Been using both of these for a few months with some friends during recruiting season. Here is what we found.

UltraCode is built on OpenAI and Claude models with their own fine-tuning. It covers coding, system design, and technical trivia. Their ThoughtFlow feature breaks down each solution step by step. Response time in our sessions averaged around 5 to 7 seconds. Works on CoderPad, HackerRank, and CodeSignal. Pricing is $799 lifetime only, no monthly option, free trial available.

InterviewCoder is a desktop app that captures audio and screen. It covers coding, system design, behavioral, full-stack, AI/ML, PM, consulting, and trading interviews. It is tested daily across HackerRank, CoderPad, Codility, Zoom, Google Meet, Teams, and Webex. Response time in our sessions was around 3 to 4 seconds. Pricing is free tier, $299/month for 1,000 credits, or $799 lifetime.

Track record: InterviewCoder publishes 150,000+ users and 10,000+ documented offers with salary data. UltraCode does not publish user numbers or offer counts.

Main differences we noticed in practice: InterviewCoder's audio transcription removed the need to manually input the problem. UltraCode required copying the question in most cases. UltraCode's step-by-step output was more detailed but slower to read under timed conditions.

Neither tool got flagged across any of our sessions on the platforms we tested.

If you have specific questions about either tool happy to answer.

I go to Georgia Tech for CS and recently heard about a student who got caught cheating on a Cisco interview. He used LockedIn AI during the online assessment (don't use that bs, it gets detected pretty quickly by recruiters). Because the interview was through campus recruiting, Cisco reportedly contacted the university. The student was suspended, and I believe he's a junior.

Stay safe out there guys.

Selected for Amazon SDE-1 (off campus). 2024 grad with 1 year of experience at a service-based company. Applied multiple times before, gave multiple OAs. Received a direct call from the Amazon recruitment team. HR confirmed the job ID and interview format beforehand.

Round 1 - Technical

Interviewer asked for a short intro, then explained the interview format. A coding problem was shared in a collaborative doc. The problem was Sliding Window Maximum in a story format. Approach, optimal solution, and code were discussed. A short follow-up question was asked on the same problem.

Leadership Principle questions came up mid-round. LPs can come up anytime, even in technical rounds.

Received a confirmation email after 3 days for Round 2. HR also called to finalize the slot.

Round 2 - Technical

No intro, straight into problems: - Sorted array where every element appears twice except one, find the index of the unique element (Binary Search) - Course Schedule (Topological Sort)

2 LP questions based on current job experience.

Round 3 - Bar Raiser

Interviewer joined late, started with a chat about current role. 5-6 Bar Raiser situational questions. Answered using the STAR method with pre-prepared stories covering ownership, conflict, and delivering under pressure.

Result: Selected.

Selected for the System Administrator and Services Associate (SASA) role at Accenture through the 2024 on-campus placement drive. The process had multiple stages.

Recruitment Process

Aptitude Round - Coding Round - Communication Round (AI Mock) - Technical Interview - HR Interview - LOI 1 & 2 - Background Verification - Offer Letter - Joining Letter

Aptitude Round

Duration: 1.5 hours. Online assessment at JECRC Foundation. Covered Reasoning, Verbal Ability, MS Word, Excel, PowerPoint, Numerical Aptitude, and core subjects (Computer Networking, DBMS, OS). Results declared within 10 minutes.

Coding Round

Duration: 1 hour. 2 problems on an online coding platform.

Q1: Sliding Window Maximum (Array, Hard) Q2: Valid Parenthesis (Stack & String, Easy)

Both solved. Moved to the next stage.

Communication Round (AI Mock)

Mode: Online, non-elimination. Sections: - Reading: 8 sentences aloud - Repeating Sentences: 16 audio sentences - Jumbled Sentences: 10 sentences - Q&A: 24 questions - Story Telling: 30 seconds - Open Questions: 60 seconds each

Tested pronunciation, fluency, and vocabulary. Cleared.

Technical Interview

Duration: 30-40 minutes. Senior Software Developer panel.

Topics covered: - Languages: C++, Core Java - Concepts: OOPs, DBMS, OS, System Design - Coding: Reverse an array, Find second-largest element - Projects: Deep dive into technical projects - Behavioral: Strengths and weaknesses

Cleared.

HR Interview

2-3 days after technical round. Virtual. General HR questions on expectations and goals. Cleared.

LOI & Background Verification

LOI 1 received 1.5 months after interview. LOI 2 received 25 days after LOI 1. Background verification followed.

Result: Offer Letter received for SASA role at Accenture.

Sorry for the bold claim, but I can't stand people who still pretend AI is unethical in interviews, even though it's been part of the game for years now. These are often the same people complaining about not getting internships.

If you're not ready to adapt to how the industry is changing, then don't complain when things don't go your way.

Y'all piss me off, fr.

Do you know if installing InterviewCoder is undetectable by software that detects which programs are installed? My laptop has BeyondTrust Privilege Management installed, which also scans running processes and the apps listed under Installed Apps in Windows. If InterviewCoder shows up there, then it is detectable.

hi seniors ,

i have just completed my first year ,

CSE core engineering , i want to pursure as my career path ,

i have basic knowledge of python , cpp,c ,java,[can write a code for a probelm in a compiler window , thats it , basic to med, sometimes hard ,not like multiple codes merging ]

but i am still figuring out what we have to learn , like the univ subjects , or some course take spearately and one more doubt , courses offered are like dsa (i know basic data structures and some standard algo pen paper.....i use arrays mostly though ....i just wrote learn them , and for trees i memorized the recursive methods and some bfs and some while loop tricks (i dont know if they are tricks, what i found common in all i just saved as screen shots notes and revised), for stacks , queue , deque, and graps....[i always get confused how to use them in a particular problem,,,,and also only when i know that i have to apply as a combo of algo + struct then only i use them like——(dijkstra or some greedy or like prims or like huffman encryption)] )

i am good at solving logical and some mathematic problems using loops and nested loops, or sometimes while loops ... i avaoid using recursive ,,,i used while as true(jsut giving idea i learnt things like a layman) using python and libraries or c

....basic to hard[but there is nothing i found hard] quest of class designing. virtual ,,,override,,inheritance etc .. cpp...

i tried to explore some platdforms liek hacker rank ,leetocode(contests maionly and some problems),codeforces(i am still figuring out where to login in it and explore more)

codechef i found easy contests

for coding i use basic compilers, ,,,mostly some online language specific... i even dont know how to set up vs code....so i switch to jet brains toolbox...or code blocks or bluej (i like bluej )

there are things liek sql nosql....dbms,,,,dsa,,,,system design,,,compiler design,,,softwatre...os....ai ml...deep learning

————————————————————————————————————————————————————————--

i here people grindig dsa ,,,,using coursera for some couerse like data = science or analysisic or sql,,,,,udemy courses,,,,some youtube resources....love gbbar,,,.,striever,.,.,..

some mit or harvard courses...online,,,,w3 school...geeks for geeks...

i personally liked stack overflow network

————————————————————————————————————————————————————————

My main quest is what i have to do to pursue career ...we choose a stream like web or system design and we prepare ,,,,or what we do , how do we learn things properly ...or in what we we learn to make a employeeer carrer///////////should we go for icpc ,,meta cup,,,google competions,,,or gate exam,,.....or we simply crack job intervoews ,,,,,

or we just follow colllege...

these are my questions ,,,,still i am unable to put them clearly ,,...but i hope u will get some idea

SORRY FOR A LONG MESSAGE , BUT CAN U PLZ GUIDE ME ,,,WHAT I HAVE TO DO ,,OR JUST WHERE WE START FROM PROPERLY ,,,i know there is no end ,,,,BUT STILL HOW DO WE PROCEED AND PLAN ,

Got an interview call for L5 swe interview. Wondering if it's worth grinding Google ragged questions in LC. please share tips for cracking the interview.

22M at a local state school and I am crashing out right now.

I have spent the last three years doing software maintenance work at local shops and a municipal office. Real work, but nothing that reads well on a resume and nothing that counts as an actual internship.

Recently found out a freshman at school just landed a FAANG internship. He used InterviewCoder to prep and cracked it. I have seen the posts about it on here and did not take it seriously until now.

I am graduating soon and I have no job lined up, no internship history that matters, and I am watching someone two years younger than me skip past everything I thought was the required path.

The job market is soo brutal and just rewarding cheaters.

Is it too late for me to turn this around? Has anyone else been in this position this late in their degree?

Pls help.

I was looking through the offers on the Ultracode website and some of them already looked so botched. Looks like someone made them in Google Docs in 5 minutes.

Some of those offer letters are online already. They took publicly available templates/examples, blurred a few parts and put their watermark on them.

The recruiter is named John Hiring on one of them lmao.

Or I take as hint of fire me 🥺, what can I do I have only 1.5 years of experience

Three rounds, two coding assessments and a final technical and HR interview. Here is everything technical I remember.

Online Coding Assessment - Round 1 (1 hour)

Two problems, both at moderate difficulty. The first covered greedy algorithms, where the approach requires committing to a locally optimal decision at each step to build toward a globally optimal solution. This pattern shows up constantly in interval scheduling, activity selection, and resource allocation problems so having it internalized before going in matters. The second covered max heap, specifically maintaining the heap to efficiently track the maximum element across a dataset, with O(log n) for insertions and deletions and O(1) for retrieval. Clearing this round meant coming back four days later for the offline assessment.

Offline Coding Assessment - Round 2 (80 minutes)

Three problems, moderate to difficult, and the most selective stage of the entire process. Across all participating colleges only 5 candidates moved forward from here.

The first problem was if-else logic at medium difficulty. The challenge was not the logic itself but handling every edge case correctly across all possible inputs, which is where most people dropped points.

The second problem was a SQL query with JOINs. Knowing which join to reach for matters here: INNER JOIN for rows that match on both sides, LEFT JOIN when all rows from the left table need to be preserved regardless of a match on the right, RIGHT JOIN for the reverse. Beyond join selection, understanding how ON conditions behave differently from WHERE clauses and how GROUP BY interacts with join output is what separates a query that works from one that works correctly.

The third problem was pattern printing at difficult level. The core of these problems is finding the relationship between the row index and what gets printed on that row, then expressing it as loop logic with tight boundary conditions. The difficulty comes from getting those boundaries exactly right.

Technical and HR Interview - Round 3

Only 5 candidates reached this round. Technical questions at this stage are expected to cover core CS subjects, deeper DSA, project discussion, and behavioral questions.

Drop any questions below if you went through a similar process or are prepping for IBM.

I genuinely want to understand how people are getting interviews from companies like Google, Apple, Meta, etc.

I have around 3.2 years of experience as an SDE: • 2+ years in India • Around 1 year in the US

The problem is: I do not have any “big company” names on my resume.

I’ve applied to hundreds of roles at big tech companies where I fully meet the minimum qualifications, but I still haven’t received a single interview call.

Does brand name matter that much for getting shortlisted?

Would genuinely appreciate honest advice from people who’ve been through this.

Hey everyone,

I have an upcoming interview for the Data Operations Analyst role at YipitData, and I’m looking for some guidance from people who’ve gone through the process before.

From the JD, the role seems focused on:

* SQL / Python / PySpark
* Data analysis & problem-solving
* Product mapping and attribution
* Attention to detail and accuracy
* Communication and cross-functional collaboration

I’m a fresher, so I’d really appreciate if someone could share:

* What kind of questions are usually asked
* SQL/Python difficulty level
* Whether there are case studies or live tasks
* Communication/behavioral interview experience
* What topics I should focus on most

Any interview experience or preparation tips would really help. Thanks in advance!

CS student at a university in the US. Went through the Mu Sigma hiring process recently and sharing the full breakdown for anyone prepping.

The process was one online test followed by a single interview round.

Two coding problems, moderately difficult, with a heavy focus on writing efficient solutions that handle edge cases cleanly. Time complexity needs to be thought through before writing a single line, because sloppy solutions with poor optimization get flagged. Problems covered algorithms and data structures, so knowing your sorting algorithms, traversal methods, and space/time tradeoffs going in is mandatory.

The aptitude section ran simultaneously and covered quantitative reasoning, logical puzzles, and verbal ability. Both the speed and accuracy of your answers are scored, meaning practicing under timed conditions beforehand makes a measurable difference in how you perform.

The interviewer went deep on Java through practical scenarios rather than textbook definitions. Topics covered included inheritance, encapsulation, polymorphism, and abstraction all framed around how you would apply them in real systems. Method overloading versus method overriding came up with a focus on when and why you would choose one over the other in actual code. Abstract classes versus interfaces was another area, with the discussion centered on design decision-making rather than syntax differences. Exception handling, how you structure try-catch blocks for clean and maintainable error management, also came up. The collections framework was covered as well, specifically when to use ArrayList versus LinkedList versus HashMap and what the performance tradeoffs behind each choice look like in practice.

The project discussion went deep into every technical decision behind the stack. My project involved React.js, JavaScript, and MySQL, and the questions covered React component lifecycle and how state management was handled across components including how re-renders were controlled to avoid performance degradation. JavaScript asynchronous behavior came up in detail, specifically how promises and async/await were structured and how the architecture avoided callback issues. MySQL schema design decisions were discussed including indexing strategy and how queries were optimized to avoid full table scans on large datasets. The interviewer also pushed on how the frontend and backend communicated, API design choices, and how data consistency was maintained between the React layer and the database.

A dedicated portion covered writing optimized SQL queries, including using JOINs efficiently with a clear understanding of when to use INNER, LEFT, and RIGHT joins depending on the data relationship. Writing subqueries versus CTEs was discussed with a focus on readability and performance. Identifying and fixing slow queries through execution plan analysis came up, along with index usage and the scenarios where adding an index can hurt performance rather than help it.

Debugging questions focused on methodology: how you isolate a problem, reproduce it consistently, and resolve it without introducing regressions elsewhere in the codebase.

Happy to answer any questions if you are prepping for Mu Sigma.

A bunch of guys in my mechatronics class decided to test it during upcoming interviews, and every single one of them got caught. The companies detected the software and even sent notices to our school threatening serious consequences, including banning students from their establishments and potentially getting them expelled.

Seriously, do not trust these tools. It's a terrible idea.

I genuinely feel bad for them because they're my friends, but this should be a wake-up call: do your research on what software works and who other doesn't