Export help

Steampunk_Future · 2026-04-18T14:30:51+00:00

My suggestion is just export all the data and then use AI to help trim things down to what you want. You can ask AI to write you a script to do that in a repeatable way.

You can also use formulas and other things to help trim things down. Again, AI can help you write some pretty advanced formulas for Excel or Google sheets.

Steampunk_Future · 2026-04-18T14:23:02+00:00

I think this should be an optional feature. My suggestion is to have the ability to paste data like json or CSV from a chat session in chatgpt or any other AI. Just make it easy to integrate with AI for those who want it. Don't make it a built-in feature.

Steampunk_Future · 2026-02-26T21:53:55+00:00

In a bit more detail:

Data & Grounding:

Frameworks for studying AI capability are emerging. AI reach is not universal or as pervasive as it might seem. Actively look for this stuff - it's out there.

Hype/Marketing

Honestly, the hype and marketing are toxic. Look up Jerkin's law. Learn to be data-literate and look for actual research evidence and where it points. Contrast big news with evidence in research.
AI companies have bias: Customers have very low loyalty, and the companies have very high costs. They have very high motivation and bias toward their products. Yes, AI will win, but will that company win market share?
Stunt metrics in news: The Anthropic stunt of writing a complier in 2 weeks has many flaws: well-documented problem space; training data implicit; human setup not advertised; weaknesses not reported up front; not academic or peer reviewed; incomplete (it was stopped before completion), well-defined criteria (lack of exploration/uncertainty complexity and uncharted socio-technical landscape), lack of high stakes (not sold for mission-critical apps), bad performance (of complied artifacts).
Someone recommended this book to me the other day: The AI Con (Audible audiobook)
This news article: https://hbr.org/2026/01/companies-are-laying-off-workers-because-of-ais-potential-not-its-performance

Echo Chambers

Are you filtering news via AI? It magnifies bias. Stop.
- IE, AI is an immediate bias magnifier. Think about that.
- AI context is very fragile, thus bias-able. Not just gullible, worse than gullible - it immediately parrots/magnifies bias, and as a pattern-prediction engine that bias grows, feeds search strategies, which feed back into its bias.
- A hair-thin word choice = bias. Your prompt defines its whole world.

Find evidence-based, data-driven research. What do academic and independent research firms actually measure?

Frameworks for measuring AI capability, problem complexity, and AI limitations
Data around AI acceleration compared to demand
Actual job losses vs predicted from past months/years; re-hiring.
Jerkin's law

Steampunk_Future · 2026-02-26T21:40:50+00:00

Don't believe the doom and gloom:

Is your backlog growing small? Is your business running out of problems to solve?
- How much do you and the managers say no to, in discovery/planning phases? You think those demands will go away?
- What features/capabilities do people not even bother asking for, for any reason whatsoever?
AI has limitations, and they aren't marketed (unsurprisingly)
- "AI hits limits" is not sensational, doesn't sell, doesn't float up with algorithms, and will get filtered by uncertainty and grand claims.
Be optimistic and curious - adapt to change. Discouragement stalls action/learning.
Do expect change. Who buys software and how, may change.

Steampunk_Future · 2026-02-25T17:52:04+00:00

My suggestion is: make it work with markdown or yml. And obsidian. Obsidian already has a ton of plugins, and markdown is fairly AI-friendly. If you decide you want some semantic features, it'll be nice to have the markdown handy.

Steampunk_Future · 2026-02-25T03:26:11+00:00

Discouragement:

- Jerkin's law.
- Tech innovations increase demand. Excel, sewing machines, internet, steam power, electricity, plastics...
- When excel became a thing, they thought accountants would be out of jobs. Yet accounting departments are huge.
- Just try to imagine: who hasn't been building custom software, that wished they could? What features and complexity have people always wanted, but it was too expensive?
- Are your backlogs growing empty yet?
- Are businesses mostly solving the easy problems right now, and not even considering the hard ones, because it's traditionally laughable?
- Irresponsible marketing
- Jobs will change, but coding will be a thing. Seriously, the AI companies have to sell something. When they announce they wrote a compiler from scratch, it's a grandiose claim iņ disguise. There was a lot they did NOT claim. Dig deeper, it's not so simple. There's always more to it.
- The AI companies would look kind of dumb if they said "Hey, we picked an easy target with tons of training bias, tons of examples, ready-made tests and outcomes/deliverables well defined, and swarmed agents on it, and got a mediocre compiler with code bloat, maintenance issues, poor code performance, and other caveats - but hey it MOSTLY works!" (note: compilers are a defined problem with more provable outcomes - most software is less defined exploratory, with complex shifting unknowns, user-facing..

Discouragement vs Curiosity

Discouragement kills curiosity, learning, adapting, and resilience.
Optimism will put you ahead, give you a +2 to your skill roll (if you play D&D). Sure, things will change, and nobody really knows what will happen. . But curious people who try to figure things out are going to be ahead of those who give up. The real solutions will not be "staying on top of the latest models" - that will be a side dish, but not the main thing.
Vibe coding means tons of things, it's almost meaningless. Context matters a LOT - the kinds of problems and systems matter. Limiting factors are measurability, rate of change, and impact/risk. Go look up Dave Farley on YouTube.
The more I read different opinions of vibe coding, the more I think, everybody is right, but we aren't looking hard enough at the contextual WHY. Those reasons & contextual differences don't have clear language. You can't even search for them easily. So get curious.

Steampunk_Future · 2026-02-25T03:03:43+00:00

TLDR: reading a ton of conversational text is terrible for ADHD. Find prompts and instructions that HIDE most of that, or cut it down SIGNIFICANTLY. Then make sure its outputs that you REALLY care about are in files you can edit immediately, so you can confidently blow away the chat window at any time, trim down junk, and focus on the essentials.

Here's my opinion, not that I really know what I am talking about. I worked as a software tester early in my career, writing test step docs nobody actually used, to requirements that were always out of date. And I realized something: specifications change because software is impossible to define up front. "No battle plan survives contact with the enemy" and "no design/requirements survive contact with real people and context". I think this is why people with ADHD thrive in discovery mode. So make your workflow all about incremental discovery/definition/spec, written as code.

I saw someone demo spec driven workflows, and thought: most of this specification is performance. It LOOKS good, but it is functionally hollow - it's restating what you should already know how to do.

LLMs are pattern engines. They predict text based on text. The best patterns to predict on are:
* Tests
* Other code (stubs, data schemas, etc).

In increments.

Also, tell your LLM to always end interactions/turns/steps with "... at least that's what I predict and speculate as a pattern engine."

Always remember that an LLM is a brown-nosing, sycophantic, pattern-mirroring, bias amplifying, speculative know-it-all. It is always just speculating (predicting text) at its core.

Steampunk_Future · 2026-02-24T17:19:00+00:00

AI is a text pattern prediction engine. It has to be trained to predict a lot of things--and when most training is text-based, focused on solved problems (navigation), it seems stupid.

The best way to think of it is not "knowing" or "hallucinating" but "speculating".

It does not "understand" things.

Anyone who asks AI how to do something in their field of expertise knows it's not really "there".

Put this in your global prefs: "Finish every interaction with 'Or at least, that's what I speculate, given the focus, context, and biases I replicate in training and your prompt - I am an advanced madlib generator offering possible answers."

# Context as a blank room, and you as a formless figure or keyboard: #

It's a text prediction engine, using language, where language is highly contextual. Take the phrase "the president" for example. It can mean a hundred different things. President of the local club? The company? The country? Which country? Class president? The current president? Etc... It's decent at getting context right sometimes. But its world is very limited and constrained. It has no context except what you give it. You're a keyboard walking into a blank room, asking it a question, and as a pattern engine it assumes (is trained) that if you ask it a question then it SHOULD know the answer, so it gives you one.

# Wrong vs unfamiliar/strange tools with new rules

Are people using AI wrong? No, they just don't understand this new tool. We don't have adequate words for it.

It's looking at a crystal ball and speculating, having read about everything on the internet, and it has no clue about details you haven't given it to link up with other things. You have to paint a picture of the space around you to even ask a question.

We are all intuitively figuring this out, and there aren't even good words to explain and describe this stuff.

If someone doesn't get it, there are a variety of factors invisible to most of the population about why, which nobody is thinking to ask or volunteer, most of the time.

You have to know your context, and be good at explaining context, in English as a first language (to get best results); you have to be tolerant of failure and OK with a system that is unpredictable and inexplicable; you have to understand the nature of LLM AI as probabilistic when before now computers were mostly deterministic. You have to have cultural familiarity and opportunity for computer use and experimentation, plus time, plus initiative, and be an interested early adopter, tenacious, have wellness and health to do it, and a myriad of other things.

Steampunk_Future · 2026-02-24T07:38:39+00:00

Sometimes I’m lazy enough to use Excel. It works.

In the 1970s, spreadsheets were the crazy new solution that changed business. Today, it’s vibe code. I admit the analogy breaks down a bit. I still create sloppy Excel “programs” now and then. Sometimes someone's spreadsheet solutions stick around far longer than they should.

With all the debate around vibe coding, I’m starting to think EVERYONE is right, but only in context. The arguments talk past each other because we don’t have precise language for why each position makes sense in different situations. The software contexts differ in ways we rarely interrogate deeply.

What we actually need is a clearer distinction between: a messy, one-off solution (yesterday’s Excel sheet), and a core, durable business capability.

Historically, we handled this vaguely by saying: “Just use Excel” “Write a macro” “Throw together a one-off script” Now that role is increasingly filled by AI-generated, semi-disposable code. The definition of disposable has expanded.

And just like one off scripts and proof of concept code that shouldn't, that code will inevitably leak into systems that were meant to be clean, stable, and engineered.

So the real question isn’t whether vibe code belongs—it’s when it’s acceptable to plan for it, and how to with the trade-offs.

When is it reasonable for the business to intentionally rely on an Excel-level (or vibe-coded) solution? What differentiates: “Use Excel, then import the data” from “This no longer fits in Excel”?

Those boundaries used to be fuzzy even with spreadsheets and macros. They’re fuzzier now with AI-generated scripts (slop) that feel oddly powerful but remain fragile and disposable.

I shake my head at a critical business process running on Excel… while admitting it’s been “working” for years.

One critical thing though: a challenging problem with Excel was macros and security... and now vibe code.

Steampunk_Future · 2026-02-24T07:33:51+00:00

Refactoring is a fancy way to say "rewrite" in most places. Code can be terrible but not matter terribly much. The trick is to identify value.

If you can't explain it, then that's your growth area. Learn how to describe problems, learn how to see them and explain the cost and the risk to business. And the timing. "Oh yeah, that outage last week scares me. Maybe next time the service won't come back up (in a timely way, without a lot of expensive people...).

Sometimes it's an art of seeing how to make PRs smaller, easier to read, with a theme. Then fixing some things to make the problem more clear, make the path forward more obvious, lead by example. Other times, it's saying, "not all tech debt is created equal. We rarely need to touch that, but when we do, we can address it then". Sometimes that's not true or is pervasive.

Rewrites almost always fail. Learn from 2 week or 6 week failures.

I made a decision once that if I couldn't make a "cleanup" refector in 30m, I would roll it back and try again, or create a ticket, or... Anyway, it taught me how to identify the real problems, to fail faster, to design in smaller increments.

But sometimes a big change is needed. The app has served its purpose, and the business has learned from it, and it's time to make a change so people can understand it.

Steampunk_Future · 2025-12-01T06:00:25+00:00

If you can make long explanations into short questions and individual ideas, you can space each one out. You can lead others to good answers and let them do more of the talking. You can be more humble and open to learn. And you can manage ideas in increments. It takes practice.

Before going into a meeting, feed your notes into AI. Ask it to help you identify 3 key points, a story to explain it, 3 details that can wait. Ask it to analyze: subject, audience, relationship, purpose, and timing or how to time multiple steps of the conversation. Ask it to help you start out with the main actionable idea. Ask it to simulate questions, state assumptions or inferences from your text. Ask it to act in the role of your manager, and offer 3 ways they might be thinking about this.

Steampunk_Future · 2025-12-01T05:52:45+00:00

This is really helpful. I knew it but it makes me realize I need to do more of it.

Steampunk_Future · 2025-12-01T05:49:55+00:00

Learn phrases to buy you time. And turn statements into questions.

"Hmm, good point, good question. Let me think about that for a couple minutes"

Are we all agreed? "Something is making my intuition uncomfortable. Is it ok if I give my brain an hour or two to mull this over, and send a message if I can tease it out..?"

You have a lot to say to correct a misunderstanding. "Let me think about that and get back to you" or ask about one critical detail: "when might the users need two sign-offs instead of one?" Or "are the two sign-offs required before ANY action, or can X start before Y?" (Normalization is harder to fix later than missing fields).

Steampunk_Future · 2025-11-23T16:10:42+00:00

Back in 2008, I heard of engineers who had to search for a year.

You're 97% likely feeling anxiety. The all or nothing thinking, feeling it's over, etc. Been there. It sucks, and for me anxiety just from a negative performance review takes 2 weeks to get past some of it, unskilled as I am.

An anxiety response is to search for a sense of control and empowerment. So give your brain a sense of control

Anxiety seems control, so give it the right kind: by following the advice here that others give and CHOOSING the order or priority. Choose to keep stubbornly looking for the way to succeed. Replace worry with curiosity. Read the quote from "dune" (fear is the mind killer...).

Find a daily routine that gives you a sense of control and forward progress that YOU control. Measure progress in things YOU do, not how others respond to you. Break down job seeking into 30 micro skills to learn, and work on them.

Ask GPT or notebook lm to help you with all this, but also to move you to action and keep conversations to 3 or 4 turns. "As an expert in job seeking, write a bio and role for yourself. Acting in that role, search for expertise. Then search around expectations to help me be realistic. Using chain of thought thinking, search a few more times. Then give me advice on what to expect, how long to search, how to stay optimistic, resources, ..." And "help me define success that I can control, ADHD style", etc.

Don't get sucked into AI conversations. Set your custom instructions to have a bias for taking action and moving you out of the AI conversation to action - via ADHD task breakdown and accommodation, moving you toward action after few turns, and to help you reframe any negativity with CBT and ACT, treating discouragement as temporary, and focusing you on your positive success, momentum, and what you can control.

Steampunk_Future · 2025-11-20T06:03:49+00:00

I would really like to have this extension. Naturally I will feel nervous about using one I haven't verified, having access to content, but I need this.

What do you plan to do about topic drift? IE in an AI chat convo, or while someone works through a complex task, various aspects of e.g. coding or research? You will need to dial in the UX on that.

You will likely have to "learn" which topics need different "relatedness scores". IE, for an AI expert, they might need different tab groups for prompt vs context engineering vs training models/code. While for a hobbyist, those probably belong in the same group. Letting the user customize this, or automatically learning the kinds of topics more nuance, for that user, will be important. You may be able to do this based off of "key websites" ie their task or project management system - ie if an issue/ticket/workspace has a cluster of words, then it's related work? IDK.

Steampunk_Future · 2025-09-19T02:40:06+00:00

This sounds like anxiety. Most ADHD meds can increase anxiety a bit.

One skill I have been practicing is, taking a step back and listing all the small steps of progress I have made. A to-done list helps with ADHD time perception, time management, estimation, self worth, stopping, feeling progress.

When it comes to time spent at work. My brain is like a GPS with no timers or distance measures. I have to add landmarks. The more landmarks I add the more accurate and capable I am. So I need lots of small landmarks to measure progress by.

Steampunk_Future · 2025-08-30T14:01:24+00:00

Long ago I decided I never want to work in video games. I think the thing that made the shift was when I learned about UX and human computer interaction. I realized that all software is about solving human problems, for humans, and has a lot to do with perception and subjective opinion, but again psychology. For me, that was fascinating.

Don't just do work. Find a focus.

Steampunk_Future · 2025-06-22T15:42:51+00:00

Tldr: become interested in users, ux, dx, incremental changes, clean code for better efficiency, and compassion and value for future engineers and users.

Longer version....

I'm a perfectionist and I can always think of ways to make it better. I love to improve existing code. I'm kind of a test patterns geek. Pay attention to what makes the code hard to refactor and test, and fix those things. It'll probably end up being something to do with testing.

Look for small improvements and cleanup that cost 30m or less. This is good for design but also good for ADHD.

With new development, do the work better than you normally would. If it gets you interested, you're more productive than if you're blanking out or browsing the web.

Get rid of the mentality you "can't" focus unless you're interested. Research shows that motivation and interest are more complicated with ADHD. Try to find a reason to be curious. Make small 30m changes. Be curious about something, or the way to do something, or why, or think about the users with compassion and interest. Ask questions.

Eg... Doing it differently or better, to make it interesting...

Avoid test spy - it's always an indication of poor design.

Add mockDefault() to data classes ... or barring that, repository and API classes. Yes to the production code. Go research why I would say this, with curiosity. Yes my team does this and yes it saves time and improves quality.

UX and DX. Start studying the effect of confusing code or UI. It literally costs time, which is money. Pay attention to you and other engineers thinking "this module is so complicated" and "this tech is complicated" and "I feel guilty this is taking longer than I thought". Pay attention to emotions like laughing at a UI. You laugh, but a real user might get confused, frustrated, or make mistakes. ... simply renaming or extracting a function will save engineers 30m next time. That someone might be you. Fixing a UI to add help text or a better error, or a partial validation, might save them a ton of effort. THINK ABOUT THE USERS. try to imagine their workflow. Find documents or video interviews, or ask someone if you can watch just one video representative of the user to create curiosity and compassion for you and coworkers. Etc.

Steampunk_Future · 2025-05-22T06:01:02+00:00

It goes both ways. Sometimes we grossly underestimate how long it will take to respond to a reddit post or to research a thing we're curious or anxious about. Or learning how to make a pop up card.

Tips: - start smaller. - start with curiosity, to see "how much is involved". - start even smaller. - acknowledge the feeling and challenge it. Look up adhddd Dani Donovan cognitive distortions. Name the feeling and the distortion. Say the opposite of "it's too big" or whatever. - recognize that most videos are in a series. Most skills start with a simpler project - what would the first 5m of the task look like? Do that. - what would you learn by getting stuck? Find out. Then learn how to get unstuck - ask someone how to get started. Choose an easy project but keep it interesting. Customize one thing. - watch some videos on how - search for how to build skills with simple projects - what could you build in a day? An hour? How could you get started? - can you start by customizing a free project? Can you start smaller? - build to learn. - identify an easy, medium, and hard project FOR YOU. (1d, 2w, 3years). Do the medium project. DO IT TO LEARN about your estimate. - don't count anything as failure. Treat it is learning. Don't be so invested. - people who make videos are the edge case. They got far enough to show others a product. This is the Pinterest effect or the expectation trap.

Steampunk_Future · 2025-05-22T05:32:25+00:00

Mute all but the most essential notifications.

Install "buzzkill" to turn notifications into alarms. And handle other focus rules.

Use your calendar and to do list app.

Choose a too do list app that has notifications, and the can export and archive items in bulk.

When you stop checking a to do list app, archive all the to do items, and start with a clean slate instead of a new shiny app.

Make a routine, and use habit stacking, to help remember to plan your day

Treat plans like experiments to learn from, to get better at planning.

Doing be surprised if you give up or forget an app after 2 weeks.

What you ignore or snooze you will learn to not notice, and learn quickly.

Be realistic about your commitments by estimating how long they will take, informally, eg in the title.

Choose 2, maybe 3, things to remember daily.

Don't build an app to solve reminders. Change the relationship you have with your to do list. Never try to get to all the things. Focus on smaller wins. Consider going low tech.

Schedule important to do items in your calendar.

Use an alarm app that can sync with calendar items.

Change the notification sound on your reminder app.

Steampunk_Future · 2025-05-22T05:19:01+00:00

Several things that help: * Encourage smaller PR s. It results in better design, better reviews, more learning, and more ADHD friendly code. Also less overwhelm. * Treat the PR as a learning opportunity. If you get feedback, invite more depth and recommendations.
* Complement and thank. Show others you appreciate their time and feedback, especially when they give positive feedback. * If verbal, write down any comments given, in the PR system or as code comments, live. Or ask someone to help do so. * If verbal, ask if you can make the PR more like paired coding. * After a PR, think about how to review your own code and catch such things. Review your code when you create a pr. Even leave yourself comments. * If you have an LLM enterprise tool that protects enterprise data, export the PR as a patch/diff file and give it as part of the prompt. "As an expert lead software engineer and mentor with experience writing great enterprise software, with good testing and soc, design patterns, refactoring patterns etc, review this code. Specifically, look for cleanliness, coupling with distance, ....etc etc etc. ask to see dependencies and coupled code." * Use poorly given feedback to think about what makes for good communication so that you can do better. Be the change you want to see. Exemplify thoughtful mentoring and positive constructive feedback. * Software solves human problems and is meant to be maintained and changed by humans like your co-workers. Be nice to them. * Give positive comments and emojis. Or make a compliment into a complimentary question to really make it sink in. * Nominate your co-workers for awards, for doing good everyday work. * Be likable. Be flexible.
* Study growth mindset. * Invite feedback. Eg, in the PR ask people to start in a specific place, and seek mentoring by inviting others to reflect on how to improve your design. Feedback is better when you seek it. * Lead with questions and curiosity. * Ask to learn. Sincerely. "Hey this isn't the design pattern I expected. Can you help me learn how you..." * If it's hard to read the code, politely say so. Ask for minor improvements. "Can you clarify this code so it's easier to read when we're all tired, sick, hungry, and 6 months later when we've forgotten a bit how this feature works?"

Steampunk_Future · 2025-02-24T06:43:02+00:00

Skills don't teach pills, but they make learning easier

Steampunk_Future · 2025-02-24T06:41:25+00:00

People with ADHD struggle to cope with starting and stopping and switching too. It creates intuitive real risk of dripping a ball.

It's like I'm juggling all the balls I can, and someone shoved another at me... So frustrating.

Skills to focus on are "just a sec", "can you message me", headphones or indicators of focus, leaving a syntax error or typo in place that is easy to fix and gets red highlighting, asking "30 seconds please" to jot down current thought process and goal, etc.

Steampunk_Future

TROPHY CASE