Roger Barnes

@amix3k I genuinely don't know what I'd use an activity log for, so not sure what to ask for. Most of the things I need relate to clarifying intent, prioritising in context & getting out of the weeds - all more related to forward view than backward

The team is making significant progress on the activity log. Soon you'll be able to export it to Markdown and feed it into an AI. We're working to make Todoist play nicely with AIs (on top of our MCP and official todoist-cli support!) Anything else you would want to see improved with the activity log?

@levi @bcherny +1. Multiple times now I've had to ask to see the plan first, which breaks the question asking flow

Often in plan mode, it'll write the plan and then ask me additional questions, like I've read the plan. The problem is I can't see it -- either I open another terminal and read the /tmp/*.md file or i have to escape out to send /plan. Would be sweet to be able to view the plan while in the question answering tool ui.

Claude Code 2.1.0 is officially out! claude update to get it We shipped: - Shift+enter for newlines, w/ zero setup - Add hooks directly to agents & skills frontmatter - Skills: forked context, hot reload, custom agent support, invoke with / - Agents no longer stop when you deny a tool use - Configure the model to respond in your language (eg. Japanese, Spanish) - Wildcard support for tool permissions: eg. Bash(*-h*) - /teleport your session to claude.ai/code - Overall: 1096 commits github.com/anthropics/cla… If you haven't tried Claude Code yet: code.claude.com/docs/en/setup Lmk what you think!

@sussanley "Our plan is clear" is usually accompanied by some kind of plan. Did you forget an attachment?

I spent today in NSW meeting businesses that want to grow, hire and invest, but are being held back by soaring power bills under Labor. Our plan is clear. We will deliver affordable energy for families and businesses while reducing emissions in a responsible and achievable way. Under the Liberal Party emissions will be reduced: * On average year on year, for every five year period of Australia’s Nationally Determined Contribution. * In Australia’s national interest by doing our fair share considering the real performance of comparable countries. * As fast and as far as technology allows, without imposing mandated costs on families or industry. Affordable power. Responsible action. That is our plan.

.@DJKanban Inc just hired its first 3 employees. What could go wrong? (Narrator: Everything) #vibecode

Naming things is hard, just ask @UnderArmour

Voting in Bradfield and undecided? My frustration with politics has turned to hope since meeting @Nicolette_Boele and volunteering. A true community independent. See for yourself: youtube.com/watch?v=X2c7SD…

@amix3k Examples of conversational things (I've started dabbling with MCP for these myself): * Reschedule anything due that looks work related until Monday * Suggest tasks that to be moved into existing sections in the work project * Tag priority tasks that I keep rescheduling for review

@amix3k 2 things: * It depends what it can do. I'm interested in things I can't already do from the app that's already on my device. * Assuming it does net new useful things, I'd be happy for the conversational interface to simply be in the todoist app, at least to start with

Would you use a conversational interface to manage your Todoist tasks directly from WhatsApp or Telegram? E.g., by sending/forwarding a message, making a call, or sending a voice note? It would be like having an assistant. How excited are you to use something like this?

I'm done wringing my hands about the state of #auspol parties. This was my first time doorknocking alongside hundreds of volunteers from all walks of life. It was fun and rewarding. It's time for a positive, representative change in Bradfield.

Happy clamshell packaging injury and fresh battery hunting day, to those who celebrate

Eminem v LLM His coffee's ready, 𝚙 is weak, cloud bill's heavy There's vectors in his pinecone already, similarity He's nervous, but on the servers, he's got json ready To drop prompts, ...

"This is either genius or bollocks" is almost always how genius emerges. You've gotta be ok with that. Keep going, keep creating.

@sqs You don't have to change code if you only ever make new messaging apps.

Writing new code is the easy part. Changing code in existing complex codebases is the hard part. Always has been.

Goals are for people who care about winning once. Systems are for people who care about winning repeatedly.

Semicolon doing some heavy lifting to separate headlines

@infobeautiful Interesting, but as an example of data viz/infographic, truly awful.

Interesting. How much the UK's free National Health Service (NHS) interventions cost (although they are given for free). Via reddit. bit.ly/IIB-NHScosts

@Rainmaker1973 Remember to tip your valet

Caption this

Hey #ProductManagement friends, liven up your next "it depends..." with one of these

"True happiness, I realized, lies in the simple act of bringing my ideas to life." 🔥

I can't tell you how elated I am that I could generate this thread from @headinthebox's talk. I've written about how I've been taking screenshots of YouTube videos and podcast players for a decade, and how I've used various LLMs to analyze those images to extract: - podcast name, episode name, current playtime I then overlay that info over the transcript, and I can easily retrieve the relevant exciting moments, and generate summaries... More here: linkedin.com/posts/realgene… I've seen people like @tsarnick and @swyx generate fantastic video excerpts, but the SaaS tools I found required too much manual interaction — I'd have to input the time codes myself. But I was talking with Steve Yegge, and the idea dawned on me that I could write my own program to do this using ffmpeg. Steps: Get the videos, extract the designated time ranges, burn in the captions using the transcripts. Maybe with a coding assistant, I could do it in under 2 hours? We paired together, with Steve being my CHOP coach (Chat Oriented Programming). And to my utter amazement, using @SourcegraphCody, I got my first video excerpt generated 1h 45m into our session — of which the first hour was mostly getting oriented, getting data together, etc. We recorded the whole thing, and he'll publish it soon. But here are my reflections: - CHOP is a new skill, but it can definitely be learned — Steve would catch me often saying, "This isn't very CHOP. You're doing a lot of typing." This was code for: stop typing, and think instead about how to get the LLM to do more work. - Cody for IntelliJ is great — it uses Claude 3.5 Sonnet under the hood, and I used the following two modalities: - Chat window for multi-turn iteration: write this function, write some tests, no different tests, tests are failing (here's the error messages), fix the code, etc. - Inline chat: highlight the function, and write a prompt like: "make the ffmpeg captions more Tarantino-like". Haha. - LLMs are great at writing tests! This becomes critical to gain confidence that the code it generates actually works. (As you'll see in the video, having super fast feedback is critical: it was like night/day when I started using Hyperfiddle RCF, from @dustingetz because I could get feedback with milliseconds) - there were at least two times when I was a little surprised at how the LLM struggled to fix the code it wrote (e.g., merge overlapping time ranges) — I finally got things working by giving it hints (e.g., add an :end map entry, so you can do the computation more explicitly). - it's super handy to have ChatGPT or whatever open to the side — to do ad hoc research. - I feel like I got done in 2 hours what normally would have taken 2 days — before we started, I told Steve that this problem falls into the category of what I'd call: "not this month" Merely the idea of struggling with ffmpeg would make me not want to tackle this. But CHOPping (writing a prompt) to "write a function that takes an MP4 file and an SRT transcript, and overlays the captions at the bottom", and seeing it work within 5 minutes was absolutely amazing. - my big takeaway and puzzle: that function was super easy. But other problems were much more difficult — like merging overlapping time ranges to extract, finding SRT time ranges that overlapped causing duplicate captions. It's like the "how to draw an owl" joke. Sometimes the LLM can draw the whole freaking owl in one shot. Amazing! But so many other times, when you're dealing with lots of constraints, it takes a lot more effort to draw the owl — it's like you have to create 4-5 different "tween frames", to guide the LLM on what actions to take. I feel like there's an intuition I still need to gain about what LLMs can and can't do well. Just like in CS, we know that regular expressions cannot count — that requires a stack. Similarly, there's probably heuristics of what LLMs can and can't do, and knowing those limitations will make using CHOP much more effective. More to come later! And I'll post a link to the video of me pairing with Steve when I get it.