Tida Rask · Founder, Serenso AI
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.

The approach
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.
Every project begins with shared context. AI needs to understand the architecture, conventions, and business domain before it writes code.
Major features begin with a written plan. Good implementation starts with clear thinking.
AI can help build software, but I make the decisions about structure, tradeoffs, and what is ready for production.
Reliable AI development comes from systems, reviews, and constraints. Better prompts help, but they are not enough.
Experience
Over fifteen years of engineering judgment, now amplified by a disciplined AI engineering workflow.
AnnuityNet platform processing $15B in annuity premiums annually for Fidelity, Merrill Lynch, and Legg Mason.
Enterprise software for biotech, labor management, and data engineering. Supported a $600M company scaling from 12 to 300 employees.
Building production software using a disciplined AI engineering workflow.
By the numbers
Work
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 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.
Major features begin with a written design. The implementation follows an agreed plan instead of being improvised one prompt at a time.
Each project maintains living documentation so AI understands the architecture, conventions, and business domain across development sessions.
AI works inside clear boundaries. Sensitive files, destructive commands, and risky changes are protected by rules and checks before they can affect the system.
Different AI reviewers focus on architecture, security, localization, testing, and project-specific rules before changes are accepted.
Regression tests and production scenarios help verify that changes improve the system instead of quietly breaking existing behavior.
AI accelerates implementation. Architecture, tradeoffs, and final decisions remain my responsibility.
Working together
More than fifteen years of production software experience shape how I design, review, and deliver systems.
I translate operational problems into software that teams can actually use.
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."
Contact
If you’re building software, improving operations, or adopting AI responsibly, get in touch.