devang raiyani

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devang raiyani

devang raiyani

@devangraiyani

co-founder https://t.co/Au01R6hb59

Mumbai 参加日 Haziran 2009
550 フォロー中523 フォロワー
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Aaron Levie
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.
Lenny Rachitsky@lennysan

Engineering job openings are at the highest levels we’ve seen in over 3 years There are over 67,000 (!!!) eng openings at tech companies globally right now, with 26,000 just in the U.S. We don’t know if there would have been more open roles if not for AI or if AI is actually leading to more open roles, but since the start of this year, the increase in open eng roles is accelerating even more.

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Kpaxs
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.
Kpaxs@Kpaxs

The brain has a primitive rule: You are what you repeatedly do. If you repeatedly do “avoid,” it updates your self-model to “the kind of person who avoids.” If you repeatedly do “show up badly but show up,” it updates you to “the kind of person who does things even when unsure.”

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IceCreamMan
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 - luma.com/socialsmum @avinashraghava @AIBoomi
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Marc Lou
Marc Lou@marclou·
Stop creating content. Build stuff that's story-worthy. Great content is a side-effect of a great story.
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Justin Skycak
Justin Skycak@justinskycak·
The most hard-hitting 2 sentences in all of talent development research:
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devang raiyani
devang raiyani@devangraiyani·
Linkedin Law of Gyan - there value you bring as a professional is inversely proportionate to the podcasts you've been on.
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Andrej Karpathy
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.
tobi lutke@tobi

I really like the term “context engineering” over prompt engineering. It describes the core skill better: the art of providing all the context for the task to be plausibly solvable by the LLM.

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devang raiyani
devang raiyani@devangraiyani·
@psychidiaries This is a better anti-smoking ad that should play in theaters instead of 'mukesh'
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Alfred Wahlforss
Alfred Wahlforss@itsalfredw·
Listen is for founders, marketers, design and insights teams. - Find pain points to hit PMF - Test ads, messages, and figma - Understand how your brand is seen - Build customer personas Reply “Listen” for access + $1,000 in credits.
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Alfred Wahlforss
Alfred Wahlforss@itsalfredw·
AI writes your code. Now it talks to your users. We raised $27M from @Sequoia to build @ListenLabs. Listen runs thousands of interviews to uncover what users want, why they churn, and what makes them convert. See how @Microsoft and @canva use it:
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devang raiyani
devang raiyani@devangraiyani·
@ParvSondhi My real optimizm around AI is that I think it abstracts way over what a document could give. It takes a leap over data that seemed like the reserve of the top professionals in the domain.
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Parv
Parv@ParvSondhi·
Documentation is going to become a very high leverage artifact. Ai - fication and its quality for many automation projects is going to be highly dependent on how good your initial documentation is
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devang raiyani
devang raiyani@devangraiyani·
@shreyas we're building a 'creative jamming' layer to solve this upstream problem called 'creativity' Would love to give you test drive soon.
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Shreyas Doshi
Shreyas Doshi@shreyas·
If you play around enough with even today’s LLMs, you’d find that AI is doing a better job on this front than 9 out of 10 humans. Of course today’s interfaces are crude and some prompting is a must, but consider how straightforward it is to make these things better in 5-10 years.
Rajesh Solanki@rajesh_energos

@shreyas @aka_le_Mulder @avadhpatel Is AI intelligence or memorising and retention? Creative thinking, first principles thinking , intuitive thinking , ability to empathise will be the human advantage.

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