Aakash Gupta Profile picture
Apr 30, 2023 20 tweets 9 min read Read on X
The last 45 days have been the biggest ever in AI.

All of this happened:

GPT-4
Auto-GPT
Midjourney v5
Runway #Gen2
Viral Drake Songs
ChatGPT in Robots

Here are the key takeaways from a crazy month and a half in AI 🧵
March 14: GPT-4

We were already collectively losing our minds over GPT-3.5. Then, GPT-4 dropped 🤯

@skirano created pong the very same day.

March 15: Midjourney v5

After having our minds blown by GPT-4's code and text, the very next day @midjourney v5 dropped.

The photorealism was unreal from the get-go. @DotCSV created the iconic sad Darth Vader drinking a Coke. Image
@juliewdesign_ showed us its full power a few days later.

March 20: Runway Gen2

After having our minds blown by text and image, video was next.

@runwayml released the next generation of its excellent text-to-video model.

@ChristianF369 showed us just how powerful the tool can be.

March 30: AutoGPT

We thought there wasn’t going to be another modality to wow us until AutoGPT dropped.

It uses GPT to write itself tasks.

And days later @SigGravitas added code execution.

Autonomous AI became a reality.

April 4: Heart on My Sleeve Released

After text, code, image, and video, what was left? Audio!

We completed the circle on all forms of creative media when TikTok user ghostwriter977 spawned the viral song of the year.

And then he did it again with a Bad Bunny x Rihanna drop.

The music labels have been reporting videos 24 hours a day to take them down.

April 17: DINOv2

We didn't just see advancements in generative AI. We also saw advancements in computer vision.

Meta released mind-blowing transformers to identify moving objects.

April 20: WebGPT

19-year-old genius @willdepue released a way to run chatGPT natively in your browser.

@SullyOmarr explained how this tech opens up the door for a massive play by Apple.
April 25: GPT Robots

Just when we thought the innovation had to slow down, Boston Dynamics put ChatGPT into their robot dog Spot.

Compelling AI in our homes looks closer than ever.

Bonus: #NeRFs took off

Although not released in the last month and a half, #NeRFs powered by @LumaLabsAI did take off.

Artists like @karenxcheng showed us just how powerful the tech is.

I thought we just needed to take a step back in and look at it all.

We are in a Cambrian explosion of AI advancement.

Language
Imagery
Music
Video
Code

Everything's moving at exponential speed - and accelerating.

What a time to be alive.
Want to go the layer deeper - The Midjourney story? The Runway story?

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This thread took half of my Saturday to write.

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Here's all of that in an image: Image

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More from @aakashg0

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

Here’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
Apr 17
OpenAI released that there will be 5 levels of AGI.

If you want to build the future of AI, you should deeply understand it.

We are just crossing step 2 of 5 to AGI.

Yet, somehow, teams are still building like we are in levels 1 or 3.

Let me explain: Image
LEVEL 1: CONVERSATIONAL AI

Remember those awkward chatbots from 2019?

They sounded human...until they didn’t.

You’d ask for help…
They’d return gibberish.
That’s Level 1.

Might be useful but it can't be your strategic moat.
LEVEL 2: REASONING AI

This is where we are right now and it’s the real unlock.

Today’s top models (like GPT-4.1, released this week) can:

→ Break down complex problems
→ Think like PhDs
→ Make sense of ambiguity
→ Power analytics, personalization & decision support
Read 7 tweets
Feb 24
I've seen my fair share of product development processes.

JPD's approach stands out as particularly principled and well thought out.

Here are the five most important things about how they build product: Image
𝗙𝗮𝗰𝗲𝘁 𝗢𝗻𝗲 - 𝗧𝗵𝗲 𝗟𝗶𝗴𝗵𝘁𝗵𝗼𝘂𝘀𝗲 𝗣𝗵𝗶𝗹𝗼𝘀𝗼𝗽𝗵𝘆

As Catalin Bridinel, Head of Design, explains:

"The product is a ship, and the user is a lighthouse that gives you direction."

This is more than a cute metaphor - it's a fundamental operating principle.
It manifested, for instance, in the early access program stages:

Step 1 - Deep dive with 10 carefully selected customers
Step 2 - Expand to 100 customers for broader validation
Step 3 - Then 1000 and GA

And it does in a million little other ways.
Read 13 tweets
Feb 14
Most people are still prompting wrong.

I've found this framework, which was even shared by OpenAI President Greg Brockman.

Here’s how it works: Image
𝗧𝗵𝗲 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴

4 words in lowercase doesn’t work.

If you want to write a PRD, or a product strategy, or something for work, you have to help the LLM get your context.

This is done in 4 parts.
𝗢𝗻𝗲 - 𝗚𝗼𝗮𝗹

LLMs know millions of ways to complete a task.

Clear goal language helps them narrow in on the way you want them to.

EG: “I want to create a Google-level Product Requirements Document for: <Feature>”
Read 9 tweets
Jan 26
We’ve been sold a million use cases for PMs to use AI.

For my money, here are the top 5: Image
AI won’t replace PMs.

But PMs who use AI will replace PMs who don’t.

You don’t even need to learn coding to join the AI revolution.

There’s one archetype taking over in organizations right now: the AI-powered PM.

Here are the top 5 ways AI-powered PMs are changing the game: Image
USE CASE ONE - PRDs

Last month, I shadowed a PM at a FAANG company.

Their first AI prompt? Beautiful but completely wrong.

So how you use it matter more than just using it to write PRDs.

Here’s the game-changing mega-prompt that fixed it:
Read 13 tweets
Dec 31, 2024
Used right, OKRs can be the most powerful product process.

But most orgs completely mess them up.

From driving empowerment to becoming tools for control…

Here’s what you need to know about when to add or remove OKRs: Image
𝗧𝗵𝗲 𝗗𝗲𝗯𝗮𝘁𝗲 𝗔𝗿𝗼𝘂𝗻𝗱 𝗢𝗞𝗥𝘀: 𝗔 𝗗𝗲𝗲𝗽𝗲𝗿 𝗧𝗿𝘂𝘁𝗵 𝗔𝗯𝗼𝘂𝘁 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁

The conversation around OKRs reveals a fundamental truth:

Alignment mechanisms aren’t one-size-fits-all.

Take Ramp, for example.

They built a $10B company without OKRs.
Their secret?

→ Exceptional product sense.

→ Metrics so clear that every team understood what success looked like without needing a formal framework.

Now look at Google.
Read 14 tweets

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