Business workflow automation
Concrete Zapier workflows for meeting notes, CRM updates, lead response, task routing, content scheduling, reporting, and knowledge capture.
29.6%
Best tweets about Zapier
27 Best Tweets About Zapier (2026)
Browse the best tweets about Zapier, featuring automations, Zaps, integrations, AI workflows, business operations, templates, and productivity results.
Useful Zapier automations, integrations, AI features, workflow design, limitations, reliability, operating outcomes, and product updates.
- Creators
- 23
- Updated
Original Xholic analysis
What 27 top Zapier posts reveal
Zapier discussion is predominantly supportive (66.7%), with practical business automation and AI-agent connectivity as prominent themes. The highest-scoring posts include agent access to connected apps and concrete workflow examples. Cautionary posts raise cost, migration, outage, and vendor-dependency concerns. A recurring viewpoint is to clarify and improve the workflow before deciding whether AI is appropriate.
- Dominant tone
- Positive
- Median score
- 4.53
- Leading format
- Opinion
- Recent posts
- 29.6%
63% of posts
All-time engagement
40.7% of posts
Published in 90 days
Conversation map
The themes creators return to
AI agent connectivity
Using Zapier SDK or MCP to give AI agents and coding environments access to thousands of connected apps and take cross-tool actions.
25.9%
Cost and platform alternatives
Zapier cost, execution-volume optimization, workflow audits, migration friction, and comparisons with n8n or self-hosted alternatives.
22.2%
Platform risk and limitations
Reliability, vendor dependency, integration limitations, outages, subscription risk, and replacing Zapier with custom-built automation.
18.5%
Integration platform landscape
Zapier as the connective layer between existing SaaS tools, including its market positioning and the broader ecosystem of no-code automation competitors.
14.8%
Workflow design
Designing effective workflows by mapping steps, choosing between humans, AI, and deterministic software, and fixing processes before adding AI.
14.8%
AI fluency and accountability
Zapier's AI fluency rubric, including organizational adoption, experimentation, capability building, human judgment, and accountability for outputs.
7.4%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 12
- Median reposts
- 1
- Median replies
- 4
- Median views
- 1.9K
Posts with media make up 44.4% of this collection. Their median all-time score is 16.4, compared with 2.93 for text-only posts.
Format mix
- Opinion 40.7% ยท score 4.82
- Case Study 25.9% ยท score 14.8
- Tutorial 25.9% ยท score 1.76
- Announcement 3.7% ยท score 17.5
Consensus and debate
Where creators agree, and where they do not
Shared view
Automation targets recurring operational work
Concrete examples use Zapier to turn triggers into operational actions, including meeting-note capture, CRM updates, Slack notifications, and rapid lead responses.
Shared view
Agents extend Zapier across app stacks
Posts describe the Zapier SDK or MCP as a way to connect coding agents to thousands of apps and enable actions across connected tools. The cited posts state access to 8,000+ or 9,000 apps.
Shared view
Design and accountability precede AI
Several posts argue for mapping the business problem and workflow before adding AI, selecting among humans, AI, and deterministic software deliberately, and retaining human responsibility for AI-assisted outputs.
Open debate
Custom builds are posed as Zapier alternatives
Individual posts describe building custom automations with Claude Code instead of using Zapier, citing subscriptions or integration constraints. These are personal accounts, not evidence of a general migration trend.
Open debate
Cost and dependency remain central cautions
Posts raise concerns about execution costs, migration effort, outages, and vendor dependency. Suggested mitigations include batching, caching, workflow audits, fallbacks, documentation, andโin some casesโself-hosted alternatives.
What performs
Patterns behind standout posts
Outlier posts span agent and workflow use cases
The five supplied score outliers span agent connectivity, selling to agents, a meeting-notes knowledge workflow, and SDK-assisted workflow review. Their individual supplied all-time scores range from 19.85 to 107.71.
Connectivity and case-study formats have higher median scores
AI agent connectivity has the highest supplied theme median all-time score (19.846). Case studies have a supplied median of 14.791, above opinion (4.821) and tutorial (1.764) formats.
Media posts have a higher supplied median score
Media appeared in 12 of 27 posts (44.4%). The supplied media median all-time score was 16.38, compared with 2.927 for text posts.
Statistical standouts
- View standout post 1 Score 107.7 ยท 23.79ร median
- View standout post 2 Score 92.7 ยท 20.48ร median
- View standout post 3 Score 40.5 ยท 8.96ร median
- View standout post 4 Score 27.2 ยท 6.01ร median
- View standout post 5 Score 19.9 ยท 4.38ร median
Creator landscape
Who shapes this conversation
The five most represented creators account for 33.3% of the selected posts.
-
1. Tiago Forte
@fortelabs
2 posts
-
2. Harsh Makadia
@MakadiaHarsh
2 posts
-
3. Sachin Rekhi
@sachinrekhi
2 posts
-
4. Wade Foster
@wadefoster
2 posts
-
5. Andrew Warner
@AndrewWarner
1 post
-
6. The Boring Marketer
@boringmarketer
1 post
Foster demonstrates SDK use in daily work
Wade Foster shares SDK-led examples from his work: reviewing Gmail, Granola, Slack, and Coda for automation ideas, and ranking content ideas from connected work data.
Forte highlights repeatable business workflows
Tiago Forte highlights automation examples including a sales workflow reported to save 90 minutes per salesperson per day and a meeting workflow spanning recording, transcript analysis, CRM updates, and Slack notifications.
Rekhi connects AI operating models and workflow agents
Sachin Rekhi discusses an AI-fluency rubric covering mindset, strategy, building, and accountability, and presents workflow-automation tools such as Zapier, Relay, and n8n as an agent category for repeatable autonomous workflows.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 27-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Zapier tweets
Top Zapier tweets from 23 creators
Ranked 01โ27
- 01
@coreyhainesco ยท
Marketing Skills v1.7.0 is out. What shipped: ๐ /aso-audit โ audit and optimize App Store and Google Play listings. Keyword analysis, visual asset assessment, competitive benchmarking, and conversion rate optimization for mobile apps. Community contribution from @basseko. ๐ ๏ธ Zapier SDK โ AI agents get direct access to 8,000+ app integrations (Slack, HubSpot, Salesforce, and more) without building a single OAuth flow. Includes install guide, CLI commands, SDK methods, and marketing automation examples. Enhanced skills: โข /community-marketing โ added task-specific questions + related skills sections โข /aso-audit โ cleaned up for cross-agent compatibility โข /social-content โ formatting fixes for platform reference links Now shipping 36 skills and 52 tool integrations. Free, open source. npx skills add coreyhaines31/marketingskills
Watch video
- 02
@boringmarketer ยท
how to use Zapier to easily connect just about any data/tool to Claude Code -create stunning reports - automate social content - skyโs the limit you can access 8000+ apps
Watch video
- 03
@AndrewWarner ยท
If you're not selling to agents, you're missing the biggest, growing market. @wadefoster showed me how Zapier does it in our monthly pod. Including: โข Give agents clean documentation โข Create stripped-down, plain-text versions of your site โข Build clean API & CLI tools โข Run queries constantly to evaluate results (YouTube link below.)
Watch video
- 04
@chrija ยท
In case it's useful for others, here's how we at @PointNineCap are adding @meetgranola notes to our AI knowledge base: 1) Saving a note in a shared folder in Granola fires a workflow in @zapier 2) Zapier creates a Google Doc, containing AI-enhanced notes + user notes + raw transcript The AI knowledge has access to our entire G-Drive, incl. the Granola folder. I'm sure @meetgranola will come up with a better solution soon ... but this works quite well for now.
- 05
@wadefoster ยท
57 hours in meetings last week. Here's how the Zapier SDK kept me sane. Every Monday, I run this prompt in Cursor: "Review my last week in Gmail, Granola, Slack, and Coda. Tell me new automation ideas. Help me be faster, more efficient, or do higher quality work." The @Zapier SDK is what makes it work. Last week it flagged 3 patterns: 1. I keep re-explaining the same strategy across meetings. โWorkflow fix: create a one-pagerโ 2. My follow-up commitments don't have owners or due dates so my AI offered to route them to a queue 3. External meeting follow-ups shouldn't be a to-do list. My AI offered to draft the emails, intros, and CRM notes The Zapier SDK lets your agent suggest and take action across 9,000 apps. Install it in Cursor, Claude Code, Codex, OpenCode, whatever you're already using. The open beta is free: https://t.co/2V2CLOSEpB
Watch video
- 06
@wadefoster ยท
My most-viewed post last week was my AI's idea. Powered by the Zapier SDK. It was waiting for me in a Slack DM. My agent reads through Granola notes, Slack, Gmail, calendar, and Cursor transcripts every Monday to find and rank 10 post ideas. I call it Scout. (I built mine in Cursor, but you could build yours in Claude Code, Codex, OpenCode, etc) Last week it surfaced a few, most notably an internal finding: "80% of applicants for a senior engineering role were fraudulent" My agent flagged it as 1) strong potential content and 2) safe enough to share broadly as a lesson The Zapier SDK is the part that makes it real. I can execute the full power of Zapier, 9,000+ connected apps, with one line of text. Our SDK open beta is free. If you build with agents, try it yourself: https://t.co/Ed9A1lYecq
Watch video
- 07
@sachinrekhi ยท
.@wadefoster's most important contribution to the emerging AI transformation playbook has been open sourcing the AI fluency rubric they use inside of Zapier to hire, onboard, and develop talent. They break AI fluency down into 4 primary components: 1๏ธโฃ Mindset - Continuously learning and experimenting with AI 2๏ธโฃ Strategy - Deciding where AI belongs in the work and why 3๏ธโฃ Building - Partnering with AI to produce quality results through clear communication and iteration 4๏ธโฃ Accountability - Applying human judgment to define success, evaluate outputs, and own the results Their rubric then defines 4 different levels of AI fluency: 1๏ธโฃ Unacceptable - Resistant to AI tools or skeptical of value 2๏ธโฃ Capable - Early user of AI tools 3๏ธโฃ Adoptive - Builds and iterates with AI to augment daily work 4๏ธโฃ Transformative - Leads AI strategy, scales enablement, and rethinks workflows Finally, they break this down for each role, covering the most important AI use cases they expect to see mastered. These now span engineering, product, support, marketing, people, legal, sales, biz ops, corp dev, channels, finance, data, and exec ops. Every organization serious about AI transformation needs to adopt a similar framework and Zapier offers a fantastic starting point.
- 08
@TaylorPearsonMe ยท
I've been trying to get better at "thinking in software" as a non-technical person. My premise is that almost all knowledge work can be visualized like a Zapier or N8N automation. A series of steps where the question is: what's the right tool for each step. AI really changes the calculus for what the right tool in two ways: 1. It can do a lot of things that traditionally required a human (E.g. Write a research report on a topic) 2. It makes it much cheaper to build deterministic software for parts of that workflow. So the tool set is broadly: - Human - AI - Software My default is typically humans (with SOPs where possible) That's the world I grew up in. But now, LLMs and software are eating that pyramid of layers of abstraction from the bottom up. - LLMs can do lots of things that only humans used to be able to do. - LLMs can build software that was historically not really worth building Using LLMs to replace human work is intuitive for me. They feel anthropomorphic enough that it's easy to substitute "delegate this to a person with a SOP" for "delegate this to an agent with a skill file." That substitution has been really productive. But, there's a lot of pieces in that workflow should really be done by deterministic software. It's both cheaper from a compute perspective and deterministic rather than probabilistic. Part of the issue is that most of my work right now is writing and project management, which doesn't lend itself to deterministic software very well. But I keep asking myself: to what extent is that just old habits and a failure to adapt to the new reality? If it's now 100x easier to build software, the ROI calculation has fundamentally changed on whether I should be doing it. My intuition about that is probably less than ideal because it's grounded in a tech paradigm that no longer exists. At the margin, we should all be building more deterministic software. The returns are probably the same as they've always been for many software projects, but the cost is down by an order of magnitude or two. Same return, 10x-100x cheaper investment โ the ROI math is just different now. I'm not a software guy, so it's hard for me to reason about the boundaries here. Curious what other people's approaches or examples look like.
- 09
- 10
@Layton_Gott ยท
A simple way to find better SaaS ideas: Look for โduct tape workflowsโ Meaning people that already are solving the problem with: โข spreadsheets โข Zapier chains โข Notion databases โข manual DMs โข messy SOPs โข 5 tools glued together โข screenshots sent back and forth If someone is already putting together a painful workaround, you do not have to convince them the problem exists. You just have to build a cleaner way to solve it.
- 11
@SimonHoiberg ยท
The "solo founder" label is misleading. You are not really solo. You just replaced employees with vendors. OpenAI, AWS, Stripe, Google, Zapier, etc. Your entire "team" is a stack of external dependencies. This is not always a bad thing. But it's definitely not "independence" either. Most of the "I run a 7-figure business solo" posts skip a few details: โ API policy changes can kill your product overnight. โ Pricing updates can wipe out your margins in a week. โ One outage in a critical tool can block your entire funnel. So what do you actually control? โ Your audience. โ Your offer. โ Your data. โ Your infrastructure. (If you set yourself up correctly!) If you want real leverage in the AI economy: 1๏ธโฃ Own your audience: Move people from YouTube, social media, etc, to your own email lists, communities, channels. 2๏ธโฃ Reduce platform risk: Use BYO key when you can. Prefer tools that are self-hostable. Have at least one fallback for key providers. 3๏ธโฃ Build simple, replaceable systems. The more custom glue you add between tools, the harder it is to switch. Keep your workflows clean and documented so you can migrate when you need to. Just be honest about what you control and what you rent. Solo is not the goal in itself. Control and sovereignty is.
- 12
@FrancescoD_Ales ยท
Google says Workspace Studio has automated 20+ billion tasks in the last 30 days, apparently. It's an AI agent builder inside Google Workspace that lets you create no-code automations across Gmail, Drive, Calendar, Sheets and more. For Business/Enterprise users. It wants to take on Zapier & Make. Powered by Gemini and most people don't know it exists yet, here's how it works:
Watch video
- 13
@fortelabs ยท
Most people assume workflow automation requires a development team or expensive consultants Hayden's team built a system that saves salespeople 90 minutes daily using nothing but Zapier, a screen recorder, and basic AI prompts The first setup took under a week. Now they can replicate it in two hours What makes you hesitate to automate the repetitive parts of your work?
- 14
- 15
@nocodelife ยท
I've been deep in a Claude Code hole for the past few months but recently have been trying out Claude Cowork to see how it compares. Here are 10 of the best Cowork tips I've found: 1/ The "End of Session" prompt. Before you close Cowork, ask it to save key takeaways to a local memory.md file AND write the exact prompt you should use to start your next session. Perfect continuity every time. 2/ Import your ChatGPT memories. Don't start from scratch. Use Claude's "Start import" tool in settings to port your entire memory history over from ChatGPT or Gemini automatically. 3/ The "Successful Examples" folder. Don't just give Claude instructions. Create a subfolder full of your best past work (emails, proposals, ads) so it can reverse-engineer your exact style and see what "success" actually looks like. 4/ Force "Plan Mode." Add "show a plan, wait for approval, then execute" to your Global Instructions. Stops the AI from rushing into assumptions, saves you a massive amount of tokens, and lets you course-correct before it acts. 5/ The Zapier MCP trick. Is Claude missing a native connector for your favourite tool? Use Zapier MCP to build a custom server that connects Cowork to 8,000+ apps like Stripe, HubSpot, or Skool. Takes a few clicks. 6/ Dynamic context routing. Don't hardwire your entire business context into every prompt. That burns through your usage limits fast. Instead, add a Global Instruction telling Claude to "only check the Business Folder if asked a strategic business question." 7/ Apple Watch and iMessage control. Enable the "Read and Send iMessage" extension on a Mac running 24/7, and you can text tasks or send screenshots to your desktop Claude directly from your Apple Watch while you're out for a run ๐ 8/ Master "hard" vs "soft" memory. Claude has two types of memory inside Projects. "Soft memory" runs automatically, sweeping your conversations every 24 hours and pulling out important details for background context. "Hard memory" is when you explicitly tell Claude to save specific workflows, preferences, or rules to a local file like memory.md. Soft memory is useful, but for the stuff you absolutely cannot afford the AI to forget, maintain those hard memory files yourself. 9/ The "Handover Test." Unsure if a workflow should be a Skill or a Plugin? If it requires 3+ steps across 2+ tools and you could hand it off to a human employee, bundle it into a shareable Plugin. 10/ Zero-hallucination maths. Never ask Claude to directly calculate totals from a folder of receipts or invoices. Instead, have it write the actual formulas into an Excel spreadsheet. It handles Excel formulas perfectly, completely eliminating AI maths errors.
- 16
@pipelineclub100 ยท
One difference that AI is making in business is replacing features of larger software that you might use. The net effect will be more churn and lower user counts if you arenโt a core sticky software. Take the example of Zapier. I had it for a few things for my SMB to create webhooks and send notifications to slack. Today I used Claude code and 40 minutes later we are doing custom webhooks for everything. Zapier was limited to the pre-designed end points of the integration. Now we added several new ways to centralize our workflow into slack with notifications.
- 17
@MakadiaHarsh ยท
What most people get wrong about AI in business: They think AI is the solution. It's not. AI is the last step. Step 1 is figuring out which problem actually costs money. Not which problem sounds interesting which one shows up on the P&L. Step 2 is fixing the workflow around that problem. Most broken processes can be fixed with a spreadsheet and a Zapier flow. No AI needed. Step 3 only after steps 1 and 2 is asking: "Would AI make this faster, cheaper, or more accurate?" I've talked 8 clients out of building AI features this year. In 6 of those cases, the solution was simpler than they expected. In 2 cases, AI was the right answer but only because we did steps 1 and 2 first. AI on a broken process is like putting a turbocharger on a car with flat tires. Fix the tires first.
- 18
- 19
@fortelabs ยท
I invited my friend and serial entrepreneur, Hayden Miyamoto, back to my YouTube channel to share the AI workflow his team uses for meetings In this video, he walks through a Zapier automation that records calls, analyzes transcripts with AI prompts, updates CRMs, sends Slack notifications, and tracks everything automatically This eliminates hours of manual notes, follow-ups, and reporting. The system works for sales calls, onboarding, team huddles, or personal learningโand you don't need developer skills to set it up
- 20
@MakadiaHarsh ยท
My playbook for keeping automation costs flat as a client scales from 100 to 10,000+ daily operations: Move 1: Batch where possible. Instead of triggering on every single event, batch process every 15 minutes. One execution with 50 items costs less than 50 individual executions. Move 2: Cache responses. If you're calling the same API with similar inputs repeatedly, cache the result. Same customer lookup doesn't need a fresh API call every time. Move 3: Self-host n8n. At 5,000+ monthly executions, the cost difference vs Zapier is $400-500/month. At 50,000, it's thousands. The math is obvious. Move 4: Kill zombie workflows. Every month I audit which automations actually ran and which are sitting idle. Move 5: Monitor per-workflow cost. Log execution time ร API calls ร data transferred for each workflow. The top 3 most expensive workflows usually account for 80% of the bill. Optimize those first.
- 21
- 22
@sachinrekhi ยท
What's the right AI tool for the job? The answer has gotten far more complicated today with the proliferation of tools. To deal with this, I've developed the following mental model around AI interfaces and their applicability to particular tasks. Chatbots - This is the category that started it all. ChatGPT, Claude, Gemini. Simple question & answers end up being useful for a whole host of exploratory questions. And this remains my daily personal driver. Copilots - Copilots then emerged as a way to use AI to manipulate artifacts. Code was the original artifact with tools like Cursor. But copilots expanded beyond code to documents with AI tooling in Notion, Google Docs, Google Sheets, and more. Whenever I want to manipulate an artifact, I reach for the appropriate copilot. Agents - Agents have emerged as fully autonomous AIs designed to execute workflows all on their own. On one side you have the coding agents like Claude Code and Codex. On the other end you have workflow automation tools like Zapier, Relay, and n8n. Whenever I want to create a fully autonomous workflow that I can repeatedly run, I reach for an agent. So now every time I think about using AI, I ask myself whether I should reach for a chatbot, a copilot, or an agent for the task.
- 23
@nurijanian ยท
Everyone's talking about Zapier's updated AI fluency rubric and the bar going up. The part worth paying attention to is the new fourth component they added: accountability. The original rubric assessed mindset, strategy, and building. V2 adds accountability with this framing: "With AI, you can delegate the work, but not the accountability." For product managers, I'd argue this is the sharpest line in the document. PMs already live at the intersection of work they do and work they're responsible for. AI just extended that surface dramatically, without changing who owns the outcome. Concretely: if you used Claude to generate a competitor analysis, a technical spec, or a go-to-market brief, and something in it was wrong, that's on you. The question Zapier is now asking in hiring is whether your workflow caught the error before it shipped. What accountability actually looks like in practice: before generating anything, write three bullet points describing what a good output would include. If you can't write them, you're not ready to generate yet. After generating, spend 5 minutes specifically on numbers, attributions, and edge case claims. Those are the three highest-risk elements in any AI-produced PM document, and they're the ones most likely to pass a quick read but fail when someone pushes back in a review. I built a `/workflow:review` workflow into PM OS for exactly this reason. It runs 7 lenses on any document before it ships: Engineering, Design, Executive, Legal, UX Research, Devil's Advocate, and Customer Voice. Even with that, you're still the one who decides what to do with the output. The workflow surfaces the risks. What you do about them was never delegable in the first place. Worth reading the full rubric if you're thinking about how your team uses AI, not just yourself. Zapier published V2 on March 31. https://t.co/JsZNJqaxN8 https://t.co/uejAoMPU0u
- 24
@SSage38676 ยท
Most founders confuse awareness with demand. Awareness = people have seen you. Demand = people understand why they need you now. For innovative products, demand doesnโt already exist at scale. You have to create it. Hereโs the step process to create demand: 1. Start with a sharp ICP Know who youโre trying to reach, what they already care about, and what pain is urgent enough to act on. 2. Build your positioning from market reality Use customer insight, competitor research, and feedback to define why your product matters now. 3. Reframe the problem Donโt just describe your feature. Teach people to see the problem differently. 4. Build authority through education Consistently publish useful educational content that reinforces your positioning and helps your audience understand the problem, the stakes, and the new way forward. 5. Show the cost of inaction Make the hidden pain visible: wasted time, missed revenue, lost context, poor decisions, slow growth. 6. Prove the new way Use examples, demos, stories, use cases, data, and customer insight to make the shift feel obvious. 7. Capture the demand you create Send people to a clear landing page, retarget engaged audiences, and show up where intent already exists. 8. Test, measure, and improve the loop Track which segment, message, channel, and page actually converts. Then double down. Example: Zapier Most people already knew Gmail, Dropbox, and Basecamp. Almost no one was looking for an "app automation platform." That's missing demand. Zapier created it by: โ Making the pain of manual work and apps not talking to each other impossible to ignore โ Publishing endless "connect X to Y" content that taught people a new problem โ Showing clear examples of time and context lost from switching between tools โ Positioning themselves as the missing glue between tools people already used They didn't wait for demand. They built it through education and problem reframing. Don't just get seen. Make the market understand why they need you now.
- 25
@evielync ยท
Before Claude Code, building an automation for my business looked like this: โ Log into Zapier. Pay for the plan that actually lets you do things. Spend two hours dragging boxes around a screen. Hit a wall because the integration you need doesn't exist. Give up and do it manually. After Claude Code: Describe the problem in plain English and it just... builds it. I have so many automations I have always dreamed of built this way: โณ Checking payment issues from my membership every Monday โณ Running morning briefs that pull from my calendar, emails, and task list โณ Writing & scheduling social media posts just by having a conversation โณ Even building live business dashboards Claude Code is like having my own private Zapier, except all I have to do is say what I want and it just goes and works it out.
- 26
@BrettErik ยท
tight feedback loops win as an operator, one of the best things you can give yourself is tight communication loops, there are a few ways to hardwire this into your workflow: 1- @clickup (personal favorite) task management seems simple enough until you begin rolling out and testing new angles, new workflows, or have any tailoring in your client-based services can't recommend clickup enough for this, or some form of fast, visible task management. i've been hammering my team and myself on this point: when in doubt assign it and give it a deadline due dates help you build the muscle of prioritization, which is in my opinion, the top skill of leaders in 2026 (not a paid promo, just my favorite tool, clickup let me know if you want it to be a paid promo tho i'm game we love it) 2- calendar event reminders sounds too simple/trite but with so many tasks that occur on a cadence, having clickup--> early calendar event on team members calendar is clutch 3- bird's eye view on all calendars call me what you will but i like having a complete view of all team member calendars so i know who's where and when, it's messy to look at for the first bit but once you're used to it it becomes priceless for timing and assigning (specific to lean teams) 4- simple task assignment zaps my personal favorite is the emoji-->clickup task simple zapier flow that goes -specific emoji response to slack message -pull slack message -uses logic to name the task -automatically adds it to a specific channel different emojis go to different channels, when in doubt it gets assigned (if anyone is using agents to do the assignment well i'd love to see it, seems like a clear use-case but easy to mess up at scale) 5- @viktor__com (again not paid but lmk because this one is fantastic) scheduled reporting using viktor has been a massive time-saver for our team, one caveat here is that you'll want to make sure you get your api connections setup right (and choose the right tools) otherwise you won't get trustworthy data for scheduled tasks +1 if you have a clean spot where all data is housed so viktor can really help you glean information 6- automate the triggers again with the zapier flows, but having a clear sense of what's happening at any point allows you to do the hard work of prioritizing tasks appropriately, make it easy on yourself. If you're in the operator seat you need to be maximizing your visibility into the key events (this does not mean ALL events, it means the ones that must happen or things break)
- 27
@JulianGoldieSEO ยท
๐ฅ๐๐ป ๐ข๐ฝ๐ฒ๐ป๐๐น๐ฎ๐ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐ ๐ณ๐ผ๐ฟ ๐ณ๐ฟ๐ฒ๐ฒ ๐ณ๐ผ๐ฟ๐ฒ๐๐ฒ๐ฟ ๐ฏ๐ ๐๐๐ฎ๐ฝ๐ฝ๐ถ๐ป๐ด ๐๐ต๐ฎ๐๐๐ฃ๐ง ๐ณ๐ผ๐ฟ ๐ฎ ๐น๐ผ๐ฐ๐ฎ๐น ๐บ๐ผ๐ฑ๐ฒ๐น ๐ผ๐ป ๐๐ผ๐๐ฟ ๐ผ๐๐ป ๐ฐ๐ผ๐บ๐ฝ๐๐๐ฒ๐ฟ. No API bills. No token costs. No limits on how many tasks you run. Here's the full setup in under 30 minutes: โ Go to https://t.co/493GbXWz04. Download it. Takes 2 minutes. โ Open terminal. Type: run qwen3.5. Model downloads automatically. โ Install OpenClaw. Select Ollama as your model provider. โ Enter port 11434. Select local mode. Pick Qwen 3.5. โ Connect to Zapier MCP and link 8,000+ apps. Gmail, Slack, Notion, anything. โ Your agents now run for free every single time. I ran an agent 10 times in a row researching AI tools, writing reports, and sending them out. Total cost: zero. When there's no cost per run everything changes. You stop being careful and start being aggressive with automation. You test 10 prompts instead of one. You let agents run overnight. You build workflows you'd never build if you were paying per token. That mental shift alone is worth more than any feature in any AI tool.
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