Aakash Gupta Profile picture
May 24, 2023 11 tweets 5 min read Read on X
Is this Google's most genius strategy yet?

Big Tech 101 has always been to steal the best product ideas built atop your platforms.

But kneecapping Calendly under the guise of security takes it to a whole new level 🧵 👇 Image
What was the secret sauce of Calendly?

It was the easiest meeting booking experience out there.

Meetings, once booked, were automatically added to your calendar.

It was magic.
This new feature from Google completely ends that magic.

By not automatically adding the meetings to your calendar, Google is causing missed meetings!

It's especially brutal if you don't have time to open the email.

I myself have missed meetings from for this reason 🤦
Why is Google doing this?

To support Google's newly released paid competitor to Calendly - Appointment Scheduling.

At $9.99, it's the same price as Calendly.

So Google has gone from competing on price (free) to going for money.

As a result, it can't afford to have a soft GTM.
The genius of what Google has done is they have put this block to users under the guise of security.

Google showed this screen to you a few weeks back.

Remember it?

If anything, most of us thought it was about competing vs Apple on privacy.

No one tied it back to Calendly. Image
The traditional example of Big Tech 101 is something like the flashlight app on iOS.

Apple added flashlight to its OS, but it didn't actively block the flashlight apps.

There was a flashlight app that 1/3rd of Japan had downloaded.

It got totally wiped out. Image
But Google is taking 'wipe out' to another level with this active blocking of Calendly.

It's gone ahead and wiped out the scheduling experience for prominent companies like:

· Calendly
· ChiliPiper
· GoodTime

And a host of other VC-backed startups:
This may actually be a regulatory risk for Google (as @michaelglena highlighted).

It's a particularly egregious form of using their free Google Calendar product to crowd out other scheduling tools.

The FTC or Justice Department could get involved.

From the FTC website:
And if there's anything that's characterized post-layoffs Sundar, it's bold bets.

So he could've gone bold here.

But - honestly, I expect him to have taken every effort to minimize legal risk in the details of this launch.

He was a PM after all.

Some of the things I have noticed in his details to minimize legal risk:

1. Not selectively targeting Calendly
2. Keeping Google Calendar free
3. Making it “1 click” friction

All of these things should help.

They certainly helped Google in many other suits under Sundar.
So - the likely scenario from 1 year from now is the the appointment market will begin to look like browser market.

With Google Chrome replaced by Google Appointment Scheduling.

(Don't forget - Sundar was the original PM on Google Chrome.) ImageImage

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More from @aakashgupta

Mar 20
Evals are the new PRD.

The companies building AI products that actually work are running 12.8 eval experiments per day. Here is the playbook with @ankrgyl, Founder and CEO of @braintrust ($800M valuation, behind Vercel, Replit, Ramp, Zapier, Notion, Airtable):

⏱ 1:43 Why vibe checks stop scaling
⏱ 6:35 Evals are the new PRD
⏱ 8:45 The Claude Code evals controversy
⏱ 18:48 Building an eval live from zero
⏱ 29:51 Connecting Linear MCP and iterating
⏱ 39:12 Why you need evals that fail
⏱ 43:36 Offline vs online evals
⏱ 47:40 Three mistakes killing eval culture

The core framework: every eval is exactly three things. A set of inputs your product needs to handle. A task that takes those inputs and generates outputs. A scoring function that produces a number between 0 and 1.

We built one from scratch on camera. Score went from 0 to 0.75 in under 20 minutes.
@ankrgyl @braintrust YouTube:

@ankrgyl @braintrust Spotify:

open.spotify.com/episode/6AK7zQ…
Read 4 tweets
Mar 20
Cursor is raising at a $50 billion valuation on the claim that its “in-house models generate more code than almost any other LLMs in the world.” Less than 24 hours after launching Composer 2, a developer found the model ID in the API response: kimi-k2p5-rl-0317-s515-fast.

That’s Moonshot AI’s Kimi K2.5 with reinforcement learning appended. A developer named Fynn was testing Cursor’s OpenAI-compatible base URL when the identifier leaked through the response headers. Moonshot’s head of pretraining, Yulun Du, confirmed on X that the tokenizer is identical to Kimi’s and questioned Cursor’s license compliance. Two other Moonshot employees posted confirmations. All three posts have since been deleted.

This is the second time. When Cursor launched Composer 1 in October 2025, users across multiple countries reported the model spontaneously switching its inner monologue to Chinese mid-session. Kenneth Auchenberg, a partner at Alley Corp, posted a screenshot calling it a smoking gun. KR-Asia and 36Kr confirmed both Cursor and Windsurf were running fine-tuned Chinese open-weight models underneath. Cursor never disclosed what Composer 1 was built on. They shipped Composer 1.5 in February and moved on.

The pattern: take a Chinese open-weight model, run RL on coding tasks, ship it as a proprietary breakthrough, publish a cost-performance chart comparing yourself against Opus 4.6 and GPT-5.4 without disclosing that your base model was free, then raise another round.

That chart from the Composer 2 announcement deserves its own paragraph. Cursor plotted Composer 2 against frontier models on a price-vs-quality axis to argue they’d hit a superior tradeoff. What the chart doesn’t show is that Anthropic and OpenAI trained their models from scratch. Cursor took an open-weight model that Moonshot spent hundreds of millions developing, ran RL on top, and presented the output as evidence of in-house research. That’s margin arbitrage on someone else’s R&D dressed up as a benchmark slide.

The license makes this more than an attribution oversight. Kimi K2.5 ships under a Modified MIT License with one clause designed for exactly this scenario: if your product exceeds $20 million in monthly revenue, you must prominently display “Kimi K2.5” on the user interface. Cursor’s ARR crossed $2 billion in February. That’s roughly $167 million per month, 8x the threshold. The clause covers derivative works explicitly.

Cursor is valued at $29.3 billion and raising at $50 billion. Moonshot’s last reported valuation was $4.3 billion. The company worth 12x more took the smaller company’s model and shipped it as proprietary technology to justify a valuation built on the frontier lab narrative.

Three Composer releases in five months. Composer 1 caught speaking Chinese. Composer 2 caught with a Kimi model ID in the API. A P0 incident this year. And a benchmark chart that compares an RL fine-tune against models requiring billions in training compute without disclosing the base was free.

The question for investors in the $50 billion round: what exactly are you buying? A VS Code fork with strong distribution, or a frontier research lab? The model ID in the API answers that.

If Moonshot doesn’t enforce this license against a company generating $2 billion annually from a derivative of their model, the attribution clause becomes decoration for every future open-weight release. Every AI lab watching this is running the same math: why open-source your model if companies with better distribution can strip attribution, call it proprietary, and raise at 12x your valuation?

kimi-k2p5-rl-0317-s515-fast is the most expensive model ID leak in the history of AI licensing.
Mandatory “find me on substack”

aibyaakash.com
“Babe, the man behind the first one man one billion dollar company reposted your tweet” 😲 Image
Read 5 tweets
Jan 28
If I were to learn PM again, I would start here.

15 steps to a PM job paying $200K+: Image
1. Understand the PM role

Start with how to break in: news.aakashg.com/p/how-to-break…

Watch Marty Cagan: open.spotify.com/episode/6KcmM7…
2. Learn PM fundamentals

Master PRDs: news.aakashg.com/p/product-requ…

Watch Dan Olsen: youtube.com/watch?v=sl7r3w…
Read 17 tweets
Nov 8, 2025
Senior AI PMs make $306K (US). Big tech pays $550K+

I analyzed 250 AI PM job postings.

Here's what hiring managers want: Image
1. AI Product Strategy & Lifecycle (94%)

Define product vision, strategy & roadmap for AI/ML features from 0→1 through scale:

• Quality Envelopes → Define accuracy thresholds
• Cascade Architecture → Right-size models
• SUQS Framework → Track success pillars
• Evals-First → Define success first
🔗 AI Product Strategy → news.aakashg.com/p/ai-product-s…
🔗 AI Prototype to Production → news.aakashg.com/p/ai-prototype…
🔗 AI Roadmaps → news.aakashg.com/p/ai-roadmap
🔗 AI Product Sense → news.aakashg.com/p/ai-product-s…
🔗 How to Build AI → news.aakashg.com/p/how-to-build…
Read 9 tweets
Oct 29, 2025
DUOLINGO COULDN'T TEACH ME HEBREW IN 2 YEARS

ChatGPT did it in just 3 months.

Here's the exact 8 Prompts I used:
1. Adaptive Daily Lesson Builder

"You're my personal Hebrew tutor. Build me a 20-minute lesson for today based on my current level [beginner/intermediate/advanced]. Include: 10 new vocabulary words with context, 1 key grammar concept with 3 examples, and 5 practice sentences I should translate. End with tomorrow's preview."
2. Real Conversation Partner

"Let's have a 10-minute conversation in Hebrew about [topic: weekend plans/work/hobbies]. Start each response in Hebrew, then add English corrections below using this format: '❌ You said X → ✅ Say Y (because Z)'. Adjust your Hebrew complexity to match my responses."
Read 9 tweets
Oct 26, 2025
In product management, not everything is straight forward maths, or solvable by AI.

Yet, some PMs still make better decisions most of the time.

How?

That's product sense: Image
"The ability to find the right solution for the user and business, despite limited and ambiguous information."

I love this definition from @Sid Arora.
You start with the PM process:

1. Take a vague & ambiguous problem statement
2. Create, or clarify the overall goal
3. Identify all users in ecosystem
4. Pick 1-2 users
5. Identify major problems of the user
6. Select the problems to solve
7. Brainstorm for solutions
8. Select the highest ROI solution
9. Build and deploy the solution
10. Measure success / collect feedback
Read 12 tweets

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