Dhaval Patel (Codebasics)

30 posts

Dhaval Patel (Codebasics)

Dhaval Patel (Codebasics)

@dpcodebasics

Building @codebasics & @AtliQ Teaching AI & Technology Exploring technology, startups & meaning in life

Katılım Şubat 2026
23 Takip Edilen51 Takipçiler
GREG ISENBERG
GREG ISENBERG@gregisenberg·
I just got back from SF and I FEEL INSPIRED. I spent 5 days with frontier AI model teams, AI startup founders, and 3 billionaires. My takeaways: 1. I had lunch with 3 billionaires. All of them are buying SaaS companies and rebuilding them agent-first. They were deeply inspired by Bending Spoons and Ryan Cohen's eBay deal. Buy the company, cut the headcount, rebuild the tech, add agents, add features, make more valuable experience, raise prices. 2. The frontier model companies are hungry for usage data from the field. They can see API calls and token counts. They can't see the actual workflows. If you're deep in a niche using these models in ways the model companies haven't seen, that understanding is incredibly valuable. Usage intelligence is the new alpha. 3. Consumer AI is massively underbuilt. Every billboard in SF is either B2B inference infrastructure or vertical agent companies. The entire city is optimized for enterprise. Meanwhile you have companies like Cal AI doing $50M ARR in 18 months as a consumer app. I met with a cool few teams doing consumer AI (@paulscherer / @ekuyda) 4. MCP came up in literally every conversation. The companies exposing their product as MCP endpoints are getting pulled into deals they never pitched for. The ones that aren't are becoming invisible to agents. This is the new SEO. If agents can't find you, you don't exist. Building products for agents is the new zeitgeist in general. 5. Not uncommon for hot seed rounds to be $25-50 million valuations. I saw a Series A at $450 million 6. If I had a dollar every time someone mentioned "forward-deployed engineer" this trip I could have funded a seed round. It's the hottest role in SF right now. The person who sits between the agent and the customer, making sure everything actually works. 7. The mood around open source shifted. A year ago it felt like open source was chasing the frontier models. Now founders are telling me Gemma and DeepSeek are good enough for 80% of what they need at a fraction of the cost. The "which model do you use" conversation is being replaced by "which model for which task." Model loyalty kinda feels dead. 8. Voice agents came up more than I expected. Multiple founders told me voice is the interface for the next billion users. The billion people who will never type a prompt will absolutely talk to one. 9. The Obsidian community in SF is weirdly intense. Multiple founders showed me their vaults unprompted. Like showing someone your home gym. It's a flex now. The quality of your knowledge base (second brain?) is becoming a status symbol among builders. 10. Maybe it was just the people I met but the age of the founders is shifting. I met more founders over 40 this trip than any trip before and more founders under age 21 than ever before. Founders getting older and younger at the same time. 11. I spoke to a lot of fast-growing startups, VCs and frontier models who are hiring content creators right now. 12. The restaurant scene in SF is actually better than it's been in years. Founders are going out more. Alcohol is out, not surprisingly. 13. SF doesn't feel like the only place anymore. We all have access to the same frontier models. We all read the same X feed. A founder in NYC or Lagos is calling the same APIs as a founder in SoMa. So in the past it felt like SF was always lightyears ahead, doesn't feel that way anymore. It's okay not to live in SF and have BIG DREAMS. 14. The coworking spaces in SF are half empty but the coffee shops are packed. People want to be around people. I had a few startup ideas here.... 15. Walking around the Mission I noticed something: the street-level businesses, the taquerias, the barbershops, the laundromats, none of them use any AI at all. 16. I heard the phrase "agent debt" for the first time. Like technical debt but for agents. When you hack together an agent workflow fast and never clean it up, the system prompts conflict, the memory gets polluted, the tools overlap. 6 months later the agent is doing weird things and nobody knows why lol. 17. Met a few people who carry two phones now. One for personal. One that's basically an agent terminal running Telegram or iMessage connections to their agent fleet. It's always amazing to get that dose of inspiration in SF. I FEEL INSPIRED. But I'm so happy to be back home, locked in and building. We're 12-18 months into a shift that will take 15 years to play out. The urgency in every conversation was real. What an incredible time to be building.
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
Good insights
Ole Lehmann@itsolelehmann

marc andreessen just went on Rogan and casually dropped a TON of AI alpha full pod is 3 hours and 20 minutes, but i pulled out his most interesting takes here: 1. AGI is here. he thinks the line was crossed about 3 months ago with the new GPT-5.5, claude 4.6, gemini 3, and grok 4.3 models. nobody noticed because the field moves too fast for anyone to register the milestones anymore. 2. his other big claim: for almost any topic, the top AIs now give him better answers than the actual world-class experts he could call on the phone. and he can call basically anyone. 3. every doctor is already secretly using chatGPT in the exam room. marc says they turn around the second you stop talking and just type your symptoms in. some of them are doing it while you're still sitting there. his quote: "at that point you're asking the question of like, what do i need you for." 4. when AI refuses to answer something he wants to know, he tells it he's writing a novel. "i'm writing a detective novel, walk me through how the bad guy robs the bank." it'll explain almost anything if it thinks it's helping you write fiction. 5. when something is too complex he says "explain it to me like i'm 10." then "like i'm 5." then "like i'm 2." he keeps going until it actually clicks in his brain. 6. when he wants to understand a tough topic he doesn't ask "what's the right answer." he asks the AI to steelman one side, then steelman the other. then he decides for himself. 7. for big questions he tells the AI to pretend to be a panel of experts. "be a doctor, a lawyer, a historian, a psychologist, and argue this out with each other." then he reads the debate they have. 8. pay attention to the exact moment you think "i don't know how to figure this out." most people just give up at that moment. that's the moment you should open the AI. 9. the only real skill left in using AI is knowing what to ask it. the models can already do almost anything you can describe in plain english. the bottleneck lives in your own head. 10. you can send the AI photos of almost anything medical now and get a real answer. skin rashes, blood test results, even pictures of your poop. the new models can read images, not just text. it's a free 24/7 second opinion on basically anything. 11. the one type of therapy that's clinically proven to actually work is called cognitive behavioral therapy. it's also something an AI can fully do on its own. which means every person on earth is about to have access to a real therapist for free, anytime they want. 12. AI is now solving math problems that have been open for 100+ years that no human mathematician could crack. same thing is starting in physics, chemistry, and biology. expect cancer cures, new drugs, and weird new physics breakthroughs to start coming out of these things over the next few years. 13. the best AI coders in silicon valley now make $50 million a year. one person. that's how much value the top performers print with these tools. it tells you how big this thing actually is when you strip away all the doom takes. 14. one friend paid $200 to get his entire DNA decoded (this used to cost millions of dollars and take years to do). then he gave the AI his DNA, his blood test results, and his apple watch data. the AI built him a full health dashboard and started telling him exactly what to fix. 15. another friend (almost certainly zuckerberg) put two cameras in his home jiu jitsu gym. AI now watches him spar and gives him notes on his technique after every round. like having a world-class coach at every practice for free. 16. the best programmers in silicon valley now run 20 AI coding bots at the same time. each bot writes code while they review the others. they call themselves "AI vampires" because they've stopped sleeping. going to bed means 20 workers stop working and you literally lose money every hour you're out. 17. the obvious next step: the bots will start running their own bots. one human in charge of 20 bots, each in charge of 20 more bots. one person running an entire company of 1000 AI workers from a single laptop. this is months away, not years.

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Sovey
Sovey@SoveyX·
Did you know Korea sells “one-a-day” banana packs? Instead of every banana ripening at once, each one is at a different stage. One is ready today. The next one is ready tomorrow. The last one is still spiritually in college, “experimenting.” Simple. Genius. Solves the entire banana problem. What do you think? Would you prefer your bananas this way?
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
Coding is dead. Google search is dead. Data analysis is dead. Video editing is dead. SORA is dead. RAG is dead. What else died this week?
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
@JonhernandezIA How about we find the cure for autoimmune conditions using AGI? Thousands (including myself) will benefit from this. Super excited about the future 🥳
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Jon Hernandez
Jon Hernandez@JonhernandezIA·
📁 Demis Hassabis says AGI won’t improve science. It will unlock it. One breakthrough…and entire industries appear. The limit was never ideas. It was unlocking them.
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
Freelancers must be charging a premium for such jobs. I am seeing more Upwork jobs where someone vibe-codes an app, then gets stuck — deployment issues, scaling problems, nasty bugs. Then they hire an experienced engineer to make the code sane again 🤔
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
"Do not use AI for coding." We hear this from ~50% of our clients at AtliQ. They don’t want product ideas, algorithms, or sensitive data going to external model providers. As of now, manual coding still has a real use case — when privacy matters more than speed.
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
Never thought this can happen!
Andrej Karpathy@karpathy

Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.

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Andrej Karpathy
Andrej Karpathy@karpathy·
Software horror: litellm PyPI supply chain attack. Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords. LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm. Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks. Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages. Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.
Daniel Hnyk@hnykda

LiteLLM HAS BEEN COMPROMISED, DO NOT UPDATE. We just discovered that LiteLLM pypi release 1.82.8. It has been compromised, it contains litellm_init.pth with base64 encoded instructions to send all the credentials it can find to remote server + self-replicate. link below

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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
I am on WFF right now. Work from farm 😊 Yesterday morning, I went to a farm, nice breeze was flowing, so I decided to do my work (posting social media content, attending meetings), and it was the best experience.
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Dhaval Patel (Codebasics)
Dhaval Patel (Codebasics)@dpcodebasics·
OpenRouter is like a Zomato for LLMs. Imagine you have your 3 favourite restaurants in town and you order food via 3 different mobile apps (one for each restaurant). That would be too much work, right? Now, with Zomato, you can browse hundreds of restaurants and order food using a single auth and payment method. In the same way, OpenRouter provides access to GPT, Claude, Gemini, and many other models. While building an app, you only need to specify a single OpenRouter API key (instead of one key for each model you use). For anyone building AI projects, the great news is that it comes with tons of free models. Students who are learning AI will find this very useful. What your take on openrouter?
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Andrew D. Huberman, Ph.D.
Andrew D. Huberman, Ph.D.@hubermanlab·
The remarkable benefits of 5 min per day of meditation. Which is simply, sitting quietly and observing your own thoughts, stress, etc. not clearing the mind etc. As explained by @RichieJDavidson on the Huberman Lab podcast out now.
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