Mostafa Sakhiri · Frontend Software EngineerEngineering Impact
“Every engineering decision should make the next feature easier to build.”
More than 8 years designing engineering systems that continuously increase a team's ability to build software.
By reducing complexity through scalable architecture, reusable foundations and developer experience, I help engineering teams build products that become easier to evolve with every release.
How I think about building software
I believe engineering is not about shipping individual features. It is about continuously increasing an organization's ability to build software.
Systems over features
I optimize for the system that produces features, not the feature itself. A well-designed system makes every future feature cheaper to build than the last.
Reduce complexity over time
Complexity compounds silently until it stalls a team. Every architectural decision should leave the codebase easier to reason about than it found it.
Build reusable foundations
Shared abstractions, once built well, pay for themselves on every feature that follows. I invest in foundations before I invest in one-off implementations.
Developer Experience compounds over time
A faster feedback loop today becomes faster delivery for years. DX is not a nice-to-have — it's a multiplier on everything the team ships afterward.
Performance should be built into the platform
Performance should be a property of the platform, not a follow-up optimization pass. When it's inherited by default, every new feature starts fast.
AI should augment engineering, not replace it
Coding agents are only as good as the context and guardrails around them. I design the workflows, documentation and review processes that let AI raise a team's throughput without lowering its bar.
Every architectural decision is a business decision
Architecture shapes delivery speed, maintenance cost and how long a platform stays adaptable. I make those trade-offs explicit to the business, not just the codebase.
Four contributions that changed how a team builds software
Each one reduced the cost of building the next feature — not just this one.
Accelerating Engineering Delivery
Tripled frontend engineering throughput by designing and deploying an AI-assisted development system enabling developers and coding agents to collaborate efficiently while maintaining high engineering quality.
- Selected by engineering leadership to lead a three-month initiative dedicated to improving engineering productivity through AI.
- Introduced Claude Code and standardized AI-assisted engineering workflows across the frontend team.
- Built reusable engineering documentation, Context Engineering practices and reusable AI skills to provide coding agents with the necessary project knowledge.
- Automated technical and functional Pull Request reviews before human review to reduce QA feedback and improve delivery quality.
Scaling Frontend Delivery
Reduced implementation time for new product pages by 50–70% by transforming the Design System into an engineering platform powering nearly 80% of the new React application.
- Owned the Design System used by a frontend team of 5–8 engineers.
- Designed a reusable DataGrid integrating data fetching, virtualization, deferred rendering and common business interactions.
- Embedded accessibility, UX consistency and performance directly into reusable engineering foundations.
- Standardized reusable abstractions shared across multiple applications and libraries.
Making Performance the Default
Reduced Largest Contentful Paint by three times on the platform's most frequently used pages by embedding performance optimizations directly into reusable frontend foundations.
- Integrated virtualization, lazy rendering and intelligent data loading into shared platform components.
- Eliminated unnecessary rendering and redundant network requests across complex user interfaces.
- Investigated production incidents and delivered targeted hotfixes to continuously improve platform stability.
Evolving the Frontend Architecture
Helped evolve Concord's frontend platform from a legacy Ember application toward a scalable React architecture designed for long-term maintainability.
- Participated in the migration from Ember.js to React.
- Designed modular architecture and reusable abstractions supporting long-term evolution.
- Reduced technical debt through continuous architectural improvements.
- Collaborated with Product, Design and Engineering teams to guide technical decisions.
Building an AI-Native Product Experience
Designed and shipped a conversational AI layer inside the platform that lets users fetch exactly the data they need, create new resources, and chat directly with an individual resource such as a contract — replacing multi-step forms and dashboard navigation with natural language.
- Built natural-language data retrieval so users can ask for the exact record or data point they need instead of hunting through dashboards and filters.
- Designed a conversational resource-creation flow, letting users generate structured resources like contracts through dialogue instead of long-form UI.
- Implemented resource-scoped chat, letting users open a specific record and ask grounded questions about its actual content rather than generic AI answers.
- Combined tool-calling and structured data access to keep every response grounded in the platform's real data — the same grounding-over-hallucination discipline behind this portfolio's own assistant.
The models behind my engineering decisions
Systems compound. Features don't.
A one-off feature solves one problem. A system solves the next ten. Systems thinking is slower in week one and faster than the alternative by week eight — and the gap keeps widening.
Developer Experience is a flywheel, not a checkbox.
Better tooling reduces friction. Less friction increases the rate of shipping. More shipping surfaces the next tooling gap sooner. I invest here first because it accelerates everything built after it.
AI multiplies engineering judgment. It doesn't replace it.
The teams that get the most from AI-assisted development have the clearest context, the strongest guardrails and the highest existing engineering bar. AI amplified throughput 3× because the review process, documentation and skills around it were built first.
Tripling Engineering Throughput through AI-Assisted Engineering
Why I was trusted to lead a three-month initiative that tripled how fast the frontend team could ship — and how AI became a reliable part of the engineering workflow, not a shortcut around it.
Read the full storyThe tools behind the systems
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Most Engineering Decisions Aren't About Technology
A framework for reasoning about trade-offs, architecture and impact — the eight principles behind every technical decision I make, and why the technology is rarely the interesting part.