Tida Rask  ·  Founder, Serenso AI

AI-first software
engineer.

Engineering judgment, amplified by AI.

AI helps accelerate implementation, testing, and iteration. My engineering workflow keeps development structured, reviewable, safe, and reliable, while architecture, product decisions, and accountability stay with me.

Alongside Serenso AI, I take on consulting and engineering work.

Tida Rask

The approach

Not just faster.
Further.

AI makes software faster to build.

It doesn't make engineering less important.

My goal is to use AI to build larger, more capable systems without lowering the standard for production software.

/01

Context before code

Every project begins with shared context. AI needs to understand the architecture, conventions, and business domain before it writes code.

/02

Plan before implementation

Major features begin with a written plan. Good implementation starts with clear thinking.

/03

Human architecture

AI can help build software, but I make the decisions about structure, tradeoffs, and what is ready for production.

/04

Guardrails over prompts

Reliable AI development comes from systems, reviews, and constraints. Better prompts help, but they are not enough.

Experience

Built long before AI.

Over fifteen years of engineering judgment, now amplified by a disciplined AI engineering workflow.

2000 – 2004

Database & Web Developer

Finetre Corp. · Herndon, VA

AnnuityNet platform processing $15B in annuity premiums annually for Fidelity, Merrill Lynch, and Legg Mason.

2013 – 2025

Senior Technology Consultant

Avenue80 Incorp. · Fairfax, VA

Enterprise software for biotech, labor management, and data engineering. Supported a $600M company scaling from 12 to 300 employees.

2025 – Today

Founder & Technology Consultant

Serenso AI · Fairfax, VA

Building production software using a disciplined AI engineering workflow.

Education
Johns Hopkins · MBA in MISKing Mongkut's · BS Math & CS
Certs
Azure FundamentalsAzure Data FundamentalsAzure AI FundamentalsAWS Cloud PractitionerIBM Python for AI
AI
ClaudeClaude CodeAzure AIGenerative AI
Languages
C#PythonJavaScriptTypeScriptSQL
Frameworks
DjangoNext.jsReactASP.NET
Cloud
AzureAWS
Databases
SQL ServerPostgreSQLMySQL

By the numbers

The record speaks.

0+years of production engineering
$0Mcompany scaled from 12 to 300 employees
0+AI-assisted production commits
0+workers tracked in a system built with this workflow

Work

Built for business
operations.

The best way to understand how I work is to look at the software itself.

These projects were designed, built, and deployed using the AI engineering workflow described above. They are in daily use, solving operational problems for the organizations that depend on them.

How I work

Engineering with AI.

Engineering judgment is still the foundation. AI changes how I build software, not how I think about software.

Building production software with AI is about more than writing better prompts. My workflow keeps AI productive while preserving the planning, review, testing, safety, and judgment that reliable systems require.

01

Plan before implementation

Major features begin with a written design. The implementation follows an agreed plan instead of being improvised one prompt at a time.

02

Persistent context

Each project maintains living documentation so AI understands the architecture, conventions, and business domain across development sessions.

03

Safety guardrails

AI works inside clear boundaries. Sensitive files, destructive commands, and risky changes are protected by rules and checks before they can affect the system.

04

Specialized AI reviewers

Different AI reviewers focus on architecture, security, localization, testing, and project-specific rules before changes are accepted.

05

Automated validation

Regression tests and production scenarios help verify that changes improve the system instead of quietly breaking existing behavior.

06

Human engineering judgment

AI accelerates implementation. Architecture, tradeoffs, and final decisions remain my responsibility.

Working together

What clients get.

Engineering judgment

More than fifteen years of production software experience shape how I design, review, and deliver systems.

Business understanding

I translate operational problems into software that teams can actually use.

An AI engineering workflow

AI helps me move faster. A disciplined engineering workflow keeps the work structured, reviewable, safe, and reliable for production.

"Tida stays engaged throughout and is genuinely eager to talk to everyone involved, especially the people who will use the system every day. The system she built is fully integrated into how SPT operates. It handles almost every aspect of our operations, supports our ISO audits, and has been running for over two years with new features still being added. Our clients are impressed when they see it, and it makes closing deals easier."

Kukwut LapteerawutManaging Director, SPT Consulting & Service Co., Ltd.

Contact

Interested in building something together?

If you’re building software, improving operations, or adopting AI responsibly, get in touch.