Sugarbug

17 posts

Sugarbug

Sugarbug

@Sugarbug_AI

Workflow intelligence. Every signal, understood. You spend 25% of your week moving information between apps. Sugarbug makes it 0%.

شامل ہوئے Şubat 2026
2 فالونگ24 فالوورز
پن کیا گیا ٹویٹ
Sugarbug
Sugarbug@Sugarbug_AI·
Your tools don't talk to each other very well. Linear has no idea what's in your Figma comments. Slack doesn't know your calendar is packed. You end up being the integration layer – checking 8+ apps every morning just to figure out what happened the day before, and moving information from tool A to tool B That ritual eats about 25% of your work week.
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Sugarbug ری ٹویٹ کیا
Para ✴️
Para ✴️@get_para·
1/ Announcing Transaction Permissions ✴️ We brought the best of modern authentication to onchain approvals Cryptographically scoped to an app, customizable, and built for real fintechs and apps In partnership with @eco and @aave
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Sugarbug
Sugarbug@Sugarbug_AI·
@aakashgupta It's not just product people. People across all roles and industries deal with the same firehose of information & logistics. It costs them 25% of their work week, and they don't even know it. The best tools these days unlock more time for critical thinking and strategic work.
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Aakash Gupta
Aakash Gupta@aakashgupta·
The PM job market is splitting into two groups right now. Group A is still writing PRDs from scratch in Google Docs. They spend 4-6 hours per document. They manually pull competitive intel. They format stakeholder updates by hand. They're working harder than ever and still falling behind on roadmap velocity. Group B built systems. They have CLAUDE.md files tuned to their product context, custom skills that encode their frameworks, and PRD writers that produce 80% of a shipping-ready doc in minutes. They spend their freed-up hours on the work that actually compounds: talking to users, building relationships with eng leads, thinking about strategy. Group A thinks Group B is "cheating" or "not doing real PM work." Group B shipped three features last quarter while Group A shipped one. The gap between these two groups is accelerating because the system builders are iterating on their setups every week. Each iteration makes the next output better. Each saved hour gets reinvested into higher-leverage work. Meanwhile Group A is running the same manual playbook from 2022. I built my system over 100+ iterations. Tested what produces output I'd actually ship vs what produces AI slop I'd throw away. Now you can skip all of that and start from a working setup in 60 seconds. The PMs who grab this will compound. The ones who bookmark it "for later" won't.
Aakash Gupta@aakashgupta

Most people try Claude Code once and quit. I wrote the guide that fixes that. Memory, skills, CLAUDE.md, and 8 specific workflows for Code + Cowork: news.aakashg.com/p/claude-cowor…

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Sugarbug
Sugarbug@Sugarbug_AI·
@ArthurzKV @AlexanderTw33ts wild that the trait most workplaces punished for decades is now the one they need most. the tools changed, the humans didn't.
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Arthurz
Arthurz@ArthurzKV·
@AlexanderTw33ts funny how ADHD context-switching goes from weakness to the ultimate advantage now that agents are hot.
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Alex
Alex@AlexanderTw33ts·
maybe the real autist/adhd advantage is that we can move up and down abstraction layers when tech like this comes along we don't even notice the change agent-maxxing feels exactly the same as writing x86 did in my first year of college i'm typing in a computer, problems are being solved, my ideas are coming to life, shareholder value is being created its not that deep bro stop getting attached to your z value on the fractal tree
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Mo@atmoio

I was a 10x engineer. Now I'm useless.

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MJ Miller
MJ Miller@Persist_Change·
@JJEnglert This is perfect. I’ve been wanting to jump into Codex but also not wanting to ‘thin myself out’ across too many tools.
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JJ Englert
JJ Englert@JJEnglert·
It’s time. Going to do a Codex 101 video + guide this week for non-developers. Been using codex for a while now, especially after hitting limits all week in CC, and it’s gotten insanely good. Everything you’ve built in CC transfers over too. I’ll show you everything you need to know to transfer, get started, and tips to customize your setup. This will make it so you can choose your tool of choice. Anything else I should cover? Let me know.
Peter Steinberger 🦞@steipete

Oh right i realize hell freezes over, we reached the point where app > cli That combined with the speed increase also means less windows necessary, codex goes brrrr now! developers.openai.com/codex/app/

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Jyoti Dwivedi
Jyoti Dwivedi@DwivediJyoti786·
IND vs NZ Final on one side 🏏 Cohort class just started on the other 💻 Multitasking mode: Watching the score 🤝 writing code Came for the match… Stayed to contribute. 🚀 Cohort people its time to learn.... 🥳 #chaicode #chaicohort
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Sugarbug
Sugarbug@Sugarbug_AI·
@martinsoorjoo the problem isn't the AI. it's ten tools each doing one thing well but still meaning ten places to check, ten contexts to hold. what if one layer just handled all of that?
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Martin Soorjoo
Martin Soorjoo@martinsoorjoo·
AI isn’t burning your people out. Managing it is. BCG found heavy AI users report “AI brain fry” — cognitive overload from supervising too many tools at once. Errors jump ~40%. Decision fatigue spikes. Top performers start thinking about quitting. AI can remove work. But unmanaged AI multiplies mental load. Leadership question: Are you increasing output — or increasing cognitive strain? This distinction matters more than most CEOs realise. Link to HBR article in first reply below #Leadership #Founder #CEO #AI #Burnout
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Sugarbug
Sugarbug@Sugarbug_AI·
@karankendre It's not the AI doing the work that's exhausting. it's supervising ten different AIs / tools doing ten different things. We need something that can help you pay attention perfectly, 110% of the time
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Karan
Karan@karankendre·
Let me explain this, because I don’t think people realize how insane this is >Researchers surveyed 1,500 workers and found a new phenomenon. They called it AI brain fry >It’s not laziness. It’s cognitive overload from babysitting AI tools while still doing your actual job. >Highest burnout rates? Software developers, IT, finance, and marketing. >Brain fry = 33% worse decision-making and nearly 10% higher chance of quitting. >AI didn’t remove the work. It added a second job on top of it >The people burning out fastest aren’t avoiding AI they’re the ones using it the most.
Pubity@pubity

Scientists have discovered that excessive use of AI tools is causing "brain fry". People are multitasking faster than ever before, but managing so many different tasks at once is causing intense fatigue, brain fog, and burnout.

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Ben Wallace
Ben Wallace@DJbennyBuff·
Request for startup: solve the 1st stage of building I want something that analyzes all feedback channels, both active (@SlackHQ, @meetgranola, support@) and passive (@sentry, logs) to help my team identify trends and business impact Low-hanging/well-scoped topics immediately get triaged to an agent
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Sugarbug
Sugarbug@Sugarbug_AI·
@FreeMrktCptlst tool fatigue is the real tax here. we got sick of it and built Sugarbug, sits behind the tools you already use so you stop drowning in new ones.
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FMC (📈,📈)
FMC (📈,📈)@FreeMrktCptlst·
“Locking in on AI” is a scam being sold to you by big clank Let the sheep get tool fatigue and waste time learning skills that’ll be obsolete in a month You should be lifemaxxing and experiencemaxxing so you can become inspired with an idea worth building! smoke weed everyday
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Sugarbug
Sugarbug@Sugarbug_AI·
@LisaFlorentina8 @PlutonAIHQ the "too many dashboards" problem isn’t just defi. every team running Linear + Slack + Figma + GitHub hits this wall. we’re building the layer that connects them so you stop being the integration layer yourself
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Lisa Florentina
Lisa Florentina@LisaFlorentina8·
➥ DeFAI is coming and @PlutonAIHQ is building the AI Agent economy DeFi promised open finance. But for most users, it’s still complicated. Too many dashboards. Too many protocols. Too many decisions that require constant monitoring. And when things move fast on-chain, mistakes become expensive. Wallet approvals. Hidden risks in smart contracts. Strategies that require manual execution 24/7. Even experienced users struggle to keep up. The deeper issue? Verification. In DeFi, users constantly need to verify information: – Is this contract safe? – Is this yield strategy sustainable? – Is this wallet activity trustworthy? But today, verification still requires time, expertise, and multiple tools. That gap is exactly where a new concept is emerging: DeFAI. The idea is simple: Combine DeFi infrastructure with AI agents that can analyze, verify, and execute actions on behalf of users. Instead of manually navigating complex interfaces, users interact with intelligent systems that help interpret on-chain data and automate strategies. And this is the direction PlutonAI is building toward. PlutonAI is developing a DeFAI ecosystem where AI Agents simplify how users interact with DeFi. These agents can help: • Analyze market conditions • Automate trading and yield strategies • Track wallet activity • Manage portfolio positions Rather than forcing users to learn every protocol, the system focuses on making DeFi more intuitive and accessible. Because the reality is: The AI Agent economy is only beginning to form. As agents become more capable, they won’t just assist users ~ they may become the interface through which people interact with on-chain finance. And the next phase of DeFi could look very different from today. 👀 There may also be some interesting milestones coming soon for PlutonAI. More updates and confirmations are expected as the ecosystem continues to evolve and strengthen its security. If you're curious about the future of DeFAI and AI-powered finance, you can join the early community here: ➾ plutonai.net/waitlist #PlutonAI #DeFAI #AIAgents
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Sugarbug
Sugarbug@Sugarbug_AI·
We were bombarded by a firehose of information we couldn't keep up with. Linear, GitHub, Figma, Slack, Notion, calendars, transcripts. all day, every day. So we asked ourselves: what would our day look like if we could pay perfect attention to everything, everywhere, all at once, 110% of the time? We built Sugarbug to find out. It watches everything we watch, keeps a living memory of every project, speaks up when it matters and ensures we don't have to go hunting for information across 10 different applications. We stopped spending our time on information logistics and started spending it on the most impactful work.
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Sugarbug
Sugarbug@Sugarbug_AI·
Monday morning. 9:30am. You haven't started actual work yet. You've checked Linear for new issues. Scanned GitHub for PR reviews. Opened Figma to see if anyone left comments over the weekend. Skimmed fourteen Slack channels. Glanced at your calendar to see what's coming. None of those tools know about each other. So you'll do the same thing again tomorrow. We're building Sugarbug to handle this. 9+ integrations, one knowledge graph, compounding context. Sign up for early access: sugarbug.ai
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Sugarbug
Sugarbug@Sugarbug_AI·
Your tools don't talk to each other very well. Linear has no idea what's in your Figma comments. Slack doesn't know your calendar is packed. You end up being the integration layer – checking 8+ apps every morning just to figure out what happened the day before, and moving information from tool A to tool B That ritual eats about 25% of your work week.
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Sugarbug
Sugarbug@Sugarbug_AI·
We're opening early access to a small group. If you struggle with increasing tool fragmentation and are tired of being the human glue between your tools → sugarbug.ai
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Sugarbug
Sugarbug@Sugarbug_AI·
What you actually get: meeting briefs ready before you are. Cross-tool context surfaced that you'd never catch on your own. A deep understanding of cross-functional projects & problems. Workflow intelligence used when needed, not another dashboard to check constantly.
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