# Dome Space — Technical Strategy & Modernization Consulting > Senior technical consulting for organizations modernizing systems, integrating AI thoughtfully, and making architectural choices that benefit from experience. Software evolves. So should the way you think about it — with help from someone who's seen the last few cycles. Dome Space is a boutique technical consulting practice founded by Aleda Jonquil, a senior software engineer with 27 years of professional experience and 17 years at the senior level. Based in Northfield, MA (western Massachusetts). ## Services ### Legacy System Modernization Your system has value — it runs your business. The question is how to evolve it safely. I map what you have, find the best sequence for change, and build a phased plan that protects what's working while making room for what's next. Focus areas: Architecture review, systems assessment, technical debt, migration planning. ### Fractional CTO & Technical Leadership Some organizations need a CTO five hours a week, not forty. I'm there for the architecture calls, the hiring decisions, the AI questions that keep coming up, and the conversations where someone needs to say "here's what I'd actually do" — then I step back until the next one. The arrangement scales to fit the company, not the other way around. Focus areas: Strategic oversight, architecture decisions, team mentorship, vendor evaluation, specialist coordination. ### AI Integration, Done Thoughtfully I've worked on production AI integrations across more than a decade — IBM Watson NLU for classification, AutoAI for ranking, the Claude API for lead pre-processing, and contributed to voice AI for an answering service. I've also retired AI services when they stopped earning their place. The goal is practical efficiency — real workflows that save your team real time — and I'll be honest about where AI fits your situation and where it doesn't. Focus areas: Workflow automation, LLM integration, ML model training, operational tooling. ### Cloud & Serverless Architecture Over a decade of production AWS — Lambda, DynamoDB, API Gateway, and more — has taught me to design serverless systems that stay clean and maintainable as they scale. The best architecture is the one that still makes sense in three years, at ten times the traffic. Focus areas: AWS serverless, API design, infrastructure review, scalability planning. ## Approach I like to understand a system before I suggest changing it. Good technical decisions come from clarity — about what you have, where you're headed, and what's actually involved in getting there. That clarity doesn't appear on its own. It takes a deliberate first step. Every engagement begins with a **paid discovery phase**: a structured assessment that produces a real deliverable — your architecture mapped, your priorities organized, and a phased roadmap you own outright. That document is useful whether or not we continue working together, and it's the most grounded way to start. After discovery, we work in phases. Each one has a clear deliverable and a natural stopping point — you continue because the work is proving its value, not because you're locked in. ### Principles - **Assess before acting.** Every system has a story its documentation doesn't fully tell. The assessment brings the real picture into focus. - **Stabilize, then modernize.** Strengthen what's running today first. A stable foundation gives you the confidence to evolve at whatever pace makes sense. - **Phased, transparent delivery.** Each phase stands on its own. You always know what you've received, what it's worth, and what comes next if you choose to continue. - **Plain language, always.** Communication isn't a soft skill. It's an integral part of technical work. If I can't explain a recommendation in terms a non-technical stakeholder can act on, I haven't finished thinking it through. ## Engagements Structured for clarity, not billable hours. Engagements are shaped around the work, not a clock. Discovery comes first — it's the most grounded way to begin, and it produces a deliverable that's valuable even if we don't work together further. ### System Assessment & Roadmap (Fixed fee) The ideal starting point. A structured review of your systems, priorities, and architecture — with a concrete modernization roadmap as the deliverable. - Architecture and codebase review - Risk and technical debt assessment - Operational bottleneck analysis - AI integration opportunities - Phased modernization roadmap _Scope depends on system complexity, number of integrations reviewed, and audit depth._ ### Fractional CTO Retainer (Advisory) Ongoing technical leadership calibrated to your situation — from monthly strategy and async support on the lighter end, to weekly hands-on architecture involvement at the deeper end. Engagements begin with a 90-day commitment. - Architecture oversight and decision support - Team mentorship and code review - Vendor and technology evaluation - AI and modernization guidance - Priority response within one business day _Engagement depth is scoped to your situation during discovery._ ## About Twenty-seven years of building software — and learning what makes it last. I wrote my first production code in 1999, for an ad agency that wanted to push the boundaries of what the web could do. I've been a senior engineer for seventeen of the twenty-seven years since. I've shipped games, dynamic websites, content management tools, reporting systems, hybrid mobile apps, serverless platforms, and most recently, AI-driven systems. Each generation of languages & technology arrived promising to make the previous one obsolete, and each one quietly turned into infrastructure the next generation built upon. In my time I've watched paradigms come and go — and I've helped the systems that had to survive each transition. For most of the past seventeen years, I've done that work at a single company that was built around a website I developed as a contractor with the marketing agency Wheelhouse Strategy — a site that produced a roughly sevenfold business surge for their client in the month after launch, prompting the site owner to launch a company around the model. The work that began as a single site became the company; the company became the platform; the platform produced **Sherloq**, an AI-driven serverless analytics app on AWS that earned IBM Partner status and was featured as an [IBM case study](https://www.ibm.com/case-studies/sherloq). Along the way I helped integrate several different production AI services — IBM Watson NLU, IBM AutoAI, the Claude API, and contributed to a Vapi voice AI for after-hours call intake — and acquired the discernment to know when to retire an AI service that has stopped earning its place. I've also learned, across many years, that a meaningful share of senior technical work isn't technical — it's noticing the structural friction a team has been working around, and solving those bottlenecks. The product specs that didn't exist. The handoff plan between departments. The meeting notes nobody was taking. The technical voice in client meetings, translating engineering decisions clearly, without condescension. My job is to tell you what I'd do, and why. If I think a direction is going to cause real harm, I'll say that clearly, once, in writing. After that, my job is to help you execute the path you've chosen as well as it can be executed — not to keep relitigating the decision. Before all of this, I studied the arts — music, film, photography, and martial arts. It may seem unrelated, but it turned out to be the part of my training that taught me to pay attention and listen, to communicate effectively, and to prefer elegant solutions over elaborate ones. I work from a geodesic dome in a forest, on a mountain, in western Massachusetts. It's an expansive, creative, and quiet space. It turns out, that makes a difference. ### Experience highlights Since 1999. - Twenty-seven years in production software, seventeen at senior level - Eleven years co-leading an IBM Partner AI platform - Shipped production AI services, and retired the ones that stopped earning their place ### Core technologies AWS / Serverless, Node.js / TypeScript, React / Angular / Nest.js, LLM Integration, ML model training, DynamoDB / PostgreSQL / MySQL, DevOps, Technical documentation. ## Selected Work Software that has to keep running. Most of what I do well, I learned by doing it for a long time on systems that had to keep running. Here's the work that shaped how I think. ### Sherloq — AI-enabled analytics platform Co-led architecture and development from 2015 onward. The work earned IBM Partner status and was featured as an [IBM case study](https://www.ibm.com/case-studies/sherloq). **Stack:** Serverless AWS (Lambda, DynamoDB, API Gateway, Cognito, IBM Blockchain), Node.js / TypeScript, React. **Production AI integrations:** - **IBM Watson NLU** — lead classification (in production) - **Claude API** — incoming lead pre-processing (in production) - **IBM AutoAI** — ad ranking (retired) **Modernization approach:** risk first, then end-of-life dependencies, then frequency of use. Stable surfaces stay stable. Everything else has to earn the change. ### Voice AI for answering service Contributed to a Vapi-based voice AI system that handles calls for businesses. Still in production. ## Contact The first conversation is free and genuinely no-pressure — really just a chance to understand your situation and see whether what I do is what you actually need. If it is, I'll propose a discovery engagement with clear scope and a fixed fee. If it isn't, I'll tell you that, and I'll point you somewhere useful, if I can. - **Email**: Aleda Jonquil — [aleda@domespace.dev](mailto:aleda@domespace.dev) - **Phone**: [+1 (413) 834-5503](tel:+14138345503) - **Location**: Northfield, MA, US - **Website**: https://domespace.dev