Should you still grind LeetCode? The software engineering interview prep plan for the AI era
On one of Anthropic's coding take-homes, over half of candidates would have scored better just handing it to Claude Code.
AI didn't kill the coding interview. It changed what counts as proof. Big-tech algorithm screens are still here, but more rounds now grade how you read, check and fix code (often with AI) and how you defend design trade-offs. Here's our 30/40/30 prep plan, adjusted for your level.
By Preston KirschnerFounder, AI Career HubUpdated
- What changed in coding interviews in 2026
- Questions to ask the recruiter before you prep
- The 30/40/30 prep plan
- Drills, talk-aloud and narration templates
- A 10-hour weekly schedule
- Should you stay a software engineer?
- Of candidates on one Anthropic take-home would have scored better by handing it entirely to Claude Code (as of May 2025).
- Over 50%
- Anthropic Engineering, Jan 21, 2026
- FAANG interviewers who said their company had moved away from algorithm questions.
- 0 of 52
- Small, self-selected sample.
- interviewing.io survey, Late 2025
- Organizations that still prohibit AI in technical interviews.
- 62%
- Vendor survey of 400 engineering leaders.
- Karat, Jan 7, 2026
- Developers using AI coding tools who use them daily.
- 73%
- Stack Overflow Developer Survey 2026, Oct 6, 2026
- Software engineers who change jobs and land in another software engineering role.
- ~70%
- LinkedIn Economic Graph, Feb 2026
In this guide
Yes, keep practicing algorithms. Stop counting problems.
In a late-2025 interviewing.io survey, zero of 52 FAANG interviewers said their company had moved away from algorithm questions, while 58% said they'd changed the kinds of algorithm questions they ask. It's a small, self-selected sample, but the direction is clear: the screen is still there, and memorized answers are worth less.
Why are they worth less? On Anthropic's performance-engineering take-home, where AI use is explicitly allowed, over half of candidates would have done better by May 2025 just handing the whole thing to Claude Code. Anthropic says each new Claude model has forced it to redesign the test (Anthropic Engineering, January 21, 2026; TechCrunch, January 22, 2026).
When AI can produce the answer, the answer stops proving skill. So interviewers are grading how you think, check and defend. Split your prep to match: patterns without AI, reading and fixing real code with AI, and system design you can defend.
What changed in 2026, at a glance
Policies differ by company and even by round. Here's what we could verify from primary sources or direct reporting, last checked October 20, 2026.
- Round
- Coding and design interviews for select roles, in CoderPad
- AI allowed?
- Yes. A built-in assistant, and candidates are expected to use it. No outside AI tools.
- What they look for
- Meta's prep tip: "being comfortable reading, debugging, and building on existing code"
- Source
- Meta Careers hiring page (read Oct 20, 2026)
- Round
- Code comprehension round in an existing codebase. A pilot for junior and mid-level roles on select U.S. teams, from H2 2026
- AI allowed?
- Gemini allowed, in the pilot
- What they look for
- "AI fluency": prompt engineering, output validation and debugging
- Source
- Entrepreneur, citing Business Insider (May 8, 2026). No public report yet confirms it's live.
- Round
- Phone screen replaced by system design. Onsite: plan, a 2-hour build, then review
- AI allowed?
- Any AI tools during the build
- What they look for
- Demo, code review, path to production, and how you used AI
- Source
- Sierra blog (Apr 22, 2026)
- Round
- AI interviewer "Chakra" in a real code repo
- AI allowed?
- Built-in AI assistant
- What they look for
- "AI fluency": framing problems for AI, evaluating and steering its output
- Source
- TechCrunch (Oct 5, 2026). 500,000+ interviews is the vendor's own figure.
- Round
- Live interviews
- AI allowed?
- No, unless they tell you otherwise
- What they look for
- Your own skills
- Source
- Anthropic candidate AI guidance (updated Jul 10, 2025)
- Round
- Assessments and interviews
- AI allowed?
- No, unless explicitly allowed
- What they look for
- Your own skills
- Source
- Microsoft Careers, "How we hire"
| Company | Round | AI allowed? | What they look for | Source |
|---|---|---|---|---|
| Meta | Coding and design interviews for select roles, in CoderPad | Yes. A built-in assistant, and candidates are expected to use it. No outside AI tools. | Meta's prep tip: "being comfortable reading, debugging, and building on existing code" | Meta Careers hiring page (read Oct 20, 2026) |
| Code comprehension round in an existing codebase. A pilot for junior and mid-level roles on select U.S. teams, from H2 2026 | Gemini allowed, in the pilot | "AI fluency": prompt engineering, output validation and debugging | Entrepreneur, citing Business Insider (May 8, 2026). No public report yet confirms it's live. | |
| Sierra | Phone screen replaced by system design. Onsite: plan, a 2-hour build, then review | Any AI tools during the build | Demo, code review, path to production, and how you used AI | Sierra blog (Apr 22, 2026) |
| HackerRank (platform) | AI interviewer "Chakra" in a real code repo | Built-in AI assistant | "AI fluency": framing problems for AI, evaluating and steering its output | TechCrunch (Oct 5, 2026). 500,000+ interviews is the vendor's own figure. |
| Anthropic | Live interviews | No, unless they tell you otherwise | Your own skills | Anthropic candidate AI guidance (updated Jul 10, 2025) |
| Microsoft | Assessments and interviews | No, unless explicitly allowed | Your own skills | Microsoft Careers, "How we hire" |
Ask the recruiter before you prep
Five questions save you weeks of prepping for the wrong format.
Hi [Name], thanks for setting this up. A few quick questions so I can prepare well: 1. Which rounds allow AI tools, if any? 2. If AI is allowed, which tool or model will be available? 3. Is the screen an algorithms and data structures problem, or something else (debugging, code review, a practical build)? 4. What's the format for the design round: whiteboard, a doc, or a coding pad with diagrams? 5. Is there a code-review or debugging round? Thanks!
The 30/40/30 plan
30% patterns, no AI. 40% read, break and fix real code with AI. 30% design you can defend.
This split is our editorial recommendation, based on the research on this page. It is not a measured statistic.
Adjust it by level. Early-career candidates usually face online assessments and phone screens as the main gate. For experienced candidates, design and judgment carry more of the loop, and SignalFire reports companies are prioritizing experienced individual contributors over training new grads (State of Tech Talent, June 2026).
- Patterns (no AI)
- 30%
- Read, break, fix (with AI)
- 40%
- Design and defend
- 30%
- Patterns (no AI)
- 40%
- Read, break, fix (with AI)
- 35%
- Design and defend
- 25%
- Patterns (no AI)
- 20%
- Read, break, fix (with AI)
- 40%
- Design and defend
- 40%
| Level | Patterns (no AI) | Read, break, fix (with AI) | Design and defend |
|---|---|---|---|
| Default | 30% | 40% | 30% |
| New grad / early career | 40% | 35% | 25% |
| Mid-career / senior | 20% | 40% | 40% |
Patterns, not problem counts
Big-tech screens are still algorithmic, but the questions are shifting: 58% of FAANG interviewers in that late-2025 survey said they've changed the kinds of questions they ask.
Here's why fresh variants beat memorized lists. In a 2024 interviewing.io experiment, candidates secretly using ChatGPT passed 73% of interviews built on well-known LeetCode questions, but only 25% with custom questions. It was a small test (32 interviews), but it shows why interviewers are moving to questions you can't look up.
Learn about 15 core patterns. For each one, solve 2–3 fresh variants timed, with no AI, talking out loud. Then change one constraint and solve it again.
- Hash maps and sets
- Two pointers
- Sliding window
- Prefix sums
- Binary search (including searching for the answer)
- Stacks and monotonic stacks
- Linked lists (fast and slow pointers)
- Tree traversal (DFS)
- BFS (level order, shortest path in unweighted graphs)
- Graphs: connected components and topological sort
- Heaps and top-K
- Intervals (sort and merge)
- Backtracking
- Dynamic programming basics (1D and 2D)
- Greedy
1. Pick a pattern. Solve 2–3 fresh problems that use it: timed, no AI, talking out loud. 2. Change one constraint (the input is streamed, memory is limited, values can be negative, there are duplicates) and solve again. 3. Say the time and space complexity before you code. 4. Write down the "tell": the clue in the problem that points to this pattern.
"Let me restate the problem: ..." "Examples and edge cases: empty input, duplicates, negatives, very large n." "Brute force is ..., which is O(...). The tell here is ..., so I'll use [pattern]." "Plan: step 1 ..., step 2 ..., step 3 ..." "Coding now. I'll test with [example] and [edge case]." "Complexity: O(...) time, O(...) space. If [constraint] changed, I'd ..."
Read, break, fix: real code with AI
This mirrors the new rounds. Google's pilot grades output validation and debugging. Meta's prep advice is "being comfortable reading, debugging, and building on existing code." Sierra is piloting a round where you review and improve a colleague's draft pull request with coding agents.
In CoderPad's State of Tech Hiring 2026 (vendor survey, March 2026), hiring leaders said that when AI is allowed, they value candidates who "catch and fix AI mistakes," "explain trade-offs and correctness" and "improve AI output through iteration."
It's also how developers already work: 73% of developers who use AI coding tools use them daily, and 48% trust AI output when they can easily verify it (Stack Overflow Developer Survey 2026, October 2026).
Twice a week, pick an unfamiliar, multi-file open-source repo in your language. Choose one with good tests and some open issues.
0–10 min Read: run it, skim the structure, find the entry point. No AI yet. 10–30 min Fix: pick a real open bug (or break something on purpose) and fix it. 30–50 min Build: add one small feature. 50–60 min Test: write tests for both changes and run the full suite. AI rules: - Think first, prompt second. Say what you want before you ask. - Use AI only for scoped subtasks. - Never accept code you haven't read. Say what it does and how you'll verify it. - Run the tests before you call anything done.
"I'm delegating [X] to the assistant because [reason]. I'll verify it by [test / reading / running it]." "This suggestion looks right, but it misses [edge case], so I'm changing [line]." "I'm not using AI for [part] because [it's the core logic and I want to reason through it]."
Design and defend
Sierra replaced its coding phone screen with a system design interview (April 2026). Meta runs design interviews for select roles in CoderPad with Mermaid diagrams and the same AI assistant. And CNN reported in May 2026 that reasoning and trade-off questions, once mostly for senior roles, are becoming standard across levels.
Each week, write up one system design as text or a diagram. Include one AI feature (RAG or an agent) and its failure modes. Then do a 10-minute "defend my past project" drill.
- A URL shortener with click analytics
- A rate limiter for a public API
- A news feed
- A chat app with message history
- A RAG assistant over a company's docs, with citations and evals
- A support agent that can take actions (like refunds), with guardrails
- A notification system with retries
- An evaluation pipeline for an LLM feature: offline test set plus live monitoring
flowchart LR User[User] --> API[API gateway] API --> App[App service] App --> Cache[(Cache)] App --> DB[(Primary DB)] App --> Retriever[Retriever] Retriever --> VDB[(Vector DB)] App --> LLM[LLM provider] LLM -.->|timeout or bad output| Fallback[Fallback + eval logging]
Paste into any Mermaid editor to render it, then adapt it to your prompt.
Project: Goal and constraints: The 2–3 big decisions I made, and the alternatives I rejected: Trade-offs I accepted, and why: What broke, and how I found out: What I'd change, knowing what I know now: How I'd handle 10x the load:
A 10-hour week on the default split
Here's what 30/40/30 looks like with 10 hours a week. Scale the hours to your time, and shift them using the level table above.
- Focus
- Patterns: one pattern, 2 fresh variants, no AI
- Time
- 1.5 hrs
- Focus
- Read-break-fix session #1
- Time
- 2 hrs
- Focus
- Patterns: variant drill and talk-aloud practice
- Time
- 1.5 hrs
- Focus
- Read-break-fix session #2
- Time
- 2 hrs
- Focus
- System design: one prompt, written up with a diagram
- Time
- 2 hrs
- Focus
- "Defend my past project" drill, then a mock or a review of the week
- Time
- 1 hr
- Focus
- Off
- Time
- 0
| Day | Focus | Time |
|---|---|---|
| Mon | Patterns: one pattern, 2 fresh variants, no AI | 1.5 hrs |
| Tue | Read-break-fix session #1 | 2 hrs |
| Wed | Patterns: variant drill and talk-aloud practice | 1.5 hrs |
| Thu | Read-break-fix session #2 | 2 hrs |
| Fri | System design: one prompt, written up with a diagram | 2 hrs |
| Sat | "Defend my past project" drill, then a mock or a review of the week | 1 hr |
| Sun | Off | 0 |
Don't hide AI use where it's banned
Interviewers are watching for it. CodeSignal, which sells proctored assessments, reported flagged cheating attempts on its tests rose from 16% in 2024 to 35% in 2025 (February 2026). Those are flagged attempts, not proven cheating.
Follow-up questions also expose code you can't explain. Use AI to prepare: generate variants, review your solutions, quiz you on trade-offs. In the interview, follow the rules for that round.
Should you stay a software engineer?
Mostly, yes, and move toward AI within the role. LinkedIn's U.S. Software Engineer Talent Landscape (February 2026) found nearly 70% of software engineers who change jobs land in another SWE role (69.0% in 2025, vs 71.4% in 2021).
Moves into generative-AI engineer roles have grown nearly 9x since 2021, but they're still under 1% of SWE job switches. And AI is the fastest-growing skill among software engineers who got hired from 2021 to 2025 (LinkedIn).
The play: add an AI layer to the job you have. Ship one AI feature to production, with evals, monitoring and a rollback plan. Then decide whether the title should follow.
SWE interview prep for the AI era
Line up the interviews to prep for
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Put the prep to work
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Browse AI engineering jobsSources
- 1.Designing AI-resistant technical evaluationsAnthropic Engineering (Tristan Hume) · Jan 21, 2026 · One performance-engineering take-home, AI explicitly allowed. The over-50% figure is as of May 2025.
- 2.Anthropic has to keep revising its technical interview testTechCrunch · Jan 22, 2026
- 3.Google is testing a new rule to transform job interviewsEntrepreneur, citing Business Insider · May 8, 2026 · Based on an internal Google document. A pilot, not a company-wide policy.
- 4.Hiring processMeta Careers · Undated; read Oct 20, 2026 · Applies to select roles.
- 5.The AI-native interviewSierra · Apr 22, 2026
- 6.HackerRank's AI interviewer offers a glimpse into what job interviews could becomeTechCrunch · Oct 5, 2026 · Interview counts are the vendor's own figures.
- 7.Candidate AI guidanceAnthropic · Updated Jul 10, 2025
- 8.How we hireMicrosoft Careers · Undated; read Oct 20, 2026
- 9.Engineering Interviews in 2026: 3 TrendsKarat · Jan 7, 2026 · Vendor survey of 400 engineering leaders in the US, India and China. "Over half use AI" is a leader estimate.
- 10.The 2026 State of Tech HiringCoderPad · Mar 11, 2026 · Vendor survey of 650+ developers, recruiters and hiring leaders.
- 11.AI is changing this job so fast the interview process can't keep upCNN · May 28, 2026
- 12.Assessment fraud more than doubled in 2025CodeSignal (press release) · Feb 25, 2026 · Vendor that sells proctoring. Figures are flagged attempts.
- 13.The results of the 2026 Developer Survey are hereStack Overflow · Oct 6, 2026 · Self-selected survey of 30,000+ developers.
- 14.2026 Developer Survey: AIStack Overflow · Oct 2026
- 15.How is AI changing interview processes? Not much and a whole lot.interviewing.io (Aline Lerner) · Sep 18, 2025 · Small, self-selected survey: 67 respondents, 52 from FAANG.
- 16.How hard is it to cheat in technical interviews with ChatGPT?interviewing.io · 2024 · 32 usable interviews.
- 17.U.S. Software Engineer Talent LandscapeLinkedIn Economic Graph · Feb 2026
- 18.State of Tech Talent Report 2026SignalFire · Jun 22, 2026 · VC-firm data weighted to 12 big tech companies.
Facts last checked Oct 20, 2026. Vendor surveys are labelled as such, and our own recommendations are marked as ours. Spot something out of date? Tell us.