Interview guides · Current Edge Solutions

Current Edge Solutions Software Engineer Interview Guide

Current Edge Solutions Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Current Edge Solutions, the Software Engineer role represents a highly specialized intersection of software engineering, automation, and physical power systems engineering. Unlike traditional software roles that focus solely on web applications or consumer services, engineers in this pipeline build, automate, and optimize the critical infrastructure that powers our communities. Whether you are specializing as a Principal Transmission Line Engineer, a Principal Substation Design Engineer, or a Distribution Engineer, your work directly impacts the resilience, efficiency, and modernization of the electrical grid. The engineering team at Current Edge Solutions is responsible for developing sophisticated design workflows, automating complex structural and electrical calculations, and modeling high-voltage systems.

This guide is scoped to a Software Engineer candidate at Current Edge Solutions.

Focus areas

Software Engineering (General)
Power Systems Domain Knowledge (Transmission/Substation/Dist
Principal-Level Engineering (Ownership/Architecture)

The Current Edge Solutions interview process

Current Edge Solutions candidates report 5 rounds over 4-6 weeks. The stages below are what candidates describe, not a published process.

Technical Screening

Initial assessment of technical competence to determine fit for the role.

What to demonstrate

Initial assessment of technical competence to determine fit for the role
Depth in Software Engineering (General)

How to prepare

Answer aloud and timed: How do you determine the optimal conductor spacing and tension for a transmission line under extreme wind and ice loading conditions?
Answer aloud and timed: Describe your approach to designing a substation ground grid. What safety standards and soil resistivity factors do you prioritize?

Technical Panel Interview

In-depth interview where candidates present past projects or solve real-world design scenarios.

What to demonstrate

In-depth interview where candidates present past projects or solve real-world design scenarios
Depth in Software Engineering (General)

How to prepare

Answer aloud and timed: What are the primary differences between designing a radial distribution system and a loop distribution system?
Answer aloud and timed: How do you calculate and mitigate the risk of galloping conductors on high-voltage transmission lines?

Behavioral Alignment

Evaluation of candidates' alignment with company culture and collaborative working style.

What to demonstrate

Evaluation of candidates' alignment with company culture and collaborative working style
Depth in Software Engineering (General)

How to prepare

Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
Re-read the description of the behavioral alignment above and write down what you would ask to confirm before it.

Safety Leadership Assessment

Assessment of candidates' understanding and commitment to safety leadership in engineering.

What to demonstrate

Assessment of candidates' understanding and commitment to safety leadership in engineering
Depth in Software Engineering (General)

How to prepare

Answer aloud and timed: How do you handle data validation when importing large GIS datasets into a power systems modeling environment?
Answer aloud and timed: Describe a scenario where you automated a manual calculation process. What tools did you use, and how did you verify the accuracy of the output?

Multidisciplinary Team Evaluation

Evaluation of candidates' ability to work within multidisciplinary project teams.

What to demonstrate

Evaluation of candidates' ability to work within multidisciplinary project teams
Depth in Software Engineering (General)

How to prepare

Answer aloud and timed: How would you design an algorithm to optimize the placement of distribution transformers to minimize voltage drop and line losses?
Answer aloud and timed: What software design patterns are most effective when building reusable modeling components for substation layouts?

Where candidates lose points

Highlight your automation experience

Whenever you discuss past projects, emphasize how you used scripting, software tools, or database management to make your engineering design workflows more efficient.

Know your codes

Be prepared to discuss the National Electrical Safety Code (NESC) and other relevant standards (such as ASCE or IEEE). Demonstrating a strong familiarity with these regulations shows you are ready to produce client-ready designs.

Always explain the "why" behind your design assumptions

Interviewers care more about your engineering methodology and safety considerations than just getting a perfect numerical answer.

Questions & practice

Identify the heaviest tenants in a five-minute window under memory pressure

Medium · top-k · heavy hitters · streaming

The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.

Approach

Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.

Follow-up

The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?

Find overlapping job attempts and peak concurrency from lease records

Medium · sweep line · intervals · leases

A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.

Approach

Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.

Follow-up

A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?

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

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.
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.
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.
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?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
How do you verify the backfill actually finished, given rows are still being inserted while it runs?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
How do you honour an erasure request while resource_revision.actor_user_id still references this table?

How do you determine the optimal conductor spacing and tension for a transmission line under extreme wind and

Medium · Power Systems & Infrastructure Design

How do you determine the optimal conductor spacing and tension for a transmission line under extreme wind and ice loading conditions?

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

Describe your approach to designing a substation ground grid. What safety standards and soil resistivity facto

Medium · Power Systems & Infrastructure Design

Describe your approach to designing a substation ground grid. What safety standards and soil resistivity factors do you prioritize?

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

What are the primary differences between designing a radial distribution system and a loop distribution system

Medium · Power Systems & Infrastructure Design

What are the primary differences between designing a radial distribution system and a loop distribution system?

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

How do you calculate and mitigate the risk of galloping conductors on high-voltage transmission lines?

Medium · Power Systems & Infrastructure Design

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

Walk us through your process for selecting structural materials (e.g., steel vs. wood poles) based on mechanic

Medium · Power Systems & Infrastructure Design

Walk us through your process for selecting structural materials (e.g., steel vs. wood poles) based on mechanical loading and environmental exposure.

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

Explain how you would write a script or program to parse raw survey data and automatically generate a prelimin

Medium · Automation & Computational Engineering

Explain how you would write a script or program to parse raw survey data and automatically generate a preliminary transmission alignment.

Approach

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

Follow-up

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

Describe a scenario where you automated a manual calculation process. What tools did you use, and how did you

Medium · Automation & Computational Engineering

Describe a scenario where you automated a manual calculation process. What tools did you use, and how did you verify the accuracy of the output?

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
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 design an algorithm to optimize the placement of distribution transformers to minimize voltage d

Medium · Automation & Computational Engineering

How would you design an algorithm to optimize the placement of distribution transformers to minimize voltage drop and line losses?

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

What software design patterns are most effective when building reusable modeling components for substation lay

Medium · Automation & Computational Engineering

What software design patterns are most effective when building reusable modeling components for substation layouts?

Approach

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

Follow-up

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

Every query on one table stalls for forty seconds mid-deploy

Medium · lock contention · ddl · migrations

During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.

Approach

Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.

Follow-up

The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?

Suggested practice checklist

Built from the rounds and topics Current Edge Solutions candidates report.

Day 1 — Map the Current Edge Solutions loop

Write out the reported sequence: Technical Screening, Technical Panel Interview, Behavioral Alignment, Safety Leadership Assessment, Multidisciplinary Team Evaluation.
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 5 reported rounds, with the weakest marked.

Day 2 — Work Software Engineering (General)

Spend the session on Software Engineering (General), which Current Edge Solutions candidates report being tested on.
Write one worked example in Software Engineering (General) and time yourself on it.

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

Day 3 — Work Power Systems Domain Knowledge (Transmission/Substation/Distribution) - Conceptual

Spend the session on Power Systems Domain Knowledge (Transmission/Substation/Distribution) - Conceptual, which Current Edge Solutions candidates report being tested on.
Write one worked example in Power Systems Domain Knowledge (Transmission/Substation/Distribution) - Conceptual and time yourself on it.

Deliverable: One timed worked example in Power Systems Domain Knowledge (Transmission/Substation/Distribution) - Conceptual.

Day 4 — Work Principal-Level Engineering (Ownership/Architecture)

Spend the session on Principal-Level Engineering (Ownership/Architecture), which Current Edge Solutions candidates report being tested on.
Write one worked example in Principal-Level Engineering (Ownership/Architecture) and time yourself on it.

Deliverable: One timed worked example in Principal-Level Engineering (Ownership/Architecture).

Day 5 — Answer out loud: Power Systems & Infrastructure Design

Answer aloud, timed: How do you determine the optimal conductor spacing and tension for a transmission line under extreme wind and ice loading conditions?
Answer aloud, timed: Describe your approach to designing a substation ground grid. What safety standards and soil resistivity factors do you prioritize?

Deliverable: Spoken answers to 2 reported Power Systems & Infrastructure Design question(s), under time.

Day 6 — Answer out loud: Automation & Computational Engineering

Answer aloud, timed: Explain how you would write a script or program to parse raw survey data and automatically generate a preliminary transmission alignment.
Answer aloud, timed: How do you handle data validation when importing large GIS datasets into a power systems modeling environment?

Deliverable: Spoken answers to 2 reported Automation & Computational Engineering question(s), under time.

Day 7 — Answer out loud: Behavioral & Project Leadership

Answer aloud, timed: Describe a time when you identified a critical safety or design flaw late in a project's lifecycle. How did you address it with the client or project manager?
Answer aloud, timed: How do you prioritize competing demands when managing multiple design deliverables with overlapping deadlines?

Deliverable: Spoken answers to 2 reported Behavioral & Project Leadership question(s), under time.

Behavioural preparation

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

How do you handle data validation when importing large GIS datasets into a power systems modeling environment?

Medium · Automation & Computational Engineering

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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 identified a critical safety or design flaw late in a project's lifecycle. How did yo

Medium · Behavioral & Project Leadership

Describe a time when you identified a critical safety or design flaw late in a project's lifecycle. How did you address it with the client or project manager?

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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 prioritize competing demands when managing multiple design deliverables with overlapping deadlines?

Medium · Behavioral & Project Leadership

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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?

Tell me about a time you had to explain a highly technical engineering constraint to a non-technical stakehold

Medium · Behavioral & Project Leadership

Tell me about a time you had to explain a highly technical engineering constraint to a non-technical stakeholder or client.

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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?

Give an example of how you handled a disagreement with another engineer regarding a design standard or softwar

Medium · Behavioral & Project Leadership

Give an example of how you handled a disagreement with another engineer regarding a design standard or software implementation.

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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?