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Super excited to share with everyone the two ways I've been developing to make building your shiny app's UI faster, easier, and more pleasant: {gridlayout} and {shinyuieditor} (🧵1/5) #RStudioConf #RStats #rstudioconf2022
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A somewhat surprising lesson I recently learned building tool schemas for an agent harness: parameter names are more nuanced than needing to be well named, the harnesses that models were fine tuned on can impact tool call preferences.
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Quick post with more details: nickstrayer.me/posts/tool-sch…
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A pretty exciting endorsement!
This new AI Notebook IDE looks really promising from the folks at @posit_pbc (the folks who made the beloved RStudio).
It's super polished and has features like allowing you to control which cells the AI sees. Elastic License 2.0
opensource.posit.co/blog/2026-07-2…
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The Positron Notebook Editor is out of beta and ready for all your notebook workflows! I am super proud of the work the team did to build this notebook experience from scratch. Something we decided was necessary to have a fantastic notebook experience for data science.
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Check out the blog post Wasim and Cindy wrote announcing the GA launch: opensource.posit.co/blog/2026-07-2…
Give it a try and let us know how you get on!
Give it a try and let us know how you get on!
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Nick Strayer retweeted
"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"
This is exactly what I've been building roborev.io for
This is exactly what I've been building roborev.io for
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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After using Opus 4.6 for a while: I dont necessarily think it's better than 4.5. I've noticed more designs that it makes that are kind of obvious "I would not do it that way, let me fix it" than I had with 4.5. #ai #ClaudeCode
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Entirely possible that my workflow though was highly fit to 4.5 and I need to figure out how to work with a new model. If that is the case I really hope we don't have to tweak workflows every 3 months as a model comes out. It's exhausting. #SoftwareEngineering
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For more than a year I have been working on a brand new Jupyter Notebook editor for Positron. This is a ground-up build of a new Jupyter Notebook experience built to leverage all the knowledge and tools Posit/Positron brings to the data science table. 🧵#jupyter
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For example, the notebooks have best-in-class AI support by leveraging full notebook context and Positron’s existing kernel/interpreter infrastructure
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I got my start in programming with Jupyter notebooks and so they are dear to my heart. If you’re an adventurous data scientist, download the latest Positron and give it a try! Feedback is welcome and highly encouraged! posit.co/blog/announcin…
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@malco_barrett giving a great and super approachable talk on causal inference in R. Awesome work he’s doing with @sherrirose
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I spoke before the attributions slide! Work with @LucyStats and @travisgerke !
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📢The {ShinyUiEditor} is finally out of its "alpha" stage! 📢
We've taken off the big scary warning about using it and want you to take it for a whirl.
See my post about this on the Posit blog:
posit.co/blog/shinyuied…
#rstats #DataScience
We've taken off the big scary warning about using it and want you to take it for a whirl.
See my post about this on the Posit blog:
posit.co/blog/shinyuied…
#rstats #DataScience
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Nick Strayer retweeted
I just discovered ShinyUiEditor.
It allows to build Shiny Apps with drag and drops!
rstudio.github.io/shinyuieditor/
It allows to build Shiny Apps with drag and drops!
rstudio.github.io/shinyuieditor/
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New {shinyuieditor} feature: the ability to clean up render functions for deleted outputs.
Started from a template with a plot you don't need? You don't have to manually go in and delete the renderPlot() code after deleting it anymore! #rstats #shiny rstudio.github.io/shinyuieditor/
Started from a template with a plot you don't need? You don't have to manually go in and delete the renderPlot() code after deleting it anymore! #rstats #shiny rstudio.github.io/shinyuieditor/
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Nick Strayer retweeted
It’s official! The FDA has approved the first Shiny app submitted by the R Submissions Working Group. Read more on Pharmaverse blog, where our Appsilonians share how we used the Rhino framework to recreate the successful app for FDA's Pilot 2 project 🦏💙
pharmaverse.github.io/blog/posts/202…
pharmaverse.github.io/blog/posts/202…
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Forgot to post this when it went live, but the new {shinyuieditor} website built with @astrodotbuild and @tailwindui components is live! Such a nice building experience. #rstats #webdev rstudio.github.io/shinyuieditor/
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I'm pretty happy with the latest feature of the {shinyuieditor}: synced IDs between your UI and server code. Did you change your slider input ID to "numBins" from "bins"? Now any server code that uses that input will update too, so your app doesn't break! rstudio.github.io/shinyuieditor/
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Sneak-peak of the new landing page for the {shinyuieditor}. I've been rewriting it in @astrodotbuild and @tailwindui and man, it's by far the nicest website-building experience I've had. Things just work the way you'd expect and it's static first.
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