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@meb

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@meb
How I would define an AI agent at the start of 2025: In abstract, a piece of software that can achieve a certain goal, and uses AI to navigate the fuzzy path of achieving that goal. More specifically, a combination of - Goal - Context management - Underlying model - Tools (datastores and functions with effects) - Prompting & self-prompting strategies (including delegating to other agents) Example: A geocoding agent Goal: Parse content from a sentence and geocode it Context Management: Trimmed sliding window. We only need the very most recent messages to get the job done. Underlying model: A simple model like 4o mini is more than enough Tools: A function to search cities with inbuilt query match ranking, and a function with access to a Google Maps geocoding API Prompting: Single turn. The agent should be able to get the job done in a single exchange, or ask the user to clarify the location if needed
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Star => Add to list => proceed to forget about repo existence
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Until recently, gpt 4o mini has been my go to for lots of agents given its low cost and latency. Did some tests today with Gemini 2.0 flash, which somehow is even less expensive, but supposed to be full 4o parity and got amazing results, especially with it following instructions very well. Shoutout to @alexpaden for sharing the tip on xml-ish tags for your prompts. Seems to be more machine readable, but also makes it way easier to structure
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Today, for the first time in a while, I solved an issue by going from stackoverflow, to Reddit, to the official docs. Nostalgia vibes
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Fun MacOS fact, there is a built in Automator app you can use to do stuff. Used it to create a “quit all” command which closes all apps on my laptop. Helps starting over with a clean slate
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I like this. Logical next step after the previous transition we’ve seen where people are moving to hiring Product Engineers, not just Software Engineers
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I’m in. Sounds great. Wanted something like this for ages that could provide a curated aggregate of various technologies and practices for my own keeping up to date needs
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Vibe marketing is also becoming a thing. Building is fun, but selling makes you free
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One thought I had the other day; I’d love to have access to tradfi through onchain rails. So being able to invest in the S&P or ETFs using my USDC would be amazing
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If agents will become a part of our lives, then I think they should also follow human social conventions. If someone tells me 3 things im doing wrong unsolicited, even though I like feedback, it’s a bit unpleasant. If someone approaches me, says they checked what I’ve been up to, and says they have some candid feedback to share and would ask me if I’m ok to share, that’s totally different vibes
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I think AI should be a congruence layer; ie helping people practice what they preach. That said, it doesn’t need to be an unsolllicited congruence layer. So if someone is happy deluding themselves, and you have no personal interest in investing the energy to help them win, let them be
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As @kompreni said, it's gonna be the pooled WETH. Haven't seen the code in a while, so would have to check.
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First time vibe coding yesterday (swift in cursor). Very cool experience and moved ahead incredibly fast compared to the old days of reading the docs, and moving up the stack from "hello world" when working with new languages. I don't think all devs are cooked yet, but this has already passed the level of the average "copy paste stack overflow without caring" dev. What I'm enjoying: 1. Being able to spend more time in product land, versus figuring out syntax. 2. Reducing the barrier to porting my engineering skills to a different language. I think LLMs will be an awesome supporter for the mobility of experienced engineering talent between language ecosystems. 3. Setting up boilerplate and screens way faster, so I can focus on iterations Speedbumps: 1. Architecture. Getting the AI to follow rules such as decomposing screens into different files, and explain certain design decisions it makes. 2. Verbosity. Feels like too much written some times. I generally have to prompt for simplicity.
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Out of principle, I wouldn't commit secrets to a repo, even if they are secured through encryption. The nice thing about a CLI script, is you could passport through some other auth, then let it do the fetching. Bonus, if you do some secret rotation, you could just ask the team to all rerun the script again and refresh secrets.
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I've used a .env.example in the past to at least have a sane list of which values I even need, along with none sensitive smart defaults. For then populating this, I think some form of a script that could tap into a secrets manager, copy .env.example to a .env.local or .env.test would be the way to go
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Interesting, everyone else here recommended Swift. Which are the criteria guiding your recommendation to use React Native?
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Thankfully, ChatGPT should be able to educate me, and help transfer over my existing builder skillz What specific things will I be grateful about?
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Out of curiosity, which features do you enjoy? My experience has been in TS / Python / Solidity land
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Infrequently. At this time, I'm more interested in shipping one off ideas and publishing to App Store. Sounds like Swift is the way to go. I've suffered enough in the node ecosystem (which I still love and use on a daily basis), that I really don't need to add React > Apple compatibility issues.
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“online community of circle-jerkers that engage in abstract philosophistry, drop vacuous platitudes, and vaguepost their way to strategic ambivalence” Based way to describe traditional French media and intellectual circles
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