Generate viral LinkedIn posts in your style for free.

Generate LinkedIn posts
Gokul Rajaram

Gokul Rajaram

These are the best posts from Gokul Rajaram.

4 viral posts with 5,719 likes, 421 comments, and 133 shares.
0 image posts, 0 carousel posts, 0 video posts, 4 text posts.

👉 Go deeper on Gokul Rajaram's LinkedIn with the ContentIn Chrome extension 👈

Best Posts by Gokul Rajaram on LinkedIn

It’s been a great 6.5 years at Square; I’ve learnt a ton and grown as a person and a leader. Excited for the next adventure at DoorDash, along with the rest of the Caviar, Inc. team!
TIMEBOXING FOR PRODUCT LAUNCHES

In March 2003, we presented the launch plan for Google AdSense to Sergey Brin. I was proud of our well fleshed out plan, with a well designed product featuring self-serve sign-up, ad management, and reporting, supported by metrics and testimonials from beta partners who were already seeing success from it. We proposed a launch date of mid September.

Sergey’s succinct feedback: “No”.

“Sergey, what do you mean? We’re pretty confident we can launch an awesome, differentiated product.”

“The product looks great but it’s taking far too long. Launch it in June.”

“June?! That’s less than three months away!”

Sergey reiterated: “Team, I need this launched by June. I will support you and help you cut through any bottlenecks. I know you can do this.”

Fast forward to 3am on June 18, 2003. Our tech lead pushed code to production and formally launched Google AdSense. The launch was incredibly successful, resulting in one of the fastest growing Internet products to date.

To get the product launched within three months, Sergey employed a technique called timeboxing, imposing a hard deadline (3 months) as a constraint on product launch. At Amazon, Jeff Bezos employed the same technique, telling a SWAT team in late 2004 that he wanted them to launch Amazon Prime before Amazon’s earnings in February.

Why did two of the most consequential advertising / commerce products - ever - both launch through timeboxing? Because it works.

Timeboxing works for three primary reasons. First, it leads to improved prioritization. By limiting the time for a project, it forced us to decide what was most important to work on. I remember cutting large swathes of features and flows in one fell swoop to make the deadline. Ironically, many of those flows later proved redundant and were never built out. And this brings up the second reason - product editing. Cutting features leads to launching a simpler, leaner, better product. This process made me a staunch believer in the power of editing to build great products. Finally, timeboxing creates a sense of urgency, increasing efficiency. Since the launch date was fixed in stone, we couldn’t procrastinate; all timelines were clearly laid out working backwards from the launch date.

(Continued in comments)
How to present

In 2006, I helped Eric Schmidt create a deck outlining Google’s strategy, for a presentation Eric was delivering to the company. It taught me a profound lesson on how to present.

When I showed up to my first meeting with Eric, he asked me to visit with every product team at Google, chat with them to figure out what they were working on, and then summarize it on one slide (for each team).

Easy enough, I thought. I would use 3-5 bullet points per slide.

“But”, Eric said, “I want no words on any slide”.

My well-laid plans disintegrated in an instant. How was I supposed to convey the key messages from each team, without WORDS?

Eric must have seen the panic on my face, and kindly gave me a hint. “Put the text in speaker notes”.

“But what goes on the slides, Eric?” I continued panicking.

That classic, gentle “Eric smile” fluttered on his face. “Why, images, of course!”

“You mean, you want each slide to just be comprised of images?”

“You got it. And use the title wisely. 7-8 words max. Let’s meet in a week to review progress.”

Little was I to know that this conversation would fundamentally change my view on how to deliver effective presentations.

17 years later, I still cling tightly to the following principles:

1. The larger the audience, the fewer the words on the slide. In Eric’s case, the audience was thousands of employees, so we had 0 words per slide.

2. The title does most of the heavy lifting, which means it cannot be passive. It must be action oriented. Eg: not “Subscriber retention” but “Subscribers continue to be retained strongly”. even better “Net revenue retention continues to be > 100%”.

3. Use memorable images that substantiate the title phrase. This image is what will occupy most of the slide area, so you need to spend much of your time thinking about what picture will best get the point across. In some cases, it might be a customer image or logo. in other cases, a graph or something else entirely. For the Google presentation, the image that gave me the most trouble was a slide on Google Search Appliance and other Enterprise products. The final image was a mosaic of a bunch of consumer product logos with an icon that denoted large enterprises. Not my finest moment but it got the point across.

4. Use speaker notes. These should contain
the details. It puts a lot of burden on the speaker since they cannot just read off the slides. But this doesn’t deter good speakers, since they prepare dozens of times, and then again.

So there you have it: my 4 principles for delivering compelling presentations to live audiences.

(CAVEAT: If the presentation is emailed to an audience who will consume it asynchronously, that has completely different rules).

How did the 2006 Google strategy presentation turn out, you ask? It went quite well, and later I got a nice thank you note from Eric. I didn’t realize at the time that I should have been the one thanking him for the once-in-a-lifetime learning opportunity.
ENTERPRISE AI: BUILD AGENTS, NOT TOOLS

In the past 2 weeks, I've met several AI agent tooling startups that have each realized that the biggest problem in large enterprises is NOT the tooling to build, test and deploy agents, but that these enterprises don't have the talent density / people / knowhow to build real life agents for complex workflows.

So these startups are pivoting to: (a) building and running agents themselves and (b) offering their original service as part of running the agent.

tldr Enterprise AI defensibility and value creation might lie in the full-stack approach to building, running and evaluating agents. Almost consulting-ish. Trying to be a pure tech platform might be a losing proposition in these early days. Some other hungry startup will own the agent and they won't use your technology stack.

Related Influencers