Five-Lane Ledger

That guide is a reference and answer key, not a second task list. Treating it as more work to do would roughly double the plan for very little new coverage. Treating it as the place you go when a GFE 75 quiz question stumps you costs nothing and saves hours.

Where it already answers GFE 75

Roughly 12 of the 21 GFE quiz questions have written answers in it: hoisting, closures, event bubbling, event delegation, null vs. undefined vs. undeclared, cookie vs. sessionStorage vs. localStorage, script async vs. defer, z-index and stacking context, the box model, box-sizing, positioning, and how a browser matches a CSS selector. In weeks 7 and 8, read its section first and write the answer in your own words in the note field.

Coding exercises that overlap

Its bigfrontend.dev list duplicates GFE 75 on curry, throttle, debounce, flatten, memoize, promisify, event emitter, the async-utils family, and _extend (≈ deep clone / data merging). Do them once, in GFE, where you get tests.

Worth cherry-picking — not in GFE 75

Its prototypal inheritance walkthrough (factory → Object.create → new → class), the this-binding corner cases, and the repaint / reflow section have no GFE 75 equivalent and are still asked. Its accessibility and web-performance sections map onto weeks 12 and 13 here — use them as the reading for those weeks.

What to skip

Its Algorithms track is a Princeton-course-plus-LeetCode-lists plan — a substitute for NeetCode 150, not a supplement. Running both would cost you 200+ extra problems for the same patterns. Pick NeetCode, which you have already started, and ignore that section. Same for its HTML/CSS chapter, which the guide itself labels mostly copy-paste.

You will have evenings where the card looks like a wall and the offer looks like a fantasy. This section exists for those evenings. It is not a pep talk. It is a reminder of how the plan is built, so that on the nights your motivation is gone, the system still carries you.

Identity first

The goal is not “finish NeetCode 150”. The goal is to become the kind of engineer who walks into a Datadog loop and belongs there. Every ticked box is a vote for that person. You do not need a unanimous vote. You need a majority — and you already have August’s votes in the bank, pre-ticked at the top of the ledger.

How the plan uses the four laws, so you do not have to

• Make it obvious. The dashboard is bookmarked, opens on the current week, and tells you exactly which card is tonight’s. You never have to decide what to do. Only whether, and that decision was made in August.
• Make it attractive. Two rewards you chose yourself, at checkpoints you can see coming. The lane strip fills in with colour as you go; by week 10 it is visibly yours. And the Design lane is spoken out loud — it is the lane that feels most like the real thing, and it is the one that moves the offer most.
• Make it easy. Six hours a week, two or three sessions. Hards are timeboxed to 30 minutes so no single problem can eat an evening. Quizzes gate the reading so you only read what you do not already know. Every task has a link, so the distance between “open the dashboard” and “working” is one click.
• Make it satisfying. The tick. The stamp when a lane clears. The fraction on the block head going up. The sticky note that turns yellow when you write on it. These are small on purpose — they fire every session, not at the end of six months.

The three rules for a bad week

• Never miss twice. A missed session is a session. Two in a row is the start of a new habit, and that one is much harder to break than the one you are building. If you missed Tuesday, Thursday is non-negotiable, even if it is twenty minutes.
• Two-minute rule. On the worst night, the task is not “solve Trapping Rain Water”. It is “open Trapping Rain Water and read it”. Starting is the habit. What happens after you start is, most nights, more than you expected.
• Reduce the scope, never the schedule. Behind? Do fewer tasks, not zero weeks. One problem and one story is a full session. The pace pill measures tasks, but the identity is built by showing up on the nights you planned to.

The plateau

Around week 3, and again around week 9, the novelty is gone and the results are not here yet. That gap is where most plans die, and it is where the work is actually compounding. An ice cube does not melt at 25, 26, 27 degrees, and then does at 32. Nothing visible happened at 31. Everything happened at 31.

What you are not allowed to do

Redesign the plan mid-block because it feels slow. Add a new resource because someone on a forum said it was essential. Start over “properly” from week 1. These all feel like progress and they are all forms of quitting. The plan is already pragmatic. The only way it fails is if it stops being followed.

Every week card carries one line written for the night you open it feeling like this. Read it, do the smallest task on the card, tick it, close the laptop.

Every one of the five loops has a dedicated behavioural round, and two of them — Cloudflare’s Orange Cloud and Spotify’s values round — are scored as filters, not formalities. This is the lane with the best return per hour, because almost nobody prepares it.

The shape

STAR, plus an R. Situation in one sentence — just enough to place the listener. Task: what was specifically yours. Action: about sixty per cent of your airtime, and say I, not we — “we” is where interviewers lose the signal. Result: a number. Reflection: what you would do differently. That last beat is what separates an answer that happened from an answer that was rehearsed, and staff-level rubrics probe for it directly.

Two minutes, then stop

Cloudflare caps that round at thirty minutes, which is roughly six stories. A six-minute answer costs you half the round. Rehearse against a timer until the whole arc fits in two minutes, and let the interviewer pull the detail out of you — their follow-up questions are where the good signal is anyway.

Lead with the outcome, then rewind

“We took p95 from 4.2 seconds to 900 milliseconds — here is how that started.” Interviewers write their impression down in the first twenty seconds. Do not spend those twenty seconds on org chart and background.

Name the scope out loud — this is the staff line

An answer that stops at your own team reads as senior, however good the work was. Say who outside your team changed what they were doing because of you. Then say what you deliberately did not do: “we consciously didn’t migrate the legacy path, because…”. Volunteering a non-goal is the single strongest staff signal, and hardly anyone offers one unprompted. Pair it with the rollback plan you had.

Quantify, or failing that, scale

If you genuinely have no metric, give a size instead: “the three teams that consumed it”, “about forty per cent of our traffic”, “a fourteen-person org”. Precision anywhere buys credibility everywhere. Vagueness reads as invention, so keep a fact sheet in each note: dates, headcount, the metric, the real name of the system.

Own the failure stories completely

Do not bring a weakness that is secretly a strength — interviewers have heard it and it costs you trust for the rest of the round. Bring a real one, keep the retelling short, and spend the airtime on what you changed afterwards and what has happened since.

One story answers several questions

A good story can serve three or four prompts with a different emphasis each time. Sixteen of them covers most loops — as long as you know which angle each one can turn. Note the alternate angles at the bottom of each story.

The 2026 addition

Expect to be asked how you used AI on the work: where it helped, where you overrode it, how you checked it. Google now grades that explicitly. Have one honest story where the answer is “it was confidently wrong and here is how I caught it”.

Practicalities

• Bullet the five beats. Never write it out in full — a memorised paragraph sounds memorised.
• Say it out loud three times before you call it done. It is a different skill from writing it.
• Bring your own question to the closing round. That round is scored too.

These five run genuinely different loops, and the differences are not cosmetic. Of the fifteen-odd rounds below, one is a LeetCode-style algorithm round. Everything else is code you would actually ship, code somebody else wrote, or you explaining a system out loud.

The five gaps this closed

• No take-home artefact. Two of the five gate on one, and both judge documentation and commit history. You now build one across weeks 12 and 13 instead of improvising it under a 72-hour clock.
• No debugging or code-review practice. Cloudflare has a dedicated debugging round; GitHub pairs you on review. Both were entirely absent. Week 14 is now theirs.
• No deep dive on your own work. Datadog, Spotify and Cloudflare all ask you to walk through a system you built. Week 14 writes it down with a diagram, the trade-offs, the non-goals and the rollback plan — the four things staff-level interviewers listen for.
• No presentation. At Datadog Staff it literally replaces a coding round. Week 15 builds it.
• No behavioural preparation at all. All five have a dedicated behavioural round, two of them explicitly weighted as filters. Hence the fourth lane.

Senior versus staff, in one line

A senior answer can be about a system you owned. A staff answer has to name someone outside your team who changed what they were doing because of you — plus the non-goals you chose and the rollback plan you had. That is why every prompt in the Stories lane asks for scope, and why week 16 ends on a cross-team architecture case rather than another algorithm.

Re-weight, don’t pivot. All three sources are still the right ones; what has changed is how much of the loop they cover. The 2026 signal is consistent across sources:

• Algorithm rounds are still the baseline gate — Google, LinkedIn and Microsoft show the clearest DSA signal — but they are one round, not the loop.
• Google has added a code-comprehension round: read, debug and optimise an existing codebase, with Gemini available, and your use of it graded — prompting, validating output, catching what the model gets wrong.
• Front-end loops moved from JS trivia to practical UI tasks: build this component, debug this layout, design this state-management pattern.
• Meta and Google are piloting AI-assisted rounds and Canva now expects candidates to use AI tools — but a January 2026 Karat survey still found 62% of organisations prohibit AI in technical interviews. Prepare for both rules.
• The widely-repeated split is roughly 30% algorithms, 70% system design and practical engineering.

What that changes in this plan

• NeetCode stays, but timeboxed. 45 minutes per problem, then read the solution and write the pattern in the note field. Finishing 150 slowly is worth less than owning 18 patterns.
• DDIA gets more valuable, not less. It is the deepest lane you have for the part of the loop that grew. That is why every chapter here carries a second task: name the one trade-off you would actually cite out loud.
• GFE ordering is inverted. Implementation and UI builds come first (weeks 1–6), quiz last (weeks 7–8) — the quiz is the part that decayed most in value.
• Weeks 10–16 are the new material. Speed rebuilds, React hooks with tests, an accessibility pass, a performance pass, a code-comprehension drill on an unfamiliar repo, one deliberate AI-assisted rehearsal, and full mock loops. That block is the answer to the trend, and it is why the plan does not end when GFE 75 does.

One thing this plan deliberately does not add: a separate LeetCode grind on top of NeetCode 150. The evidence points the other way.

Two resources worth adding, from the Front-End Engineer Blog channel

Evgenii Ray — the author of the Notion guide above, now SWE at Meta in London — spent the past year interviewing across HFT, finance and FAANG and turned the questions into a free two-day Frontend Masters intensive in March 2026: around 60 front-end problems solved live, ending in a small Google Sheets clone, with the problems published as a GitHub repo. He has an earlier Frontend Masters course on front-end system design too. Both sit closer to what these loops now ask than the GFE quiz does.

Two of his choices are worth copying. He solved that entire stream by hand, no AI agents — which is the skill 62% of loops still test. And he is redirecting his own learning at client-side AI engineering and model optimisation, alongside Meta’s Dev AI Infrastructure team. If you want one differentiator beyond this plan, that is the one a staff-level front-end candidate can credibly claim in 2026.