AI Pair Programmer
Google Gemini
Multimodal Reasoning Assistant
Anthropic
Safety-First Reasoning & Deep Analysis
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xAI Grok
Real-Time Insight Assistant
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OpenAI
General-Purpose Frontier Assistant
VS Code IDE
AI-Native Code Editor
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NotebookLM
AI Research & Knowledge Synthesis
Dia
AI Browser & Ambient Assistant
Perplexity
AI-Powered Search & Agentic Browser
Google AI Studio
AI Discovery & Prototyping
Explore frameworks, protocols, and AI-native infrastructure
Embeddings and vector search shape retrieval, MCP and agent protocols structure tool use, TanStack sharpens application state, orchestration frameworks coordinate AI flows, UI primitives keep interfaces precise, and edge runtimes carry the whole system closer to the user.
6 ecosystems • 30 technologies
Radar Logic
Rings show practical maturity. Inner rings indicate tools already shaping real product decisions; outer rings mark active exploration and emerging bets.
Quadrants
Pipelines, not isolated tools
The real power of a tech stack is not in individual tools but in how they flow together. These three pipelines show how information moves from raw input to polished output.
Prompt-to-Production Pipeline
From natural language prompt to deployed application in a single workflow. v0 generates UI, Copilot fills implementation gaps, Vercel handles deployment.
Research-to-Insight Engine
Legal and financial research starts with Perplexity surfacing the latest sources, NotebookLM grounding synthesis in uploaded documents, then flows through Bloomberg and LexisNexis for validation before producing actionable insight reports.
Data-to-Decision Framework
Raw data enters through SQL queries, undergoes statistical analysis in Python or R, and surfaces as interactive visualisations in Next.js dashboards.
AI Discovery Pipeline
From open question to cited brief in a single session. Perplexity surfaces the landscape with real-time citations, NotebookLM grounds the analysis in your uploaded corpus, and Dia provides ambient context as you browse — producing structured, source-verified briefs.
The complete stack at a glance
Every tool, framework, and technology actively used across frontend, backend, data, and professional domains. Dot colour indicates proficiency: accent = high, dimmed = foundational.
Skill depth across domains
Proficiency measured by frequency of professional use, depth of domain knowledge, and ability to produce production-ready output.
Core programming languages and frameworks for building robust applications.
Data analysis, automation, financial modelling
Web applications, dashboards, tooling
Financial databases, reporting queries
Statistical analysis, portfolio modelling
Principles behind the stack
Tools are only as good as the principles guiding their selection and use. These four pillars define how technology choices are evaluated, adopted, and integrated into professional practice.
Context-First Development
Every tool is chosen for its contextual fit, not its popularity. The right abstraction at the right layer reduces friction and compounds productivity over time.
AI as Infrastructure
AI tools are not novelty features but foundational infrastructure integrated at every stage of the workflow, from research to deployment.
Data-Driven Decisions
Professional expertise is amplified by data, not replaced by it. Quantitative tools provide the evidence base for qualitative judgment calls.
Security & Compliance by Default
In finance and law, security is not optional. Every tool selection considers data handling, access controls, and regulatory compliance from day one.
Technology does not replace expertise — it reveals how much more is possible when expertise is properly amplified.
Every hour saved on routine work is an hour reinvested in judgment.
— AVW