Aakash Gupta Profile picture
Jul 16 โ€ข 7 tweets โ€ข 2 min read โ€ข Read on X
>50% of PM interviews now ask metrics questions.

But not all metrics questions are the same.

5 categories + 16 sub-categories to know: Image
๐—ฆ๐˜‚๐—ฐ๐—ฐ๐—ฒ๐˜€๐˜€ ๐— ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฐ๐˜€ (๐Ÿฎ๐Ÿญ% ๐—ผ๐—ณ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€)

Three major flavors here:

Product launch success: Measuring launching GPT-5.

Feature success: Measuring a mobile payment feature.

Business model success: What would you look at if we launched a marketplace?
๐——๐—ถ๐—ฎ๐—ด๐—ป๐—ผ๐˜€๐˜๐—ถ๐—ฐ๐˜€ (๐Ÿฎ๐Ÿฎ% ๐—ผ๐—ณ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€)

Investigating issues when metrics drop.

Sudden drops: IG Stories dropped 5% overnight. Approach?

Gradual declines: Monthly retention declining 6 mos. Why?

Unexpected changes: Feature 30% โ†’ 60% engagement. WDYD?
๐—˜๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป (๐Ÿญ๐Ÿต% ๐—ผ๐—ณ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€)

A/B testing and measurement strategy.

A/B test design: How design A/B test for new onboarding flow?

Measurement strategy: Testing social feature, etc

Statistical rigor: A/B results show conflicting signals?
๐— ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฐ ๐——๐—ฒ๐—ณ๐—ถ๐—ป๐—ถ๐˜๐—ถ๐—ผ๐—ป (๐Ÿฎ๐Ÿฐ% ๐—ผ๐—ณ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€)

Defining metrics to measure success:

- User engagement on video (engagement)
- Customer support success (business)
- Search relevance (technical)
- Fortnite's new season launch (design)
๐—ง๐—ฟ๐—ฎ๐—ฑ๐—ฒ-๐—ข๐—ณ๐—ณ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ (๐Ÿญ๐Ÿต% ๐—ผ๐—ณ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€)

Balancing priorities and constraints:

1. Increase premium revenue, how measure trade-offs?
2. Lower signup friction attracts worse users, evaluate?
3. Slow app to add complex feature, evaluate trade-off?
A lot of people get good at 1-2 types (eg success metrics + diagnostics) but they aren't good at all 5.

Make sure your practice covers every type.

Should I share all my interview cheatsheets?

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More from @aakashg0

Jul 17
There's a new PM interview in town.

But most PMs don't know it yet.

Last week, a PM messaged me in panic:

"I just got destroyed in a Google interview. They wanted me to prototype something with AI tools. I'd never even heard of 'vibe coding' before."

Here's what happening:
This isn't isolated. I'm coaching more PMs who are blindsided by this new interview format every week.

Here's what's happening behind the scenes:

The nature of the PM role is undergoing its biggest shift in years.

We're now moving to the era of AI PMs.
Companies are looking for PMs who can:

1. Build AI features (understanding evals & tech details)
2. Use AI to focus on high-leverage tasks
3. Prototype with AI tools like pros

And their interviews are changing to match.

At Google, this is only in India (for now).
Read 6 tweets
Jul 14
Context engineering is the new prompt engineering.

Here's everything you need to know: Image
1. Etymology

It's unclear who coined the term, but two folks have been particularly important in its rise:

Andrej Karpathy and Dex Horthy.
2. What It Is

It's all about thinking beyond the prompt - thinking about ALL of the tools you have to drive success.

5 are the most important to understand:

a. RAG
b. Memory
c. State/ History
d. Prompt Engineering
e. Structured Outputs
Read 8 tweets
Jul 11
Which is it: use LLMs to improve the prompt, or is that over-engineering?

By now, we've all seen a 1000 conflicting prompt guides.

So, I wanted to understand:

โ€ข What do actual studies say?
โ€ข What do experts at OpenAI, Anthropic, & Google say?

Here are the answers: Image
I spent the past month in Google Scholar, figuring it out.

I firmed up the learnings with Miqdad Jaffer at OpenAI.

Some of my favorite takeaways from the research:
1. It's not just revenue, but cost

You have to realize that APIs charge by number of input and output tokens.

An engineered prompt can deliver the same quality with 76% cost reduction.

We're talking $3,000 daily vs $706 daily for 100k calls.
Read 10 tweets
Jul 5
If you're preparing for PM interviews in 2025, there's one question type you cannot afford to mess up: Metrics.

Here's the history of how it over took product hiring and why it's the silent killer of PM dreams: Image
PMs have been getting hit with questions like these...

And while theyโ€™re not as sexy as product sense or design...

Theyโ€™ve quietly become non-negotiable in most interviews. Image
So, what happened?

In the late 2000s, Big Tech needed a way to simulate real PM work...

- Something they could ask in 45 minutes
- That showed judgment under pressure
- And gave them clean signals across a large candidate pool.

Metrics interviews were perfect.
Read 9 tweets
Jun 26
Jira Product Discovery (JPD) just launched their biggest update yet.

It will take them from 18K โ†’ 36K customers.

Hereโ€™s why I think so: Image
1. From Teams โ†’ Teams of Teams

I covered Jira Product Discovery (JPD) earlier this year.

They were really good for a product team.

Now, with this monthโ€™s launch of Premium, they are really good for multiple product teams.

This is a huge unlockโ€ฆ
2. The Lack of Standardization Problem

For a Head of Product or CPO that has multiple things they are taking care of, itโ€™s hard to get a central view of everything.

Everyone has a slightly different roadmap template.

JPD allows you to centralize all of that!
Read 9 tweets
Apr 21
AI prototyping has changed what it means to be a PM, designer, and engineer in forward-thinking organizations.

Here's how: Image
The Old Way

Hereโ€™s what most product development lifecycles look like:

1. Ideation

Most teams barely prototype at the idea stage.

A rare few exceptional designers and PMs do (~5%)
2. Planning

Here, more teams use prototypes, but it still is an exception few (~15%), while sketches and mockups are much more common (>75%)

3. Discovery

In more empowered companies, many teams would test prototypes in the discovery phase (~50%)
Read 10 tweets

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