Tim Watson

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Tim Watson

Tim Watson

@TimWatson

CTO/Cofounder @intro Backed by @a16z & @sevensevensix

Los Angeles, CA 参加日 Şubat 2009
742 フォロー中6K フォロワー
Sawyer Merritt
Sawyer Merritt@SawyerMerritt·
Co-founder of Uber, Travis Kalanick on Waymo vs. @Tesla self-driving: "Waymo is obviously ahead. Their issue is manufacturing, scale, urgency, and fierceness. Then you’ve got Tesla: fundamentals, science, hard mode times 100. When does the ChatGPT moment happen for vision? It’s super inspiring, but what’s the timeline on it? And then there are a lot of other little guys that don’t really have the stuff yet." (via new @theallinpod interview)
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Tim Watson
Tim Watson@TimWatson·
About once a week a waymo gets stuck in this alley for no reason. Sometimes just sits there for half an hour, sometimes backs all the way back down the alley. Been happening for over a year
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Kenton Varda
Kenton Varda@KentonVarda·
Worries that software developer jobs are going away are backwards. There is SO MUCH software to build right now, that previously wasn't possible (uses AI directly) or wasn't cost-effective (too niche). We're going to have more developers, and orders of magnitude more software.
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Eylon Levy
Eylon Levy@EylonALevy·
All the world’s worst people are really sad today.
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Tim Watson
Tim Watson@TimWatson·
I've been using a few different code review bots for a while now and @Macroscope is easily the best one. Still catches things no matter how thorough I am before I push
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Tim Watson
Tim Watson@TimWatson·
AI will always need more data but they’re good enough now that they can run experiments and make their own data
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Tim Watson
Tim Watson@TimWatson·
.@WillManidis ----------|---- @mattshumer_ Definitely not nothing but also not doom and gloom. Capable people will be more capable. 100 years of progress will be compressed into 10-20. Everything will be alright
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Tim Watson
Tim Watson@TimWatson·
In the history of technology when things become easier to do more people do them. A lot of things are about to become a lot easier to do
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Aditya Agarwal
Aditya Agarwal@adityaag·
It is very clear that we are not in any kind of AI bubble. If coding is anything to go by, the amount output that will be produced is going up by 100-1000x. We are vastly under-prepared in terms of the electricity, compute, memory and token requirements for the coming years. This is going to happen to every domain that knowledge workers operate in.
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Tim Watson
Tim Watson@TimWatson·
It is wild how good AI agents have gotten in even just the last few months. And this is still just the beginning
Greg Brockman@gdb

Software development is undergoing a renaissance in front of our eyes. If you haven't used the tools recently, you likely are underestimating what you're missing. Since December, there's been a step function improvement in what tools like Codex can do. Some great engineers at OpenAI yesterday told me that their job has fundamentally changed since December. Prior to then, they could use Codex for unit tests; now it writes essentially all the code and does a great deal of their operations and debugging. Not everyone has yet made that leap, but it's usually because of factors besides the capability of the model. Every company faces the same opportunity now, and navigating it well — just like with cloud computing or the Internet — requires careful thought. This post shares how OpenAI is currently approaching retooling our teams towards agentic software development. We're still learning and iterating, but here's how we're thinking about it right now: As a first step, by March 31st, we're aiming that: (1) For any technical task, the tool of first resort for humans is interacting with an agent rather than using an editor or terminal. (2) The default way humans utilize agents is explicitly evaluated as safe, but also productive enough that most workflows do not need additional permissions. In order to get there, here's what we recommended to the team a few weeks ago: 1. Take the time to try out the tools. The tools do sell themselves — many people have had amazing experiences with 5.2 in Codex, after having churned from codex web a few months ago. But many people are also so busy they haven't had a chance to try Codex yet or got stuck thinking "is there any way it could do X" rather than just trying. - Designate an "agents captain" for your team — the primary person responsible for thinking about how agents can be brought into the teams' workflow. - Share experiences or questions in a few designated internal channels - Take a day for a company-wide Codex hackathon 2. Create skills and AGENTS[.md]. - Create and maintain an AGENTS[.md] for any project you work on; update the AGENTS[.md] whenever the agent does something wrong or struggles with a task. - Write skills for anything that you get Codex to do, and commit it to the skills directory in a shared repository 3. Inventory and make accessible any internal tools. - Maintain a list of tools that your team relies on, and make sure someone takes point on making it agent-accessible (such as via a CLI or MCP server). 4. Structure codebases to be agent-first. With the models changing so fast, this is still somewhat untrodden ground, and will require some exploration. - Write tests which are quick to run, and create high-quality interfaces between components. 5. Say no to slop. Managing AI generated code at scale is an emerging problem, and will require new processes and conventions to keep code quality high - Ensure that some human is accountable for any code that gets merged. As a code reviewer, maintain at least the same bar as you would for human-written code, and make sure the author understands what they're submitting. 6. Work on basic infra. There's a lot of room for everyone to build basic infrastructure, which can be guided by internal user feedback. The core tools are getting a lot better and more usable, but there's a lot of infrastructure that currently go around the tools, such as observability, tracking not just the committed code but the agent trajectories that led to them, and central management of the tools that agents are able to use. Overall, adopting tools like Codex is not just a technical but also a deep cultural change, with a lot of downstream implications to figure out. We encourage every manager to drive this with their team, and to think through other action items — for example, per item 5 above, what else can prevent a lot of "functionally-correct but poorly-maintainable code" from creeping into codebases.

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