/faq

Tell me about yourself

I'm a senior full-stack engineer with a strong systems mindset and a focus on how things behave in the real world.

I learn by understanding how systems behave in the real world — how data flows, how state changes, and where assumptions break down. Rather than relying on memorisation of documentation or specific frameworks, I focus on first principles and context, which allows me to adapt quickly as tools, requirements, or constraints change.

I specialise in taking complex or fragile setups and shaping them into systems that are reliable, understandable, and resilient in day-to-day use. I work end-to-end, take ownership of outcomes, and care deeply about how things behave once they're live.

How do you learn and retain things?

By reasoning through real scenarios.

I learn best when I can observe a system directly — tracing behaviour, debugging failures, and seeing how it responds to change or load. This builds a mental model of how things actually work, not just how they're described.

Once I understand that model, the knowledge transfers easily across languages, frameworks, and architectures. The specifics may change, but the underlying principles remain the same.

What are you best at?

I tend to do my best work when I'm given space to understand a system properly and improve it thoughtfully.

• Understanding complex systems quickly
• Identifying hidden assumptions and edge cases
• Debugging issues that don't have obvious causes
• Choosing appropriate tools based on constraints, not trends
• Designing systems that remain stable as they evolve
• Reducing operational and cognitive overhead for teams

I'm particularly effective in environments where clarity matters more than flash.

How do you approach problem-solving?

I start by building a clear mental model of the system:

• what goes in
• what state exists
• how that state changes over time
• where uncertainty or failure can occur

Once that model is solid, decisions become much easier. This lets me move between technologies confidently, because I'm reasoning about behaviour and trade-offs rather than surface-level syntax.

What's your core tech stack?

I'm not attached to tools. I'm attached to systems that work.

How do you use AI in production?

Carefully and intentionally.

I use AI where it removes manual work, helps with classification or retrieval, and supports humans instead of replacing judgment. That usually means RAG instead of free-form generation, with clear boundaries, fallbacks, and observable behaviour.

Most real systems work better with deterministic flows, explicit state, and AI used in narrow, well-defined steps. When I do build agent-like behaviour, it's interruptible, observable, scoped to a real task, and designed to fail safely.

If I can't explain what it's doing clearly, it doesn't ship.

How do you approach backend architecture?

I favour simple, deliberate designs with clear ownership and predictable behaviour.

Rather than optimising for novelty or theoretical elegance, I aim for systems that feel dependable in practice and are:

• easy to reason about
• difficult to misuse
• understandable by someone new to the codebase

If a system only makes sense after a long explanation, it's usually carrying unnecessary complexity.

Monoliths or microservices?

Monoliths by default.

I've seen too many teams add complexity before they have a real scaling problem. A well-structured monolith is usually faster to ship, easier to debug, and cheaper to run.

I reach for microservices only when reality forces the decision.

How do you test your work?

I test the parts that are expensive to get wrong.

That usually means:

• core logic
• system boundaries
• anything that's painful to debug in production

I care more about confidence than coverage percentages.

How do you handle legacy systems?

With respect.

Legacy systems usually exist because they once solved a real problem. I try to understand why before changing anything.

I prefer:

• isolating risk
• improving things incrementally
• leaving systems better than I found them

How do you work day-to-day?

I work in tight feedback loops:

• understand the real problem
• observe how the system actually behaves
• make the smallest change that meaningfully improves it
• ship
• learn from reality

I optimise for momentum and clarity, not perfection.

What does success look like in your first 30 days?

• I understand the system well enough to debug it confidently
• I've shipped at least one meaningful improvement
• I've identified risks others have learned to live with
• I'm trusted to work independently

What roles are you looking for?

• Backend-heavy or full-stack roles
• Teams shipping real products
• Environments where engineers own outcomes
• Permanent roles or long-term contracts
• Remote-first preferred

What kind of work do you avoid?

• Roles with no ownership
• AI work that exists only for demos or pitches
• Over-engineered systems without users
• Teams where production is rare or political

What motivates you?

• Solving real problems
• Debugging hard things
• Removing unnecessary complexity
• Shipping systems people rely on

I get energy from making things work properly.

Why should someone hire you?

Because I bring calm, clarity, and depth to complex problems.

I think carefully before acting, adapt quickly when circumstances change, and stay steady under pressure. I focus on building systems that hold up over time. I'm comfortable working independently, collaborating closely with others, and taking responsibility for outcomes.

I don't optimise for show — I optimise for systems that work reliably in the real world.

What's your availability?

Open to the right permanent role or long-term contract.
Not interested in short, low-ownership engagements.

What's your rate or salary range?

Shared privately once there's alignment on expectations and scope.
If price is the first conversation, we're probably not a fit.

Final note

If you value engineers who learn through reality, debug deeply, and ship systems that survive contact with users, we'll work well together.

How do I contact you?

Email: jake@nought.digital