A founder demonstrates building a fully automated AI research workflow using Gumloop and prompts, outperforming expensive paid tools. This shows how solo builders can rapidly automate complex research tasks without code or developers.
1/
I launched Intelligence & Power yesterday.
Day 1: I built a fully automated AI research pipeline in 90 mins.
β’ No code.
β’ No developer.
β’ Just Gumloop + 3 prompts.
The output? Better than tools Iβve paid $500/mo for.
Hereβs the breakdown:
This setup details how to run a multi-model AI agent pipeline locally with persistent memory for just $15-35/month, enabling builders to automate complex workflows affordably. It's a practical blueprint for deploying powerful AI automations without high cloud costs.
The setup: OpenClaw as the agent framework, ClawRouter for model routing (Gemini Flash for simple tasks, Claude Sonnet for complex ones),
OpenViking for persistent memory.
All running locally on a $600 Mac Mini. Monthly API cost after optimization: $15-35.
This tweet describes an AI CEO that automates key business functions using specialized agents (code, design, monetization, marketing, etc.), offering a blueprint for fully automated business operations. Builders can leverage this concept to streamline or even fully automate their own ventures.
2/ So we built an AI CEO.
Every day it runs specialized agents across every channel that matters when building a business:
- Code agent
- Design agent
- Monetization agent
- Launch agent
- Translation agent
- Email marketing agent
- SEO agent
- more
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AI agentsautomationbusiness opspassive incomeSaaS
build a SaaS on top of itoffer it as a servicerecurring
A founder replaced a costly vendor contract with a custom AI workflow using Claude API and Make, achieving similar results at a fraction of the cost. This highlights a replicable approach for automating business processes and slashing expenses.
I replaced a Β£55,000/year vendor contract with an internal AI system I built in under a week.
Same ticket routing, auto-replies, and QA scoring - but no lock-in and ~90% cheaper.
The vendor called it βAI-powered automation.β
So I built it myself with Claude API + Make +
PokeeClaw is a robust AI agent platform featuring RL-powered tool selection and secure sandboxing, enabling builders to automate complex workflows across 1,000+ integrations. This can help entrepreneurs streamline operations or deliver automated services at scale.
PokeeClaw is a different beast.
Enterprise-grade AI agent platform. 1,000+ integrations. RL-powered tool selection. Secure sandbox.
I test AI agents constantly for this newsletter. Most are demos. This one just⦠did the work.
OpenClaw can automate the entire SDR processβfrom researching prospects to qualifying and handing off leadsβenabling one person (or bot) to do the work of 20. Builders can leverage this to create scalable, automated lead generation services or products.
My #1 use case for OpenClaw now is having one SDR do the work of 20.
- Take ICP
- Research prospect
- Turn into lead
- Contact lead
- Qualify lead
- Hand to AE
This tweet shares a detailed AI and Python workflow that enables a solo builder to operate at the scale of a full team, automating tasks and boosting productivity. It's highly relevant for entrepreneurs seeking to streamline operations and scale without hiring.
My manager thought I had a team.
I was alone.
Here's the exact AI + Python workflow that
made me look like 5 developers
(Save before your team finds it )
This tweet outlines an end-to-end automated workflow using n8n and AI to qualify leads, send cold emails, follow up, and book meetings with zero manual effort. Builders can leverage this to streamline client acquisition or offer it as a service.
The n8n workflow nobody is building:
Lead comes in.
AI qualifies them.
Cold email sends automatically.
Follow-up sequence kicks in.
Meeting books on calendar.
Zero manual intervention after the initial setup.
A ready-to-use workflow combining Tally, Make/n8n, Claude, Airtable, and Gmail to automate lead qualification and follow-up, helping solo founders capture and convert more leads with minimal setup and cost.
Setup time: ~2 hours
Monthly cost: ~$15
Leads you stop losing: all of them.
Tools:
Tally.so +
Make.com or n8n + Claude(or nay LLM) + Airtable + Gmail
DM me "qualify" β I'll send you the Make/n8n template.
#AIAutomation #SoloFounder
This tweet outlines a simple, actionable process for automating a repetitive weekly task using AI, enabling entrepreneurs to reclaim time and boost efficiency. It's a practical framework for building automation pipelines that can underpin scalable, passive income businesses.
Start this weekend:
Pick ONE task you repeat weekly
Write down every step
Give AI your rules + 3-5 examples
Iterate 10+ rounds
By Sunday, you'll have one workflow running at 80% quality with 5% of your time.
That's not a hack. That's a system.
The tweet highlights the inefficiency of using ChatGPT as a simple search tool and urges builders to create multi-step AI workflows that automate complex tasks. This mindset shift enables entrepreneurs to leverage AI for scalable, hands-off business processes.
1. The Tab Trap
Situation: You keep ChatGPT open in a tab and paste one question at a time like it's Google. You use the most powerful tool in history as a search engine.
System: Build actual workflows. Chain prompts, connect tools, let AI do 5 steps while you do 1.
Why it
A fully local AI agent setup that automates coding and tasks, accessible via Telegram, with zero data leaving your device. Builders can leverage this to automate workflows or offer privacy-focused AI services.
COMBO MENARIK = GEMMA 4 + OLLAMA + OPENCLAW (FULL LOCAL)
So this setup creates a personal AI agent that:
runs on your laptop (local)
can code, automate, etc.
can be accessed via Telegram
100% FREE, NO API, 0 data leaves
STEP 1
Download & Install:
A builder fine-tuned an open-source AI model to autonomously handle research, automation, and tool calls with high accuracy, running 24/7 on a Macbook. This showcases a practical, low-cost automation pipeline that can be adapted for various business tasks.
I'm doing that already.
> took OS model
> fine tuned it on (80M dataset)
> now running 24/7 on my macbook
> with 98% accurate tool calls
> it design its own workflows
> can talk, research, automate, save
> and much more
Launching soon.
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AI agentautomationworkflowopen sourcetooling
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A free 350M model enables running full AI agents locally to automate workflows and call APIs. Builders can leverage this to create custom automation solutions or integrate into existing processes.
This tool feels illegal to be free.
A 350M model runs full AI agents.
Calls APIs.
Automates workflows.
And it runs LOCAL
Link in the comments
This tweet outlines a manager loop for reviewing, scoring, routing, and retraining AI outputs, enabling builders to automate quality control and continuous improvement in AI-driven products or services.
Then build the manager loop:
- review samples
- score outcomes
- route edge cases
- retrain prompts and policies
This tweet outlines a workflow where AI ingests raw sources, summarizes them, and updates multiple knowledge pages instantly. Builders can leverage this to automate research, content curation, or knowledge base updates, saving time and scaling operations.
THE WORKFLOW
Exactly how it works:
β Dump sources into raw/
β Tell AI to βingestβ
β It reads + summarizes
β Creates concept pages + links
β Updates index + existing knowledge
One file can update 10β15 pages instantly.
Amadeus introduces agents that live inside DeFi platform UIs, automating user interactions in real time. Builders can leverage this to create seamless, automated DeFi experiences, reducing friction and enabling new passive income models.
DeFi has incredible infrastructure, but the user experience still slows adoption.
With Amadeus, agents live directly inside a platformβs UI, helping users interact with DeFi in real time, without leaving the product.
A shift from tools you operate β to agents that operate for
Demo of an AI-powered workspace that automates sourcing, risk spotting, and supplier management for product launches. Builders can leverage this to streamline operations or offer automated sourcing solutions.
In this demo, watch an Agentic AI-powered DesignβtoβSource workspace turn from βwhere are we on this?β into βdone.β Spot risks early, line up suppliers, and keep a product launch moving fast.
A builder shares their workflow for managing many AI agents in parallel using a custom UI and 160+ custom commands, showcasing a scalable approach to automating complex tasks. This highlights how entrepreneurs can orchestrate agent-based automation for business efficiency.
I run many tasks in parallel so there's not much downtime. I built a UI where each AI agent appears as an avatar on a 2D map (Arcane Agents). I spend most of the day hopping between them assigning and reviewing work.
I've set up ~160 custom commands the agents can call to access
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The tweet introduces a workflow where a second AI agent audits the code generated by a first, addressing trust and reliability issues in AI code review. Builders can adapt this oversight pattern to automate and improve quality in their own AI-powered products.
Happy Easter! I hid an Easter egg in my latest article. First person to find it wins a GitHub Mona plush
AI agents shouldnβt be trusted to review their own code. So I built a second agent that watches the first.
mainbranch.dev/articles/adver
β¦
A builder used NansenCLI to create an end-to-end encrypted Smart Money bot that delivers insights directly to DMs. This shows how to automate delivery of high-value financial signals securely, which can be productized or offered as a service.
5/
@Voidly_ai
used #NansenCLI to build an E2E encrypted Smart Money bot directly to DMs
Kaebox AI streamlines shipping by auto-filling customs and carrier forms from a single entry and printing labels at pickup, reducing errors and saving hours. Builders can leverage this to automate e-commerce logistics or offer streamlined shipping services.
We built Kaebox AI to auto-fill customs and carrier forms from one entry and print labels at pickup. Save hours and cut errors by up to 70%! Try smoother shipping and real-time tracking today:
wix.to/ugivPeG #shipping
This tweet shares a recipe for assembling an AI agent pipeline using Nanochat, Percepta transformer VM, and cloud compute from Replit and Modal. Builders can use this stack to automate complex workflows or power AI-driven products.
Haha!
My recipe:
1x nanochat
1x Percepta transformer VM
github.com/Percepta-Core/
β¦
$3000 of
@Replit
agent
$3000 of
@modal
GPU
Highlights key agent frameworks (LangChain, AutoGen, CrewAI) that enable building AI systems capable of reasoning, decision-making, and task automationβcrucial for entrepreneurs automating business processes or creating scalable passive income streams.
3. Learn Agent Architectures & Frameworks
This is where βAIβ becomes βsystems.β
Focus:
LangChain (ecosystem thinking)
AutoGen (multi-agent workflows)
CrewAI (task delegation logic)
Goal: Understand how agents reason, decide, and act.
This tweet shares actionable strategies to reduce costs and optimize workflows when using AI agents, such as economy modes and planning steps. Builders can immediately apply these to streamline automation pipelines and improve profit margins.
Hey Sethman, you can try the following to help manage Agent costs:
β Economy Mode (~1/3 the cost per task)
β Code Optimizations (reduces rework loops)
β Fast Mode for simple tasks like UI changes
Also try Plan mode first for smaller tasks so Agent maps things out before
The tweet describes using Surf Studio to set up an automated airdrop radar that alerts users to new crypto/NFT projects before launch. Builders can leverage this workflow to spot and act on early opportunities, potentially monetizing through content or services.
Let me share something I've been tinkering with lately.
The
@noise_xyz
project I shared this morning was actually one I spotted through the airdrop radar monitoring I set up using Surf Studioβit pushed it to me about 18 hours before launch.
These past couple of days, I've
Integration of SurfAI's crypto intelligence signals with ODEI's memory and workflow features enables automated, context-aware crypto monitoring and action pipelines. Builders can leverage this stack to create hands-off, value-added crypto tools or services.
Weβve done a preliminary review of the
@SurfAI
architecture.
Yes, we can integrate it into
app.odei.ai.
Thereβs real potential here for our users: Surf as the crypto intelligence signal layer, with ODEI adding memory, personal context, and action workflows on top.
This tweet breaks down which AI tools excel at specific tasks, helping builders avoid the common pitfall of using one tool for everything. Matching tools to workflow patterns enables more efficient, scalable automation for passive income projects.
When to use which AI tool:
Structured data + triggers β Make/Zapier
Visual workflows β n8n
Reasoning + context β Claude
Code generation β Cursor/Windsurf
High-volume + low latency β Direct API
The mistake: Using one tool for everything.
Match the pattern, not the hype.
Ascii.dev automates the spawning and management of multiple AI agents to produce concrete deliverables like reports, PRs, builds, and videos. Builders can leverage this to automate complex workflows and scale output with minimal manual intervention.
legit
Ascii.dev is leaning towards that
- spawns and manages many agents for you
- pushes your agents to implement or produce a great plan through
- pushes agents to produce deliverables such as reports, PRs, hosted builds and videos
- bubbles up important bits to
Replit Agent now supports a native X connector, enabling users to quickly set up integrations through guided steps. This streamlines building automated workflows, saving time for entrepreneurs looking to connect services or automate tasks.
We have a native X connector. Just tell
@Replit
Agent what you want to build and it will set up the integration for you, guiding you through a few quick steps.
RepLoom is an AI agent that automates prospecting, qualifying, and following up on B2B leads, freeing sales teams to focus on closing deals. Builders can leverage this to streamline lead generation or offer automated sales services.
Inside sales reps shouldn't be data entry clerks. RepLoom is an AI agent that prospects, qualifies, and follows up on B2B leads while your team focuses on closing.
A ChatGPT-powered system that converts unclear goals into actionable plans, enabling entrepreneurs to automate client onboarding, productivity coaching, or workflow setup services. This can be leveraged to streamline business processes or offered as a value-added service.
This ChatGPT system turns vague goals into something you can actually follow through on
bit.ly/3QpOMHR
MyClaw offers a no-code, serverless way to automate daily tasks using AI, making it easy for builders to create personalized automation workflows without technical setup. This can streamline operations or be packaged as a service for clients.
OpenClaw got powerful.
MyClaw made it effortless.
No server. No terminal. No weekend debugging.
Pick your skills β fill preferences β your AI runs your day.
Visit Now:
β
MyClaw offers effortless, one-click AI automation, enabling builders to create workflows or products that actually execute tasks without setup. This can streamline business operations or be integrated into new services.
OpenClaw got insanely powerful.
MyClaw made it effortless.
One click. No setup. Your AI actually does things now.
Learn more about MyClaw and try it right here
A hands-on checklist of new AI tools and workflowsβHermes agent, Claude Dispatch, Google AI Studio, Perplexity modes, and NotebookLMβshowcasing how to automate research, content, and data tasks. Builders can immediately test and integrate these for streamlined, revenue-generating automation.
Weekend AI to-do list:
β’ Experiment with Hermes agent
β’ Connect Claude Dispatch
β’ Test new Google AI Studio
β’ Read Anthropic's new Claude Cookbooks
β’ Set up first NotebookLM
β’ Financial research with Perplexity Computer/Finance mode
β’ Connect health data to Perplexity
β’
The tweet shares a workflow using multiple LLMs to analyze project security, highlighting that each model finds unique vulnerabilities. Builders can adopt or offer this workflow to automate and improve security reviews for clients or their own products.
I'm no longer leaving the security analysis of my last few projects to a single LLM.
Here's my workflow:
First, I have GLM, Kimi, Minimax, Gemini, Claude, and Codex analyze the API, auth, and other critical areas separately.
Each model catches different vulnerabilities and
Gemini can execute specific app features directly, letting users interact without opening the app. This opens up new automation and integration opportunities for builders to streamline user workflows and create seamless experiences.
Good read on how Gemini can execute specific features of your app without requiring the user to open the app. Also, the integration looks quite easy.
This update shows how AI models can automate code validation by checking if implementations match design docs, highlighting strengths and weaknesses of GPT, Claude, and Gemini. Builders can use similar pipelines to automate QA, reducing manual work and speeding up product development.
Overnight update 5. I added a checking phase that just verifies whether the code is matching the design docs.
- GPT wrote tests for the design docs themselves all night, assert if words were present
- Claude passed 89/91 tests, but cheated core reqs
- Gemini hit API rate limits
A builder shares how they automated event discovery by scanning thousands of social posts with AI, and reduced costs by moving away from expensive hosted models. This highlights a workflow for automating data collection and processing at scale.
Entirely depends on what you are doing. I built a site that uses AI to autonomously find events going on. It has to scan thousands of social media posts. This was getting expensive using even the βliteβ versions of hosted frontier models. Iβve managed to move it entirely now to a
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The tweet highlights a shift from generic AI copy-paste to building specialized AI teams, each tool handling a unique task. This approach enables entrepreneurs to automate complex workflows for scalable, passive income businesses.
STOP copy-pasting from ChatGPT or Claude
The smartest entrepreneurs are already building AI teams, where each tool is responsible for one task and does it exceptionally well.
Here's the stack:
abi-core-ai 1.9.22 introduces agent-based digital foremen for real-time monitoring of construction schedules, RFIs, and resources, reducing delays and manual oversight. Builders can leverage this to automate project management for clients or integrate into existing workflows.
AI hits the jobsite: abi-core-ai 1.9.22 lets you spin up agent-based βdigital foremenβ to watch schedules, RFIs, and resources in real time, cutting delays and rework while your team focuses on high-value tasks.
TRAE SOLO is a newly launched AI agent that can actively operate within your files, projects, and workflows, not just answer questions. Builders can leverage it to automate repetitive tasks or streamline client work, saving time and increasing efficiency.
TRAE just launched SOLO.
Itβs an AI agent that doesnβt just answer,
It actually works inside your files, projects, and workflows!
I tested it with 2 real tasks in 15 minutes. Here's what stood out
This AI-powered agent streamlines lead triage by extracting, scoring, and following up with prospects from Slack messages, reducing manual sales work. Builders can leverage or offer this workflow to automate client acquisition for themselves or others.
Built an AI-powered lead triage agent that ingests Slack messages, extracts prospect details, scores lead quality, and automates follow-up actions.
Highlights a Python + GPT-4 agent with a memory layer that improves through user interactions. Builders can leverage this iterative learning approach to create smarter, more autonomous AI products that reduce manual oversight.
Built with Python + OpenAI GPT-4. Key is the memory layerβevery interaction teaches the agent. Not magic, just iteration at scale. β MACP CEO (AI agent)
Workflow Machine is a new tool for automating tasks for you and your AI agents, making it easier for builders to streamline operations and reduce manual work. This can help entrepreneurs scale their projects with less effort.
Workflow Machine (
@b0ssy2
) just launched on ShipYard HQ!
Simplify automation for you and your AI agents
shipyardhq.dev/products/workf
β¦
#ShipyardHQ #ProductLaunch #IndieSaaS
SelfClaw.ai has overhauled its AI agents to improve how they think, remember, trade, and communicate. Builders can leverage these advanced agents to automate complex workflows or business processes.
1/
SelfClaw.ai has been shipping quietly.
Time for a proper update.
We rebuilt how AI agents think, remember, trade, and talk to each other. Here's the thread
EvoAgentX uses algorithms to automatically generate and optimize agent workflows based on plain-language goals. Builders can leverage this to rapidly prototype, automate, and improve AI-driven business processes with minimal manual setup.
Evolution
Prompt writing, tool setup, workflow topology β all of it has room to improve. The systematic way to do it: let algorithms search for better Agent configs.
That's exactly what EvoAgentX does. Give it a goal in plain language. It auto-generates multiple Agent workflows,
This tweet introduces three methods for building automated workflows on Action Model AI, including an AI builder that generates workflows automatically. Builders can leverage this to streamline business processes or offer workflow automation services.
Hello Everyone,
I know there's someone somewhere who doesn't know how to build a workflow on
@ActionModelAI
, but not to panic. That's why we're here, to educate you.
There are 3 ways to build a workflow on Action Model AI:
β The AI builder generates one for you automatically
n8n is a free, open-source tool for automating workflows across apps, APIs, and AI models without coding. Builders can use it to streamline business processes or create automated services for clients.
n8n is a free, open-source workflow automation tool (like Zapier, but you can self-host it). It connects apps, APIs, AI models, and services to automate tasksβno coding needed.
The video is a 60-min tutorial showing how to build real workflows (e.g., AI agents, SEO tools,
A CLI tool that lets you spin up multiple AI agents across different repos, each running isolated, self-healing workflows. This enables builders to automate complex dev or ops tasks at scale, reducing manual intervention and increasing reliability.
This is basically what our agent orchestrator cli unlocked for us. We can spin up N number of agents across N repos following durable self healing workflows that make sure thngs are tight. Everything isolated in gitworktrees till its tested and route to the best model for the
NoimosAI offers an autonomous AI marketing team that can detect product or service mentions on social media and enable rapid responses, streamlining customer engagement for builders aiming to automate outreach and support.
Autonomous AI Marketing Team NoimosAIβgive it a try! As just one example of how to use it, it can detect mentions of your product or service on social media and enable quick responses!
noimosai.com/ja
This tutorial explains how to prevent AI agents from degrading in performance due to overloaded context windows, a key issue for anyone automating workflows or building AI-driven businesses. Understanding and managing context as a finite resource helps maintain reliable automation and reduces errors.
The more you use an AI agent, the more "junk" fills up its context window, leading to hallucination and ignored instructions.
This AI automation tutorial (on YouTube) explains how to maintain peak performance by treating context as a finite resource.
It covers everything from
This tweet outlines a step-by-step workflow for leveraging AI to automate and enhance content creation, making the process more efficient and professional. Builders can use this framework to streamline their own content pipelines or teach it to clients.
Most people ask AI for the final answer too early.
Wrong move.
The better workflow is:
Step 1: extract
Step 2: simplify
Step 3: improve
Step 4: format
Step 5: publish
Thatβs how pros use it.
This tweet shares a practical approach to automating business workflows with AI by starting small and iteratively building automation for repetitive, multi-platform tasks. It's valuable for builders seeking to streamline operations and free up time for higher-leverage activities.
I've automated so much of my business with AI over the last 2 months. But I didn't start by automating everything.
Here's the pattern I used:
1// Pick one annoying workflow that's regular and touches multiple platforms
2// Build it in assisted mode β you direct each step, AI
The tweet highlights how Blackbox AI reduces the complexity of setting up multi-agent workflows, making advanced automation more accessible for builders. This can help entrepreneurs streamline operations and unlock new passive income opportunities.
Multi-agent workflows are powerful, but the setup is the real bottleneck, tools like Blackbox AI already solved a big part of that.
Qwen3.6-Plus demonstrates superior tool-use optimization and agentic planning compared to GPT-4, making it a strong candidate for automating complex, multi-step business workflows. Builders can leverage this for more efficient client automation or agent-based services.
Qwen3.6-Plus's agentic capabilities are legit - the planning layer uses reflection patterns similar to what I've built with Claude MCP.
Key difference is their tool-use optimization beats GPT-4 on multi-step workflows.
Been testing it against my Claude agents for client
A custom AI workflow pulled daily medical data from hospital systems to improve patient care and catch errors. This highlights a blueprint for automating healthcare data monitoring, which builders could adapt for other high-stakes, data-rich environments.
A son built a βvibe-codedβ AI workflow to help his mother navigate stage 4 cancer and catch critical medical errors. Sadly, she passed away, but what he built with AI changed how she was cared for in her final days.
- Pulls daily medical data from the hospitalβs Epic system to
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This tweet shares actionable design patterns for building robust, production-ready coding agents, highlighting trade-offs and practical implementation tips. Builders can use these insights to automate coding workflows or enhance agent-driven products.
If you missed, check out my latest post
β12 patterns behind production coding agentsβ
1. Persistent instructions: durable rules repo. Helps consistency. Trade-off: goes stale.
2. Scoped context: load rules by directory. Helps local accuracy. Trade-off: harder to debug.
This tweet shares a refined workflow for structuring AI prompts using a spec, foundation, and especially a context file step, which improves output quality. Builders can use this to create more reliable AI automations or offer prompt engineering as a service.
This workflow is exactly what I've been refining with clients since early Cursor days.
The spec β foundation β context pattern is gold, especially the context file step - most people skip it and wonder why their prompts produce garbage.
The Lovable/Bolt decision tree is crucial
This workflow automates the process of ingesting content, extracting concepts, and generating a queryable markdown wiki. Builders can leverage this to streamline knowledge management or power AI-driven content products.
The current workflow is simple:
β’ingest URLs or local files
β’extract concepts
β’generate linked markdown pages
β’resolve wikilinks
β’query the compiled wiki
β’optionally save answers back into the wiki
AWS has introduced two new Frontier Agents that autonomously learn and improve over time, enabling builders to automate complex workflows and reduce manual intervention. This opens up opportunities to create scalable, hands-off systems for passive income or service automation.
AWS just launched two Frontier Agents. They learn and improve over time, never tire, and run autonomously. Read more in The AI Economy:
go.aws/3POnzyx
This highlights a method to connect local AI coding agents with popular messaging platforms, enabling chat-based coding workflows. Builders can leverage this integration to automate coding tasks or offer AI-powered coding assistants via chat, streamlining client or team interactions.
Add this to your toolkit: Bridge local AI coding agents (Claude Code, Cursor, Gemini CLI, Codex) to messaging platforms (Feishu/Lark, DingTalk, Slack, Telegram, Discord, LINE, WeChat Work). Chat with...
This tool automates personalized direct message outreach at scale, saving time and boosting results. Builders can leverage it to streamline lead generation or client acquisition workflows.
GM! Building DMpro AI driven DM automation for personalized outreach at scale.
Saves time, drives results:
A team uses an internal AI agent to automatically track activity across Slack, Discord, and Clockify, generating daily status reports without manual input. Builders can replicate or productize this workflow to save time for teams.
No one on my team writes daily updates anymore
We have an internal AI agent that tracks everything across Slack, Discord, and Clockify, and generates the status report at the end of the day
Highlights a tool ('49agents') that centralizes the management and monitoring of multiple AI agents, solving the pain point of tracking agent progress across different terminals. This is valuable for builders automating complex workflows or orchestrating agent-based systems.
this is essentially what i built with 49agents - a canvas that acts as theθ°εΊ¦δΈεΏ for multiple agents. claude code is great at polling for task completion but watching multiple agents across different terminals is where it falls apart. having one surface where you can see which
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build a SaaS on top of itoffer it as a servicerecurring
Cobl lets users generate fully formatted proposals using five AI agents in a single conversation, automating a tedious business process. Builders can leverage this tool to streamline client work or offer proposal generation as a service.
One conversation. Five AI agents. Fully formatted output.
Free plan lets you generate 3 proposals/month.
Try Cobl:
cobl.ai/?utm_source=tw
β¦
MyClaw's new 'Essential Skills' lets users quickly deploy AI agents for tasks like inbox management or stock tracking. Builders can leverage this to automate workflows or offer tailored agent setups as a service.
MyClaw just launched βEssential Skills.β
Hereβs the flow:
- Browse Skill Hub
- Pick a skill (inbox, daily brief, stocks, etc.)
- Fill your preferences
- Click install
Thatβs it.
You now have a working AI agent!
A platform that combines multiple AI tools to help freelancers and entrepreneurs deliver higher-quality work faster, reducing manual effort and increasing client satisfaction. Useful for automating service delivery or scaling freelance operations.
Impress every client with faster, smarter, and high-quality results powered by multiple AI tools in one place. Work less, deliver more, and stand out instantly.
Start working like a pro today!
launch.ai-pro.org/sparkdeal
#AIPro #FreelancerTools #WinClients #AIForWork
A simple AI workflow: record yourself describing your project, transcribe it, and have AI identify reasoning gaps. This can streamline product validation and save time for entrepreneurs.
Three AI workflows that sound too simple but saved me weeks this month.
- The logic check
I describe what I'm building out loud. Voice memo.
Paste the transcript and ask: where does my reasoning have gaps?
Not 'is this a good idea.' Where is the logic weak.
That
Showcases a no-code workflow for classifying and prioritizing emails using Google Workspace Studio, enabling automated inbox management. Builders can adapt this to streamline client communications or offer as a productivity service.
Aryan Irani built an AI email organizer in Google Workspace Studio that classifies every incoming message, applies labels, and only sends a Google Chat notification when something is genuinely urgent. No code required β just an Extract step, a Decide step, and a rubric you write
A builder shares how quickly a personal AI assistant's memory can be corrupted by low-quality models, highlighting risks in deploying autonomous AI agents. This is crucial for entrepreneurs considering AI-powered automation, as it exposes reliability and trust issues that must be solved for scalable, hands-off income streams.
I built a personal AI assistant on a Mac Mini. Within 48 hours, cheap models had poisoned its memory with fabricated colleagues, fictional file shares, and an imaginary costume party. Here is what I learned.
This demo showcases practical AI workflows and a live agent using real data, highlighting how operational AI can drive impact, security, and adoption. Builders can learn how to implement similar automation pipelines for clients or their own ventures.
AI wins arenβt about how many models you enable. Theyβre about impact, security and adoption. This
@CDWCorp
demo dives into real workflows and a live agent using live data. Curious what βoperational AIβ really looks like? Learn more & register at the link:
dy.si/MFPPau
A workflow using Claude to automate Google Analytics 4 data analysis, reducing manual effort for entrepreneurs tracking web performance. Builders can leverage this to streamline reporting or offer analytics automation as a service.
Check out the latest article in my newsletter: This Claude Workflow Simplifies GA4 Data Analysis.
linkedin.com/pulse/claude-w
β¦ via
@LinkedIn
A personal cognitive operating system using Poke, Notion, and Claude automates content creation, milestone tracking, and long-term planning. Builders can adapt this workflow to streamline their own projects or offer similar automation solutions.
i built a cognitive operating system so i can focus on being a father.
this setup (poke + notion + claude) is the engine behind everything:
- producing the post-labor parenting newsletter
- building a milestone tracker for lucian
- architecting the thesis for 2044
itβs a shift
meethenry.ai offers early access to a new platform for AI agents, enabling builders to automate workflows or services. This could be leveraged to create automated solutions or services for clients or internal use.
Be one of the first to try the new frontier of AI agents:
meethenry.ai
This tweet shares actionable advice on configuring AI agent modes (Economy and Lite) to reduce costs and tailor automation for specific tasks. Builders can use these settings to streamline workflows and maximize profit margins in AI-powered businesses.
Hi Stacy, thanks for reaching out again!
Can you try adjusting your Agent Mode settings to tailor your prompts for your use case? We recommend Economy Mode to optimize on Agent costs to reduce that spend, and Lite Mode if you're trying to change simple tasks.
In addition, you
A builder created an automated tool to monitor when online services update with their vaccination status. This highlights a practical automation workflow that can be adapted for tracking other types of online data changes.
How it started
How it's going
(yes I built an automated tracker to detect when online services update with my vax status)
π 6,787 viewsβ€ 42π 2π¬ 3π 00.7% eng
automationtrackingdata monitoringworkflowbuilders
build a SaaS on top of itoffer it as a servicerecurring
Replit Agent now offers an 'AI SDR' skill, enabling users to automate sales development tasks directly from the platform. Builders can leverage this to streamline outreach or integrate it into client workflows.
To use the AI SDR skills, simply ask Replit Agent, or use the + button from the input box after logging in and the select the "AI SDR" skill
Shows how to use n8n and AI agents to automate repetitive info-checking tasks, freeing up time and demonstrating a workflow that can be productized or offered as a service.
I was wasting time every morning checking dollar rates manually.
So I built an AI agent on n8n that sends the rate automatically to my Telegram at 8am.
Your time is worth protecting. Let a system handle the repetitive work.
@NexithAIAcademy
#aiautomation #workflowautomation
A hands-on experiment with Openclaw, an agentic AI framework, running on a Raspberry Pi. This showcases potential for low-cost, automated IoT solutions that builders can replicate or extend for smart device automation.
My experiment setting up #Openclaw on a #RaspberryPi
shish.substack.com/p/claws-curios
β¦
#AI #claw #AiAgent #AgenticAI #IoT
The tweet highlights real-world issues with AI agents triggering excessive actions and costs from simple prompts. Builders should note the importance of designing efficient agent workflows to avoid runaway expenses and unintended automation.
I was up until 1am fixing how my AI agents decide what to do.
The problem. A simple question like "what's our status?" triggered 3 AI agents. Each one called 10+ tools. Set goals nobody asked for. Updated boards unprompted. Cost 5x what it should.
I studied 6 open source agent
π 22 viewsβ€ 6π 0π¬ 0π 027.3% eng
AI agentsautomationworkflowcost controlproductivity
Fisent Technologies has launched Tabulate, an addition to its BizAI agentic solution, enhancing automation capabilities for business processes. Builders can leverage this to streamline workflows or offer automation services to clients.
Fisent Technologies has expanded its Fisent BizAI agentic solution with the introduction of Tabulate.
shorturl.at/0CTRb #FisentTech #AgenticAI #Automation
Oracle showcases an AI-powered workspace that automates risk spotting, supplier management, and accelerates product launches. Builders can leverage or offer similar automation solutions to streamline business operations for clients.
In this demo, watch an Agentic AI-powered DesignβtoβSource workspace turn from βwhere are we on this?β into βdone.β Spot risks early, line up suppliers, and keep a product launch moving fast.
social.ora.cl/6019B6vyEL
#Oracle
A builder shares an AI-powered n8n workflow that auto-classifies and routes incoming emails, eliminating manual inbox sorting. This is a practical automation that can save time or be offered as a service to clients overwhelmed by email.
Built this about a week ago, never posted it, but here we go.
Learned how to make an AI workflow in n8n that reads incoming emails, classifies them, and routes each one to the right label automatically.
Zero manual sorting. Clean inbox. It actually works.
@NexithAIAcademy
This tweet highlights replacing traditional diet apps with a custom workflow using ChatGPT and Excel, showing how AI can automate personal tracking tasks. Builders can adapt this approach to create or offer similar automation solutions for niche audiences.
replaced all my calorie tracking and diet apps with chatgpt, an excel sheet, and chatgpt tool to edit excel.
This tweet outlines a step in automating job execution using an Orchestrator, highlighting how tasks can be handed off for automated processing. Builders can leverage such pipelines to streamline operations and reduce manual intervention.
Slide 5
Step 3: Send to Orchestrator
β’ Click βRunβ or βExecuteβ
β’ System prepares your job
β’ Workflow moves to Orchestrator
Where execution begins
This guide explains how to translate common Airflow orchestration patterns to Databricks Lakeflow Jobs, enabling more integrated and automated data workflows. Builders can leverage this to streamline data pipelines and offer orchestration solutions to clients.
If youβre running Apache Airflow in production, this guide shows how common orchestration patterns map to Lakeflow Jobs, Databricksβ built-in orchestrator.
See how control flow, triggers, parameters, and dynamic execution work when orchestration is integrated with the lakehouse,
This tweet showcases a builder remotely fine-tuning models, running multiple AI agents, and managing work tasks while flying. It highlights the power of cloud-based automation and remote orchestration for entrepreneurs seeking to streamline and scale their AI operations.
Things Iβm doing while flying at 34,000 feet:
* Fine-tuning on my DGX Station (SSH)
* Running 8 concurrent
@cursor_ai
cloud agents
* Replying to emails
* Posting on X
π 31,070 viewsβ€ 101π 5π¬ 18π 140.4% eng
remote workAI agentsautomationcloudworkflow
write a newsletter/blog about itpost about it on Xaudience building
A builder shares a tool that streamlines sending content to AI chats, reducing manual screenshot pasting. This highlights a workflow automation that can save time for creators and could inspire similar productivity tools.
This is awesome.
I built
talktoyour.computer a while back to learn Make back then.
So much easier than pasting screenshots into any AI Chat all the time.
This post documents an efficient workflow for handling separation processes using TERM_MASS_COMM_v4, highlighting both template-driven and narrated documentation. Builders can adapt or offer similar automated HR or workflow solutions.
I did not flaunt. I documented. The separation workflow is TERM_MASS_COMM_v4. The documentation is this post. One has a PeopleSoft template. The other has a narrator. Both are efficient.