Michael Branconier

721 posts

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Michael Branconier

Michael Branconier

@mike_branc

FDE @rungalileo | building web apps | 🏡 https://t.co/7Q9kopAcbO | 👩‍❤️‍👨 https://t.co/YIOvgVspVv

Katılım Mayıs 2016
470 Takip Edilen187 Takipçiler
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Michael Branconier
Michael Branconier@mike_branc·
My 2024 Wrapped as a dev: After my last tweet (and some encouragement from @idode_k ) I wanted to share a bigger thread with demos of each project I built this year. Looking back at my GitHub graph, even I'm surprised at how showing up consistently can add up. Here we go:
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Michael Branconier
Michael Branconier@mike_branc·
People will definitely exploit this but I am optimistic it will empower indiehackers building niche products. With google, you were limited to a few keywords when searching for a product or service. With genAI chatbots, you can have a whole conversation working through what exactly it is u want and that niche project built by that one guy across the world will show up.
Stripe@stripe

Today, we’re launching the @link wallet for agents. It lets you securely empower agents to spend on your behalf. Your payment credentials are never exposed and you approve every purchase. link.com/agents

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Matt Ambrogi
Matt Ambrogi@matt_ambrogi·
Give me a fresh nextjs app, a supabase project, a vercel account, claude api keys, and I can do anything.
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Michael Branconier
Michael Branconier@mike_branc·
Gotta be one of the best tweets I’ve seen on here. It makes it better that I can’t imagine a world where I don’t have my whoop. Inspiring shit fr
Will Ahmed@willahmed

You have no experience. You’ve never started a company. You’ve never had a full time job. Nike is going to kill you. You’re a kid. You don’t have technical skills. You shouldn’t build hardware. Apple is going to kill you. You can’t build hardware. You can’t measure heart rate non-invasively. Athletes don’t care about recovery. Under Armour is going to kill you. It won’t be accurate. You don’t listen. You’re an ineffective leader. You can’t recruit great talent. You’re going to have to pay every athlete. You can’t measure sleep non-invasively. It’s too expensive to research. Athletes are a small market. The product costs too much to make. The product costs too much to sell. Your valuation is too high. Consumers aren’t going to want it. Hardware is too hard. You should measure steps. Fitbit is going to kill you. You can’t build a marketing engine. You can’t raise enough money. You need a real CEO. Google is going to kill you. You can’t be a subscription. You can’t build a brand. You can’t do consumer in Boston. Your valuation is too high. You shouldn’t make accessories. You shouldn’t make apparel. Lululemon is going to kill you. You can’t predict Covid. Stay in your niche. You are going to run out of money. You can’t build a health platform. Amazon is going to kill you. You can’t measure blood pressure. You can’t get medical approvals. The market is too small. You don’t understand AI. The market is too competitive. It won’t work internationally. The supply chain is too complicated. You can’t build an AI. You can’t raise enough money. It’s too competitive. Healthcare isn’t going to want it. … Just keep going ✌️

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Michael Branconier retweetledi
dax
dax@thdxr·
right now everything in the world is telling you to go faster, ship more, add that feature, start another project so i'm actively working on feeling ok not doing any of that
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“paula”
“paula”@paularambles·
“this is a significant refactor” just put the tokens in the bag lil bro
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Michael Branconier
Michael Branconier@mike_branc·
Damn Gemini being overworked, fell asleep on the keyboard
Michael Branconier tweet mediaMichael Branconier tweet media
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Lev Neiman
Lev Neiman@NeimanLev·
I built the same caching library twice. Once at @DoorDash in Kotlin, now at @rungalileo in Python. Both times, the problems were identical. Here's what I learned 🧵
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Michael Branconier
Michael Branconier@mike_branc·
Not a financial advisor or tax advisor or whatever i have to say to not get sued but claude + free tax usa is a great stack for doing your taxes
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JJ Watt
JJ Watt@JJWatt·
Genuine question on a restaurant situation: You walk up to a counter to order. You find your own table and seat yourself. If you order coffee, they hand you a cup and you go fill it up yourself. If you order food, they hand you a buzzer and when it goes off, you go pick it up yourself. The iPad has a “20%, 25%, 30%, Other” tip option, with 20% already preselected. What’s your move?
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Galileo
Galileo@rungalileo·
Every agent your team ships has its own hardcoded guardrails, its own bespoke logic, its own failure modes. That's not governance. These brittle controls soon become a liability. Galileo is proud to announce the open-source launch of Agent Control 🚀 Agent Control is the open-source control plane that solves for the open, centralized governance needs for all your AI Agents. 💬 "We've had a front-row seat to agent development at Fortune 500 and digital-native companies. They have been struggling to hard-code safety rules and controls into each agent which makes them brittle. With Agent Control, developers can now create policies in one place and then use those to enforce guardrails everywhere." — @YashSheth46, Co-founder & CTO, Galileo Agent Control integrates seamlessly with all your agents using the @ control hook or just by leveraging our native integrations with some of the leading agent frameworks. No redeployment. No code changes. No vendor lock-in. 💬 “Centralized management of policies can help organizations to manage AI agent behaviors. A unified control plane and centralized governance of agents can help organizations efficiently deploy AI agents at scale. Organizations that embrace eval engineering as a core competency will shorten the time to value for their AI investments. By taking a lifecycle approach, organizations can achieve a continuous improvement loop for AI systems.” – Tim Law, @IDC Research Director, AI and Automation Agent Control is already backed by partners including @awscloud, @Cisco AI Defense, @crewAIInc, @glean, @ServiceNow, and @rubrikInc, and it works with the guardrail providers you already use, from our Luna models to NVIDIA NeMo or AWS Bedrock. The repo is live, built in the open with contributions from some of the largest AI infrastructure companies in the world, try it out today: agentcontrol.dev Watch Yash walk through how it works in the video below, and check the comments for links to our launch webinar, announcement blog, and full press release. 👇
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Michael Branconier
Michael Branconier@mike_branc·
I do feel this strange anxiety lately when I just vibe code something important because it works and the tests pass, but I know the second something goes wrong, I wouldn’t know what to do and would be reliant on an agent to solve the problem. It’s just like cheating on a test in high school. If you just copy off of someone else and don’t understand, the second you can’t see the test you’re cheating off of you’re toast. It’s better to understand. But this has a limit. I know python is built on top of some other programming language but i never once have had that impact the system I am building. Maybe that is because I am still earlyish in my career but maybe not. So in today’s context I often wonder, if AI can just fix the bugs it creates, then why does it matter if I know what it is doing? I don’t really know. But I do know that at the end of the day, who ever releases the code or imitates the agent that releases the code is the one who is held accountable. And if I am gonna be held accountable, I want to be confident that what I’ve built is going to work. I think the solution right now is to take advantage of the fact that u can ask an LLM anything you need to understand. So you may not need to know the nitty gritty of the code but you do need to at least high level understand what tf is going on. When we used to write code by hand, understanding at least to a certain degree was required to get the thing working. Now it is optional but I think there is huge upside to spending time understanding. So now if something that used to take you 4 hours takes you 5 minutes, that’s awesome, but I’d argue you should spend 25 minutes after, or honestly however long it takes, to understand what tf is going on. It still is gonna take less than 4 hours and you are gonna be much better off because of it. And the beautiful thing is that AI makes it easier than ever before to ask questions and understand what tf is going on. So instead of being 48x faster and having no idea what is going on, it’s better to be 8x faster and have a solid understanding..
dex@dexhorthy

Here’s what’s gonna happen: - you replace your code review with feedback loops (sentry, datadog, support tickets, etc) - you stop reading the code - software factory fixes everything - one day something breaks at 3am, agent can’t fix it - nobody’s read the code in 3 months - you have 3 weeks of downtime trying to re-onboard and fix it - you lose significant % of your contracts and users - your company is now dead

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Matt Ambrogi
Matt Ambrogi@matt_ambrogi·
One of the most useful tricks for agent evals: for each trial, output the model's reasoning. You see why the model is doing what its doing. Surfaces parts of the prompt and tool design that are confusing the agent.
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Michael Branconier
Michael Branconier@mike_branc·
Such a great point that big companies are essentially remote anyway. I’ve worked in person and I’ve worked remotely. It’s harder to connect remotely, but the pros 100% outweigh the cons for me. I’m more productive, I’m more efficient and my quality of life is better.
Alex Bouaziz@Bouazizalex

x.com/i/article/2018…

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Michael Branconier
Michael Branconier@mike_branc·
THIS is the upside to AI. It makes learning permission-less. The same way a kid who copies off of someone else can’t keep up when put on the spot with a test, you can’t win if you just blindly press command + y as a dev. If you’re naturally curious and want to learn it’s an amazing time. If u just are copying and pasting from chatgpt, you’re toast. Also important to remember, like always, that you and you alone are responsible for your output. It doesn’t matter if u wrote it by hand or used claude or n8n or whatever. You must be accountable for the outcome. You must understand how the things work. Because when things go wrong, and they will. Your ass is on the line and you better be able to figure it out. The more you offload to someone or something else, the harder this becomes. I suppose the question that comes next is if it even matters. If AI can fix its mistakes just as fast as it makes them, then who care? I think this is a valid question, but I really don’t think we are there yet, so I’d error on the side of understanding.
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