CoderPad AI-Assisted Interview Guide 2026: Plan Mode, Edit Mode, Codex, and Playback

CoderPad AI Assist can help produce a patch, but it cannot establish that the patch satisfies the contract. The latest-version exercise below shows why: a dictionary that keeps the last encountered event fails when events arrive out of order, and a validator that forgets old versions can miss a conflict.

Use AI-assisted Software Engineer practice to rehearse planning, patch review and testing alongside this original worked example.

What the current CoderPad modes allow

As checked on 8 October 2026, CoderPad documents Ask for discussion, Plan for a proposed approach and Edit for code changes. Shared mode exposes the shared assistance to both parties; Private assistance is Ask-only for the interviewer. Organization and pad settings affect the experience, and interview instructions determine what the candidate may do. Codex and Claude Code availability is documented for Enterprise environments, not promised in every interview. CoderPad AI Assist.

Before the exercise, confirm whether AI is allowed, which modes are enabled and whether external tools are prohibited. If the interface can edit code, keep a small enough diff to inspect. Ask the assistant to name assumptions before implementing; an attractive plan that omits conflict detection is still incomplete.

Playback documentation explains how the pad’s activity can be reviewed. Treat your prompt, code and test history as part of a coherent work record; do not confuse pad playback with a recording of every unrelated desktop action. CoderPad playback.

A complete Plan → Edit → Verify → Explain example

Use this original practice fixture in a local Python file. It is not code from CoderPad or an employer. The task: reduce a sequence of events to the newest version of each record. Every event has id, nonnegative integer version and value. Preserve input data. Repeating the same ID/version/value is harmless; a conflicting value at the same ID/version must raise an error, even if that version is no longer the latest.

Plan: make the missing requirement visible

An illustrative assistant plan says, “Store each record in a dictionary by ID and replace it whenever a newer version arrives.” That covers latest-state selection but misses conflicts in older versions. Request a second structure keyed by (id, version) and test an old-version conflict after a newer version. Keep validation separate from selection.

The intentionally weak starting function is:

def latest(events):
    return {event["id"]: event for event in events}

It chooses the last encounter, not the highest version; it returns original mutable dictionaries; it cannot detect a conflict. Before changing it, supply a failing trace: version 3 arrives before version 1 for record A. The expected result remains version 3.

Edit: inspect a small, complete replacement

def latest(events):
    chosen, versions = {}, {}
    for event in events:
        if not isinstance(event, dict):
            raise ValueError("event must be an object")
        if not isinstance(event.get("id"), str) or not event["id"]:
            raise ValueError("nonempty string id required")
        version = event.get("version")
        if type(version) is not int or version < 0 or "value" not in event:
            raise ValueError("invalid version or missing value")
        key = (event["id"], version)
        if key in versions and versions[key] != event["value"]:
            raise ValueError("conflicting version")
        versions[key] = event["value"]
        if event["id"] not in chosen or version > chosen[event["id"]]["version"]:
            chosen[event["id"]] = dict(event)
    return chosen

events = [{"id":"A","version":3,"value":"new"},
          {"id":"A","version":1,"value":"old"}]
assert latest(events)["A"]["value"] == "new"
assert latest([]) == {}
assert latest([{"id":"A","version":0,"value":None}])["A"]["version"] == 0
assert latest(events + [dict(events[0])]) == latest(events)
try:
    latest(events + [{"id":"A","version":1,"value":"conflict"}])
    raise AssertionError("old-version conflict missed")
except ValueError:
    pass
assert events[0] == {"id":"A","version":3,"value":"new"}

This fixture assumes values are immutable scalars such as strings, integers or None. dict(event) is a shallow copy, so nested values would remain shared; extend the contract and copy policy before claiming deep isolation. In a production event log, conflict detection also needs canonical value representation and a durable version record, not a growing process-local dictionary.

Verify: tests need expected outcomes, not only execution

Run the file and retain the actual exit result. The tests establish newest-version selection independent of encounter order, an empty stream, version zero, repeated events, an older-version conflict and unchanged input. They do not establish thread safety or persistence across restarts. Add malformed-ID and negative-version tests before calling the input contract complete.

Explain: defend the cost and one changed requirement

“I scan n events once using average constant-time dictionary operations. Latest state uses O(m) entries for m distinct IDs, while conflict detection uses O(v) entries for v distinct ID/version pairs. I kept all versions because the contract requires detecting conflicts after a newer version arrives. If memory must be bounded, I need a retention horizon, an external store or a weaker conflict-detection guarantee.”

That last distinction is the useful review answer. Saying the whole algorithm uses O(m) memory would hide the versions dictionary. For a 40-minute practice attempt, allow 5 minutes for contract, 10 for planning/failing fixtures, 15 for editing and execution, and 10 for review. Keep the initial function, final patch, rejected assumption and test results. CoderPad’s mode controls and playback support the interview workflow; this mock’s prompts and review checks are editorial examples, not a vendor scoring scheme.

Keep a before-and-after diff for the mock

The intentionally weak function is one line: overwrite a dictionary entry whenever the ID appears. That makes a small failure easy to explain. With A/version 3/new followed by A/version 1/old, its output is old. The corrected function compares versions, validates fields, records all seen version pairs and copies the selected record dictionary. Each added responsibility should correspond to a stated requirement or failing fixture.

An illustrative Plan request can be: “List the state needed to preserve the newest version and reject conflicting replays of older versions. Do not edit yet. Values are immutable scalars.” Review whether the plan mentions both dictionaries. An illustrative Edit request can be: “Implement only this function and its boundary checks. Preserve the caller’s input. Do not introduce persistence or change the public signature.” These are example prompts, not a transcript of an actual CoderPad run.

If the assistant proposes dropping old versions to reduce memory, ask what guarantee changes. A stream containing version 3 and then two inconsistent version-1 events must still raise under the current contract. You can accept a retention horizon only after changing the requirement. Optimization cannot silently weaken validation.

Test malformed input without hiding the reason

Use separate cases for a non-object event, an empty ID, a negative version, a boolean version and a missing value. Version zero is valid, and a value of None is valid; checking either with a generic truthiness test would reject acceptable input. A valid repeated value should remain harmless. A conflicting value should fail even when it cannot change the selected latest record.

For the practice function, the errors are ValueError rather than a production response schema. If the follow-up asks for an API, define the status, indexed error details and whether one bad event fails the whole batch. Do not invent partial success after implementing a fail-fast function without explaining the changed contract.

Use playback as a coherent work record

A reviewer should be able to follow why you changed the code: a contract, a counterexample, a bounded edit and executed checks. If a patch was wrong, say which test exposed it and how you repaired it. A final working result does not require pretending the first assistant response was correct.

Keep the review proportionate. Read the changed function, inspect the tests’ expected outcomes and rerun the relevant cases. An assistant’s explanation of correctness is a hypothesis; execution and your invariant provide evidence. Explain remaining limits such as process-local state, growing history and shallow copies without turning the interview into an unrelated production redesign.

At the end, give a thirty-second handoff: “The newest-version selection is independent of arrival order. Old-version conflicts are retained and rejected. The supplied checks pass. Values are scalar, and persistence and concurrent writers remain outside this function.” That is more reviewable than saying you used Plan and Edit successfully.

Make the assistant’s output reviewable

Your plan should name the two distinct stores: one remembers every (id, version) payload for conflict checks, while the other selects the highest version per ID. If an assistant collapses them into one dictionary, trace version 3, version 1 and a conflicting replay of version 1. The output may still contain version 3 while the validator incorrectly accepts the conflict. A plausible final result can hide a validation defect.

The code uses shallow copies because the fixture treats values as immutable scalars. With nested lists or dictionaries, equality, mutation and snapshot semantics need an explicit contract. Do not casually say “copy makes it immutable.” Python copy semantics.

A seven-session plan with evidence

1. Confirm the assessment’s tools and modes; practice without assistance once.
2. Implement the latest-version contract and write a version-order test.
3. Add the conflicting old-version replay, which distinguishes validation from selection.
4. Ask for a bounded plan and review its assumptions before permitting edits.
5. Inspect a patch line by line. Reject any unrelated change and rerun the checks.
6. Explain time and memory using the number of distinct version pairs, not only IDs.
7. Run a forty-minute mock and finish with a short handoff: what changed, what ran and what remains assumed.

Can I assume Codex is available?

No. Ask about the particular environment. The vendor documentation’s Enterprise availability is a product boundary, not an entitlement for every candidate.

Is a correct final dictionary enough?

No. The contract also rejects conflicting replays. Test a conflict on an old version even when a newer version has already won selection.

What should I explain after using Edit mode?

The agreed contract, the patch’s invariant, executed tests, complexity and any remaining assumptions. You should be able to reproduce the reasoning without reading the assistant’s explanation aloud.

Sources and Further Reading

• CoderPad AI Assist
• CoderPad playback
• Python copy semantics

Editorial revision: 8 October 2026. Current hiring details remain role-specific; unavailable source pages and unverified timings are identified in the text.