devang raiyani

co-founder

[devang raiyani @devangraiyani]

@numberbee7070 @DesigningUber another app :(

will try though - all for startups disrupting incumbents.

[devang raiyani @devangraiyani]

In general, the Uber experience @Uber @DesigningUber continues to not add up. Was thinking Uber Black would hold up to a better standard. All they've done is upgraded the car - the drive experience is still terrible.

[devang raiyani @devangraiyani]

@benblumenrose I'd expect a higher level of positioning / framing skills from them given the obvious traps and learning from the Jaguar debacle. But I guess any work by large committees always looks like this..

[Ben Blumenrose @benblumenrose]

Our 2026 Design in AI Report is now live!

This report is the culmination of thousands of people hours and many late nights to create what we believe is the most comprehensive, well-researched report capturing and synthesizing the state of Design + AI today.

While we used AI in many areas, a report like this still required deep thinking, grit, and humans coming together to do what they do best.

The final report spans nearly 20k words covering the survey results of over 900 people paired with dozens of qualitative interviews.

Over the coming months we will also release 7 beautiful case studies showing how top design teams are working on the ground featuring designers at @AnthropicAI, @framer, @linear, @NotionHQ, @Shopify, @SierraPlatform, and @stripe.

This work is a true labor of love to help guide a design community we hold so dear.

Link in the comments and please let us know what you think. Your feedback helps us shape how we will evolve this work over the coming years...

[devang raiyani @devangraiyani]

also, have you noticed it's a mad scramble at the end of the ride - they are distracted by the notification of the next ride, for which there are penalities / disincentives if they don't make the quota. quite a dark pattern @DesigningUber

[devang raiyani @devangraiyani]

Particularly in BLR, cabbies feel they're entitled to drive how they want. I pay a premium for uber black - all i get is a cleaner car, the driver is still aggressive and doesn't care about passenger comfort / drive experience.

[Jediwolf @Jediwolf]

What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS

[Aaron Levie @levie]

Jevons paradox is happening in real time. Companies, especially outside of tech, are realizing that they can now afford to take on software projects that they wouldn’t have been able to tackle before because now AI lets them do so.

We’re going to start to use software for all new things in the economy because it’s incrementally cheaper to produce. Marketing teams at big companies will have engineers helping to automate workflows. Engineers in life sciences and healthcare will automate research. Small businesses will hire engineers for the first to build better digital experiences.

And as long as AI agents still require a human who understands what to prompt, how to review when an agent goes off the rails, how it guide back, how to maintain the system that was built, how to fix the ongoing bugs, and more, we will still have humans managing these agents.

This is why all the advice you get of not going into engineering is wrong. The world is going to increasingly be made up of software, and the people that understand it best will be in a strong economic position. This will happen in other roles as well where output goes up and demand increases.

[Kpaxs @Kpaxs]

Your brain is tracking your behavior. Constantly.

It’s building a model of who you are based on the data you’re giving it.

And the data is your actions. Nothing else counts.

This isn’t a metaphor. It’s literally how identity formation works.

[IceCreamMan @Ktens]

AIBoomi Socials is coming Mumb(ai)!

The Bombay Socials is scheduled for Fr(ai)day the 13th, and promises to not have hallucinations! Meet fellow builders, doers and and other figure-outers.

Entry is curated, so please apply - https://t.co/P5D3edhlHT

@avinashraghava @AIBoomi

[devang raiyani @devangraiyani]

Beyond the infrastructure collapse, the Indigo fiasco points to a collapse of class distinction... insightful read!

[Santosh Desai @desaisantosh]

During the Indigo fiasco a common sentiment expressed was that our airports looked like railway stations. That says a lot about how we imagine both, and about how we see inequality as the natural order of things. Today in the TOI.

[Marc Lou @marclou]

Stop creating content.

Build stuff that's story-worthy.

Great content is a side-effect of a great story.

[devang raiyani @devangraiyani]

This what a POC looks like...

[Crémieux @cremieuxrecueil]

Pretty interesting:

Companies that have adopted AI aren't hiring fewer senior employees, but they have cut back on hiring juniors ones.

[Justin Skycak @justinskycak]

The most hard-hitting 2 sentences in all of talent development research:

[devang raiyani @devangraiyani]

Linkedin Law of Gyan - there value you bring as a professional is inversely proportionate to the podcasts you've been on.

[Andrej Karpathy @karpathy]

+1 for "context engineering" over "prompt engineering".

People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window with just the right information for the next step. Science because doing this right involves task descriptions and explanations, few shot examples, RAG, related (possibly multimodal) data, tools, state and history, compacting... Too little or of the wrong form and the LLM doesn't have the right context for optimal performance. Too much or too irrelevant and the LLM costs might go up and performance might come down. Doing this well is highly non-trivial. And art because of the guiding intuition around LLM psychology of people spirits.

On top of context engineering itself, an LLM app has to:
- break up problems just right into control flows
- pack the context windows just right
- dispatch calls to LLMs of the right kind and capability
- handle generation-verification UIUX flows
- a lot more - guardrails, security, evals, parallelism, prefetching, ...

So context engineering is just one small piece of an emerging thick layer of non-trivial software that coordinates individual LLM calls (and a lot more) into full LLM apps. The term "ChatGPT wrapper" is tired and really, really wrong.

[devang raiyani @devangraiyani]

@psychidiaries This is a better anti-smoking ad that should play in theaters instead of 'mukesh'

[devang raiyani @devangraiyani]

@itsalfredw listen

[devang raiyani @devangraiyani]

@itsalfredw @sequoia @conviction @pearvc @aigrant @schreier @charliecurnin @mvernal @pranavreddy @arasha Listen, this is awesome!

[devang raiyani @devangraiyani]

when superheroes fall, they land like squirrels... :)

[Massimo @Rainmaker1973]

«The best thing I’ve learned this week is that when squirrels fall - they land like superheroes»