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Robots and Pencils Software Engineer Interview Guide

Robots and Pencils Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Robots and Pencils, a Software Engineer plays a pivotal role in bridging the gap between humanities and science—the "pencils" (creative design and user experience) and the "robots" (robust technology and engineering). You will not just write code; you will design, build, and scale digital products that solve complex business problems for a diverse range of clients. From sleek consumer-facing mobile and web applications to complex enterprise-grade platforms, your work directly shapes how users interact with technology. This role is highly collaborative and consultative. You will work alongside talent-dense teams of designers, product managers, and fellow developers to translate creative concepts into high-performing, clean, and maintainable software.

This guide is scoped to a Software Engineer candidate at Robots and Pencils.

Focus areas

  • React
  • Code Review
  • Software Engineering (Role Fundamentals)

The Robots and Pencils interview process

Robots and Pencils candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Contact

The process begins with initial contact to discuss the role and gauge interest.

What to demonstrate

  • The process begins with initial contact to discuss the role and gauge interest
  • Depth in React

How to prepare

  • Answer aloud and timed: How do you approach selecting the right technology stack for a greenfield web application?
  • Answer aloud and timed: Can you explain the differences between various state management patterns in modern frontend frameworks like ReactJS?

Collaborative Interviews

Candidates participate in multiple interviews with at least two team members to assess fit.

What to demonstrate

  • Candidates participate in multiple interviews with at least two team members to assess fit
  • Depth in React

How to prepare

  • Answer aloud and timed: How do you ensure your CSS/HTML implementation is both responsive and highly performant across different devices?
  • Answer aloud and timed: What design patterns do you rely on to keep a codebase clean, modular, and easy to maintain as a project scales?

Technical Deep-Dives

Engage in conversational technical discussions focusing on architecture and code analysis.

What to demonstrate

  • Engage in conversational technical discussions focusing on architecture and code analysis
  • Depth in React

How to prepare

  • Answer aloud and timed: Walk me through this block of code. What potential performance bottlenecks or security vulnerabilities do you see?
  • Answer aloud and timed: How would you refactor this component to make it more reusable and testable?

Final Decision

The team collaborates to make a final decision based on the interviews and assessments.

What to demonstrate

  • The team collaborates to make a final decision based on the interviews and assessments
  • Depth in React

How to prepare

  • Answer aloud and timed: What is your process for conducting a constructive and thorough code review for a peer?
  • Answer aloud and timed: Describe a time when you had to work with a designer whose creative vision clashed with technical or performance constraints. How did you resolve it?

Where candidates lose points

Highlight your cross-functional experience

Be ready to talk about how you work with designers, product managers, and clients. Robots and Pencils prides itself on the intersection of design and technology, so showcasing your ability to collaborate across disciplines is a major differentiator.

Master the "Why" behind your technical choices

During architectural discussions, don't just state what technologies you use. Explain why you chose them, what trade-offs you considered, and how those decisions benefited the project or client.

Brush up on your code review skills

Since you may be asked to review code during the technical round, practice reading other developers' code and identifying areas for improvement regarding performance, security, accessibility, and readability.

Be proactive about follow-ups

Some candidates have experienced communication gaps when project pipelines shift unexpectedly. Keep in close contact with your recruiter to ensure your status remains clear.

Questions & practice

Walk me through this block of code. What potential performance bottlenecks or security vulnerabilities do you

Medium · Code Comprehension & Review

Walk me through this block of code. What potential performance bottlenecks or security vulnerabilities do you see?

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

  1. Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
  2. Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
  3. Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
  4. Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

  • The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
  • The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

Track a rolling failure rate per destination for circuit decisions

Easy · sliding window · ring buffer · circuit breaker

The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.

Approach

  1. Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
  2. Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
  3. State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
  4. Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.

Follow-up

  • The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
  • A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

  1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
  2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
  3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
  4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

  • A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
  • The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.

Approach

  1. Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
  2. Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
  3. Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
  4. Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.

Follow-up

  • The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
  • Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?

How do you approach selecting the right technology stack for a greenfield web application?

Medium · Application Design & Tech Stack

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Can you explain the differences between various state management patterns in modern frontend frameworks like R

Medium · Application Design & Tech Stack

Can you explain the differences between various state management patterns in modern frontend frameworks like ReactJS?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

How do you ensure your CSS/HTML implementation is both responsive and highly performant across different devic

Medium · Application Design & Tech Stack

How do you ensure your CSS/HTML implementation is both responsive and highly performant across different devices?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

What design patterns do you rely on to keep a codebase clean, modular, and easy to maintain as a project scale

Medium · Application Design & Tech Stack

What design patterns do you rely on to keep a codebase clean, modular, and easy to maintain as a project scales?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

How would you refactor this component to make it more reusable and testable?

Medium · Code Comprehension & Review

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

One customer endpoint stalls deliveries to every other destination

Medium · bulkhead · timeouts · saturation

The egress service delivers about 1.5k webhooks/second across 40,000 destinations, with a per-destination concurrency cap of 4 and a 10-second connect-plus-read timeout. Throughput falls to 300/second, queue depth climbs, and p99 delivery latency for unaffected destinations goes from 200 ms to minutes, while the error rate barely moves. One tenant holds 900 destination rows whose URLs share a hostname that now answers in 9.5 seconds. Explain the mechanism with the arithmetic, then give the containment in the order you would apply it.

Approach

  1. Look at saturation before errors. A flat error rate with collapsing throughput says nothing is failing, things are waiting, so the first signal to pull is in-flight request count or pool wait time rather than the error counter. This is the distinction that decides the whole investigation.
  2. Group in-flight work by resolved host, not by destination id. The cap is keyed per destination row, so 900 rows sharing one hostname buy 3,600 concurrent slots against a single host, each held for 9.5 seconds. The bulkhead was never a bulkhead for that host, and grouping by the wrong dimension is why the dashboard looked healthy.
  3. Do the arithmetic in both directions. Required concurrency is arrival rate times latency, so 1.5k/second at 200 ms needs about 300 in flight, which is entirely consumed by 3,600 slow slots; conversely whatever concurrency is left sustains rate equals concurrency divided by 9.5 seconds, which is the 300/second you are seeing. Matching both numbers is what promotes this from a plausible story to the mechanism.
  4. Explain why the circuit breaker never helped. It opens on consecutive failures, and a 9.5-second response inside a 10-second timeout is a success. Slow is not failing, so an error-rate breaker cannot see this; you need a slow-call ratio, a deadline propagated from the caller's remaining budget, or a concurrency limiter.

Follow-up

  • The host recovers to 80 ms. How long does the queue take to drain, and what does the drain do to the recovered host?
  • Where should the 10-second timeout number actually come from?

Suggested practice checklist

Built from the rounds and topics Robots and Pencils candidates report.

Day 1 — Map the Robots and Pencils loop

  • Write out the reported sequence: Initial Contact, Collaborative Interviews, Technical Deep-Dives, Final Decision.
  • For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.

Day 2 — Work React

  • Spend the session on React, which Robots and Pencils candidates report being tested on.
  • Write one worked example in React and time yourself on it.

Deliverable: One timed worked example in React.

Day 3 — Work Code Review

  • Spend the session on Code Review, which Robots and Pencils candidates report being tested on.
  • Write one worked example in Code Review and time yourself on it.

Deliverable: One timed worked example in Code Review.

Day 4 — Work Software Engineering (Role Fundamentals)

  • Spend the session on Software Engineering (Role Fundamentals), which Robots and Pencils candidates report being tested on.
  • Write one worked example in Software Engineering (Role Fundamentals) and time yourself on it.

Deliverable: One timed worked example in Software Engineering (Role Fundamentals).

Day 5 — Answer out loud: Application Design & Tech Stack

  • Answer aloud, timed: How do you approach selecting the right technology stack for a greenfield web application?
  • Answer aloud, timed: Can you explain the differences between various state management patterns in modern frontend frameworks like ReactJS?

Deliverable: Spoken answers to 2 reported Application Design & Tech Stack question(s), under time.

Day 6 — Answer out loud: Code Comprehension & Review

  • Answer aloud, timed: Walk me through this block of code. What potential performance bottlenecks or security vulnerabilities do you see?
  • Answer aloud, timed: How would you refactor this component to make it more reusable and testable?

Deliverable: Spoken answers to 2 reported Code Comprehension & Review question(s), under time.

Day 7 — Answer out loud: Behavioral & Cross-Functional Collaboration

  • Answer aloud, timed: Describe a time when you had to work with a designer whose creative vision clashed with technical or performance constraints. How did you resolve it?
  • Answer aloud, timed: How do you handle a situation where client requirements change mid-sprint, impacting your architectural decisions?

Deliverable: Spoken answers to 2 reported Behavioral & Cross-Functional Collaboration question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

What is your process for conducting a constructive and thorough code review for a peer?

Medium · Code Comprehension & Review

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Describe a time when you had to work with a designer whose creative vision clashed with technical or performan

Medium · Behavioral & Cross-Functional Collaborat

Describe a time when you had to work with a designer whose creative vision clashed with technical or performance constraints. How did you resolve it?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you handle a situation where client requirements change mid-sprint, impacting your architectural decisi

Medium · Behavioral & Cross-Functional Collaborat

How do you handle a situation where client requirements change mid-sprint, impacting your architectural decisions?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Can you share an experience where you had to explain a highly complex technical concept to a non-technical cli

Medium · Behavioral & Cross-Functional Collaborat

Can you share an experience where you had to explain a highly complex technical concept to a non-technical client or stakeholder?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?