Interview rounds
Explaining AI mistakes to a non-technical executive: words that keep the project alive
When a non-technical executive asks why the AI got it wrong: an explanation that keeps the project alive, with bad and good wording side by side.
FDE interview rounds, explained, page 2
One round at a time: what it asks of you, what employers say about it, and how to practice it out loud.
Posts 13 to 24 of 43.
Interview rounds
FDE online assessments: HackerRank, CodeSignal and AI-run screens, and how to prepare for each
FDE online assessments on HackerRank, CodeSignal, CoderPad and AI-run screens: what employers publish, what candidates report, how to prepare.
Interview rounds
Fine-tuning vs RAG vs prompting: the decision an interviewer wants to hear you make
When a customer says ‘just fine-tune it’: how to choose between fine-tuning, RAG and prompting, with worked scenarios and the words to explain your call.
Interview rounds
Forward deployed engineer take-homes: what real prompts ask for and how to scope yours
What published and candidate-reported FDE take-home prompts ask for, the deliverables they share, and how to scope yours to the time box.
Interview rounds
How to answer ‘why FDE?’ so it survives the follow-up questions
‘I like customers and code’ invites a harder follow-up. Three weak answers to ‘why FDE?’, why each breaks, and a rewrite built on something you did.
Interview rounds
How to answer open-ended technical interview questions without rambling
A time-boxed structure for open-ended technical interview questions, with the exact transition sentences and a worked example, so you stop rambling.
Interview rounds
How to build a golden set for LLM evals when the customer has no labeled data
The customer wants proof and has no labels. Build a golden set from real traffic: stratified sampling, expert labels, agreement checks and versioning.
Interview rounds
How to tell a customer the project is late: the interview answer and the real email
A structure for telling a customer the project is late: the spoken answer, the follow-up email, and the phrases that make it worse.
Interview rounds
LLM evaluation in the interview: how to answer ‘how do you know it works?’
The demo looks great, then the interviewer asks how you know it works. A full answer names the metric, the data, the baseline, the result and monitoring.
Interview rounds
LLM-as-a-judge: the failure modes to name before the interviewer does
Position bias, verbosity bias, self-preference and rubric drift: the LLM-as-a-judge failure modes, and how to check a judge against human labels.
Interview rounds
Palantir decomposition interview example: a full walkthrough of a reported prompt
A full walkthrough of a Palantir decomposition prompt one candidate reported, built on London taxi data, with what to say out loud at each step.
Interview rounds
Palantir’s learning interview: how to learn a new concept on the spot, out loud
In Palantir’s learning interview you are taught something new, then use it in code. What Palantir publishes, what candidates report, and how to practice.
Start with a guide
Every post belongs to a longer guide. Each guide covers its topic whole.
- The decomposition interview: how to break down a vague customer problem
- The forward deployed engineer interview, round by round
- The forward deployed engineer resume
- Forward deployed engineer salary: what employers post and file
- Forward deployed engineer vs sales engineer
- Forward deployed engineer vs software engineer
- Forward deployed engineer vs solutions architect
- What is a forward deployed engineer?