01
Technical expertise
Code quality, architecture, APIs, frontend systems, testing, debugging, and maintainability.
10+ years in software development, now combined with end-to-end software project management.
Technical expertise, planning and coordination to turn business needs into executable software.
Experience first
AngeliniLabs grows out of real software work: frontend and full-stack development, architecture and integrations, maintainability, technical debt, feature implementation, team collaboration, Agile projects, and increasingly broader project responsibility.
01
Code quality, architecture, APIs, frontend systems, testing, debugging, and maintainability.
02
Scope, priorities, planning, dependencies, risks, stakeholder needs, team coordination, and preparation for release.
03
AI as an accelerator for selected work, not as a substitute for technical judgment, review, or responsibility.
Professional focus
I can work across the full project lifecycle — from analysis and technical planning to coordination, implementation support, progress monitoring, and release — while remaining close enough to the code to make grounded decisions.
01
Hands-on frontend and full-stack development with TypeScript, React, Angular, APIs, testing, debugging, and maintainable implementation practices.
02
Requirements and scope, roadmap, estimates, priorities, dependencies, risks, team and vendor coordination, progress monitoring, and support through release.
03
TCAF provides a public way to delegate selected software tasks to AI within explicit boundaries, with human review and clear verification.
Public work
TCAF documents a controlled approach to AI-assisted development. Software Delivery Planner makes project planning and engineering decisions visible, while Travel AI Flight Optimizer shows end-to-end product work with live providers, deterministic logic, research, and reporting.
Public beta · v0.3.3
A framework for using different AI tools in professional software development without giving them control of the project. Task Contracts define what may change, working code is preserved where possible, verification is explicit, and developer review remains required.
Public project · work in progress
A React, TypeScript, and Fastify portfolio application for planning and monitoring a software project. The repository includes working project and feature flows, shared contracts, automated tests, OpenAPI documentation, architecture notes, and a documented backlog.
Public project · MVP complete
A local-first React and TypeScript travel-planning application combining live flight discovery through Kiwi MCP, deterministic shortlist ranking, home-to-airport transport planning, source-backed destination research, and standalone HTML reports.
TCAF method
Repeated use of AI in software development exposed recurring problems: scope expansion, unnecessary rewrites, lost context, and expensive debugging. TCAF grew from the need to keep the useful acceleration while making changes easier to understand, review, and verify.
Notes
A growing collection on maintainability, technical coordination, Agile work, project risk, and the practical use of AI in software development.
Note 01
AI can accelerate individual developers, but it becomes useful to project planning only when its effect on review, rework, verification, and cycle time is observable enough to learn from.
Note 02
Why maintainability, debugging effort, onboarding friction, and code quality affect cost, development speed, reliability, and continuity.
Contact
I am available for selected project-based, fractional, contract, or role-based opportunities involving Technical Project Management, technical planning, software development, assessments, and controlled AI-assisted development.