Yeshwanth Jagannath

Webdev.OptOutside believer.

[Yeshwanth Jagannath @yesh06]

Inclination towards open weight LLMs is increasing for vertical AI use-cases. Below is a list of the to help make some informed decisions. Best Open Source LLM in 2026: Rankings, Benchmarks, and the Models Worth Running https://t.co/EWXK4b4I6M

[Andrej Karpathy @karpathy]

This is the the quote I've been citing a lot recently.

[Andrew Ng @AndrewYNg]

AI-native software engineering teams operate very differently than traditional teams. The obvious difference is that AI-native teams use coding agents to build products much faster, but this leads to many other changes in how we operate. For example, some great engineers now play broader roles than just writing code. They are partly product managers, designers, sometimes marketers. Further, small teams who work in the same office, where they can communicate face-to-face, can move incredibly quickly.

Because we can now build fast, a greater fraction of time must be spent deciding what to build. To deal with this project-management bottleneck, some teams are pushing engineer:product manager (PM) some teams are pushing engineer:product manager (PM) ratios downward from, say, 8:1 to as low as 1:1. But we can do even better: If we have one PM who decides what to build and one engineer who builds it, the communication between them becomes a bottleneck. This is why the fastest-moving teams I see tend to have engineers who know how to do some product work (and, optionally, some PMs who know how to do some engineering work). When an engineer understands users and can make decisions on what to build and build it directly, they can execute incredibly quickly.

I’ve seen engineers successfully expand their roles to including making product decisions, and PMs expand their roles to building software. The tech industry has more engineers than PMs, but both are promising paths. If you are an engineer, you’ll find it useful to learn some product management skills, and if you’re a PM, please learn to build!

Looking beyond the product-management bottleneck, I also see bottlenecks in design, marketing, legal compliance, and much more. When we speed up coding 10x or 100x, everything else becomes slow in comparison. For example, some of my teams have built great features so quickly that the marketing organization was left scrambling to figure out how to communicate them to users — a marketing bottleneck. Or when a team can build software in a day that the legal department needs a week to review, that’s a legal compliance bottleneck. In this way, agentic coding isn’t just changing the workflow of software engineering, it’s also changing all the teams around it.

When smaller, AI-enabled teams can get more done, generalists excel. Traditional companies need to pull together people from many specialties — engineering, product management, design, marketing, legal, etc. — to execute projects and create value. This has resulted in large teams of specialists who work together. But if a team of 2 persons is to get work done that require 5 different specialities, then some of those individuals must play roles outside a single speciality. In some small teams, individuals do have deep specializations. For example, one might be a great engineer and another a great PM. But they also understand the other key functions needed to move a project forward, and can jump into thinking through other kinds of problems as needed. Of course, proficiency with AI tools is a big help, since it helps us to think through problems that involve different roles.

Even in a two-person team, to move fast, communication bottlenecks also must be minimized. This is why I value teams that work in the same location. Remote teams can perform well too, but the highest speed is achieved by having everyone in the room, able to communicate instantaneously to solve problems.

This post focuses on AI-native teams with around 2-10 persons, but not everything can be done by a small team. I'll address the coordination of larger teams in the future.

I realize these shifts to job roles are tough to navigate for many people. At the same time, I am encouraged that individuals and small teams who are willing to learn the relevant skills are now able to get far more done than was possible before. This is the golden age of learning and building!

[Original text: https://t.co/1pUxNC5UXk ]

[Andrej Karpathy @karpathy]

Wow, this tweet went very viral!

I wanted share a possibly slightly improved version of the tweet in an "idea file". The idea of the idea file is that in this era of LLM agents, there is less of a point/need of sharing the specific code/app, you just share the idea, then the other person's agent customizes & builds it for your specific needs.

So here's the idea in a gist format: https://t.co/NlAfEJjtJV

You can give this to your agent and it can build you your own LLM wiki and guide you on how to use it etc. It's intentionally kept a little bit abstract/vague because there are so many directions to take this in. And ofc, people can adjust the idea or contribute their own in the Discussion which is cool.

[Yeshwanth Jagannath @yesh06]

@burkov @MindsDB Just did. Thank you.

[Yeshwanth Jagannath @yesh06]

Man invents AI to create, then builds AI to catch AI's creations, forever chasing our own digital tails. 😅 #TechTreadmill

[Yeshwanth Jagannath @yesh06]

@netflix - WTF! Such a horrible experience streaming the fight night. #wtfnetflix #TysonPaul

[Beff (e/acc) @beffjezos]

This video gave me shivers.

So grateful to have witnessed history with my own eyes �

[think like a real estate appraiser @ThinkAppraiser]

THIS IS EVERYTHING.

BOOKMARK THIS.

IMMEDIATELY.

[Yeshwanth Jagannath @yesh06]

@editingemily Couldn’t agree more.

[Chris Johnson 🥝/🇺🇸 🛩️🧊 @chrisjohnson_nz]

This is incredible and will be life changing for so many people. WOW. I wonder how the Elon haters will reconcile this one?

[Yeshwanth Jagannath @yesh06]

A new paradigm in web search is here. Love what is being built as a future displacement for the classic google search. @perplexity_ai has definitely perplexed! 😎

[Perplexity @perplexity_ai]

We are happy to announce that we've raised $73.6 million in Series B funding led by IVP with participation from NVIDIA, NEA, Bessemer, Elad Gil, Jeff Bezos, Nat Friedman, Databricks, Tobi Lutke, Guillermo Rauch, Naval Ravikant, Balaji Srinivasan.

[Yeshwanth Jagannath @yesh06]

@WonderfulNuts I’ve DM’d the details. I look forward to your response.

[Yeshwanth Jagannath @yesh06]

@WonderfulNuts - I’d expect better quality control from y’all as a leading pistachio company. Dead maggots in the nuts is not one of them. *disappointed*

[Sahil Bloom @SahilBloom]

If you sit in back-to-back meetings at work, read this:

[Yeshwanth Jagannath @yesh06]

One for the books!

[Billy Oppenheimer @bpoppenheimer]

When he was 11, Kobe Bryant played a full 25-game basketball season without scoring a single point.

He then took a simple mathematical approach to becoming one of the all-time greats:

[Yeshwanth Jagannath @yesh06]

Thanks Lane 8 for spending 1,353 minutes with me in 2022. I couldn’t stop listening to No Fun. #SpotifyWrapped https://t.co/IdD5AlQnRk

[Yeshwanth Jagannath @yesh06]

@TechTrainerTim I prefer the CLI, just more cleaner and easier cmdlets to work with.

[Wonder of Science @wonderofscience]

Earth's rotation visualized in a stunning timelapse that follows a fixed point in the sky.

Credit: Martin Giraud