Vamsidhar Kodam

[Vamsidhar Kodam @vkodam]

@sama Curious to hear what surprised you the most.

Also, it’d be great to have an official OpenAI showcase for real-world use cases at the edge. A lot of the best examples are scattered across Reddit/X today; a central place would help people see what’s possible.

[Andrew Ng @AndrewYNg]

The invention of modern writing instruments like the typewriter made writing easier, but they also led to the rise of writer’s block, where deciding what to write became the bottleneck. Similarly, the invention of agentic coding assistants has led to a new builder’s block, where the holdup is deciding what to build. I call this the Product Management Bottleneck.

Product management is the art and science of deciding what to build. Because highly agentic coding accelerates the writing of software to a given product specification, deciding what to build is the new bottleneck, especially in early-stage projects. As the teams I work with take advantage of agentic coders, I increasingly value product managers (PMs) who have very high user empathy and can make product decisions quickly, so the speed of product decision-making matches the speed of coding.

PMs with high user empathy can make decisions by gut and get them right a lot of the time. As new information comes in, they can keep refining their mental models of what users like or do not like — and thereby refine their gut — and keep making fast decisions of increasing quality.

Many tactics are available to get user feedback and other forms of data that shape our beliefs about users. They include conversations with a handful of users, focus groups, surveys, and A/B tests on scaled products. But to drive progress at GenAI speed, I find that synthesizing all these sources of data in a PM's gut helps us move faster.

Let me illustrate with an example. Recently, my team debated which of 4 features users would prefer. I had my instincts, but none of us were sure, so we surveyed about 1,000 users. The results contradicted my initial beliefs — I was wrong! So what was the right thing to do at this point?
- Option 1: Go by the survey and build what users told us clearly they prefer.
- Option 2: Examine the survey data in detail to see how it changes my beliefs about what users want. That is, refine my mental model of users. Then use my revised mental model to decide what to do.

Even though some would consider Option 1 the “data-driven” way to make decisions, I consider this an inferior approach for most projects. Surveys may be flawed. Further, taking time to run a survey before making a decision results in slow decision-making.

In contrast, using Option 2, the survey results give much more generalizable information that can help me shape not just this decision, but many others as well. And it lets me process this one piece of data alongside all the user conversations, surveys, market reports, and observations of user behavior when they’re engaging with our product to form a much fuller view on how to serve users. Ultimately, that mental model drives my product decisions.

Of course, this technique does not always scale. For example, with programmatic online advertising in which AI might try to optimize the number of clicks on ads shown, an automated system conducts far more experiments in parallel and gathers data on what users do and do not click on, to filter through a PM's mental model of users. When a system needs to make a huge number of decisions, such as what ads to show (or products to recommend) on a huge number of pages, PM review and human intuition do not scale.

But in products where a team is making a small number of critical decisions such as what key features to prioritize, I find that data — used to help build a good mental model of the user, which is then applied to make decisions very quickly — is still the best way to drive rapid progress and relieve the Product Management Bottleneck.

[Original text: https://t.co/1tulDs3k7U ]

[Vamsidhar Kodam @vkodam]

I'm on the waitlist for @perplexity_ai's new agentic browser, Comet: https://t.co/LOsuNbt41O

[Vamsidhar Kodam @vkodam]

@IndiGo6E @IndiGo6E I sent the details few days ago and still no response. I’ll have to initiate legal action if not addressed quickly.

[Vamsidhar Kodam @vkodam]

@DGCAIndia @IndiGo6E @UPI_NPCI UPI transaction initiated and amount deducted from bank account. Indigo didn’t neither confirm payment nor issue a PNR. Customer care refuses to answer questions on the refund. Money is stuck with @IndiGo6E

[Vamsidhar Kodam @vkodam]

@DGCAIndia @IndiGo6E @UPI_NPCI UPI transaction initiated and amount deducted from bank account. Indigo didn’t neither confirm payment nor issue a PNR. Customer care refuses to answer questions on the refund. Money is stuck with @IndiGo6E

[Vamsidhar Kodam @vkodam]

Just a few months post Shreyas Doshi's Product Management course on Maven and already seeing a positive impact on my approach. Truly a game changer for those in the PM field. Highly recommend to those looking to upskill! #productmanagement #professionaldevelopment @shreyas

[Vamsidhar Kodam @vkodam]

@IndiGo6E Any update?

[Vamsidhar Kodam @vkodam]

@DGCAIndia @qatarairways @RGIAHyd @IndiGo6E 3 days without my bags and still no update from neither the marketing carrier (QR) nor operating carrier (6E)! 😡🧳 This codeshare connection has turned into a nightmare. Hoping for a speedy resolution ASAP! #LostLuggage

[Vamsidhar Kodam @vkodam]

@qrsupport I sent a DM with my details and haven’t seen a response yet.

[Vamsidhar Kodam @vkodam]

@qrsupport Sent a DM with details. It has been almost 4 days and no response yet.

[SabreNews @SabreNews]

Sabre Unveils First Product Powered by its Proprietary
Sabre Travel AI Technology https://t.co/rNWJpNT3kp

[Vinod Khosla @vkhosla]

Capitalism served it's purpose well when production efficiency was the major factor. Today it is more focused on demand gen and that is not socially as valuable. It needs to go from efficiency/selling goal to adding income distribution as a second goal. Need modified capitalism

[Shashi Tharoor @ShashiTharoor]

3/3 That doctor's suicide is a tragic reminder that our brave medics need our understanding, sympathy & support. Working in these difficult conditions, every shortcoming is mercilessly attacked while their achievements &out-of-the-way efforts are unappreciated. #SupportOurDoctors

[Shashi Tharoor @ShashiTharoor]

2/3 A few days back a young doctor running a clinic in Kollam committed suicide over an alleged botch-up in treating a young girl who later expired. He had been mercilessly attacked on social media. Many medical professionals work under intolerable strain. They deserve better.

[Shashi Tharoor @ShashiTharoor]

1/3 In Thiruvananthapuram, a doctor's suspension for alleged negligence has led to a flash strike by medics at Govt Medical College Hospital. A Govt that failed to give doctors the resources&working conditions to cope w/enormous pressure punishes doctors!
https://t.co/Bukwe9BD90

[Vamsidhar Kodam @vkodam]

This is totally different level!

[Raphaël Millière @raphaelmilliere]

I asked GPT-3 to write a response to the philosophical essays written about it by @DrZimmermann, @rinireg @ShannonVallor, @add_hawk, @AmandaAskell, @dioscuri, David Chalmers, Carlos Montemayor, and Justin Khoo published yesterday by @DailyNousEditor. It's quite remarkable!

[Women in Statistics and Data Science @WomenInStat]

Today, we’re going to play a game I’m calling “IT’S JUST A LINEAR MODEL” (IJALM).

It works like this: I name a model for a quantitative response Y, and then you guess whether or not IJALM.

1/

[John Poppelaars @ORatWork]

Giving #mathematics the credit it deserves; published a new blog entry on 2011, the Year of Math. http://bit.ly/goT6SB