Long-form guides for your interview prep

How to prepare for agent SDK developer interviews covering tools, planning loops, computer use, evals, safety, and production agents.

A clear comparison of AI-assisted builders and full-stack engineers, with hiring signals, interview expectations, and skill gaps.

What AI engineer interviews test in 2026, including LLM apps, RAG, evals, tool calling, system design, and production tradeoffs.

How to prepare for AI red team interviews covering model misuse, prompt injection, safety evals, threat modelling, and reporting.

How to use LLMs for interview practice, mock loops, coding drills, behavioural stories, and policy-safe preparation in 2026.

A realistic eight week plan for learning data structures and algorithms for coding interviews, with what to study each week, how to practise, and how to avoid grinding without progress.

A detailed breakdown of the STAR method for behavioral interviews, with timing, full sample answers, and the mistakes that make answers fall flat.

A practical guide to STAR, SBI and CAR, when to use each framework, and how to make behavioural answers sound specific and credible.

How to interview well when you are moving into tech from another field, covering how to frame past experience, close skill gaps, and handle the doubt questions.

A realistic guide for bootcamp graduates, career changers, returning parents, and non-tech professionals moving into tech roles.

The handful of recurring patterns behind most coding interview questions, with how to recognise each one and a worked example for the common ones.

A YMYL-safe framework for understanding tech compensation, reading salary bands, handling offers, and negotiating without fake scripts.

How to handle data scientist case study rounds, from framing a business problem to experiment design and communicating results, with worked structure and common pitfalls.

How to prepare for DevOps and site reliability engineer interviews across Linux, CI/CD, infrastructure as code, reliability, and incident response, with examples and the signals interviewers want.

A candidate-first guide to forward-deployed engineer roles, interviews, customer work, travel, technical scope, and career tradeoffs.

How to prepare for frontend coding interviews, from core JavaScript behaviour to building a small React feature live, with worked examples and the signals interviewers look for.

A practical, printable interview preparation checklist for tech candidates: what to do four weeks out, the week before, the night before, and the morning of. Free, no signup.

Concrete techniques to manage interview nerves before and during technical interviews, so anxiety stops costing you rounds you could pass.

A practical week-by-week plan for running mock interviews that build real skill, fix blind spots, and prepare you for coding, system design, and behavioural rounds.

How to follow up after an interview in a way that strengthens your case, from thank-you notes to chasing a slow response without being pushy.

A focused guide to passing the technical phone screen, covering setup, communication, common formats, and the mistakes that get strong engineers cut early.

A week-by-week plan for preparing for technical interviews, from foundations and stories to practice and final logistics, with a realistic weekly workload.

A grounded guide to dealing with interview rejection, learning what you can from it, and turning each setback into better preparation for the next process.

A calm guide to the warning signs worth noticing during a hiring process, from the recruiter's first message to the final round, and how to weigh them.

A practical checklist for the day of an onsite interview, covering planning, what to carry, how to handle a multi-stage loop, and how to leave a good final impression.

A focused process for researching a company before an interview, from the product and the people to the questions that show you did the work.

A factual approach to finding salary ranges for a role before you interview, using public data sources and reading the numbers in context.

A practical setup guide for remote and video interviews, covering your tech, environment, camera, audio, and how to handle problems when they happen.

How to ask questions that show judgement and help you evaluate the role, with patterns tailored to the recruiter, the hiring manager, peers, and senior leaders.

A practical guide to how reference checks work in a tech hiring process, who gets contacted, what they are asked, and how to prepare your referees.

Learn to spot the unspoken signals in a job description, from urgency and team health to interview style and growth, so you apply with eyes open.

Learn how to decode seniority, scope, red flags, compensation clues, AI policy, and interview risk from a tech job description.

How to prepare for machine learning engineer interviews across ML fundamentals, coding, ML system design, and deployment, with concrete examples and the tradeoffs interviewers expect.

How to clean up your GitHub and portfolio before interviews so reviewers see real engineering judgement, not abandoned tutorials and messy commits.

A repeatable framework for product manager case interviews, covering product design, strategy, and metric questions, with worked structure and the judgement interviewers reward.

A practical comparison of prompt engineering and LLMOps, with responsibilities, interview signals, skills, and transition paths.

A practical guide to finding remote tech roles after return-to-office, with filters, evidence, recruiter scripts, and interview signals.

The SQL and analytics questions that come up most in interviews, from joins and window functions to metric design, with worked queries and the reasoning interviewers want to hear.

A working method for backend system design rounds, covering data modelling, consistency, queues, and the failure cases interviewers push on, with concrete examples.

How senior engineers should prepare for system design rounds, from scoping requirements to defending tradeoffs, with a repeatable structure and concrete examples.

A practical Twitter clone system design guide covering requirements, timelines, fanout, storage, caching, APIs, and interview tradeoffs.

A practical playbook for take-home coding assignments, covering scope, time management, what reviewers actually grade, and how to present your work.

How employers detect LLM-generated take-homes and how candidates can do honest work that proves real engineering ability.

How to handle modern take-home projects, time-box scope, use AI honestly, prepare for follow-ups, and avoid unpaid-work traps.