Share your best AI workflow. We could show it to 2M+ people.

I created a data extraction and enrichment tool using a free Google Gemini account to write the necessary Python scripts. The tool extracts contact lists based on specific search criteria and enriches the contact details through API calls to Lusha. Step-by-step: 1. I used a free Google Gemini account to write the necessary Python scripts. 2. I applied specific search criteria to extract a list of contacts. 3. I enriched the contact details using API calls through Lusha.

After a sales call, the conversation is only part of the work. Someone still needs to write the notes, update the CRM, remember the next step, prepare the follow-up email, and make sure the deal does not disappear between meetings. I wanted that entire post-call process to happen automatically. I created an Awish workflow that starts when a sales call ends. It analyzes the conversation, extracts the important sales information, updates the CRM, creates the next actions, drafts a personalized follow-up email, and sends the team a short summary. The workflow looks for the information I would normally write down myself: what the prospect needs, the objections they raised, their timeline, agreed next steps, and anything that could affect the deal. Customer-facing actions stay under my control. The workflow prepares the follow-up, but I can review important messages before they are sent. Step-by-step: 1. I tell Awish what I want to happen after every sales call: analyze the conversation, update the CRM, prepare the follow-up, and notify the team. 2. Awish understands the request, plans the workflow, and determines which applications are needed. 3. I connect my meeting platform, HubSpot, Gmail, and Slack to the automation. 4. When a call ends, the workflow analyzes the transcript and extracts the prospect’s needs, objections, timeline, decisions, and agreed next steps. 5. It creates or updates the contact and deal in HubSpot and adds any follow-up tasks that came out of the conversation. 6. It drafts a personalized Gmail follow-up based on what was actually discussed instead of using a generic sales template. 7. It sends a short Slack summary to the team with the deal status, important points, and next action. Instead of a sales call ending as a transcript or a page of notes, it immediately becomes structured CRM data, clear next actions, and a follow-up that is ready to review. The useful shift for me is that the workflow is not replacing the sales conversation. It is handling everything that normally gets forgotten or delayed after the call.

I have a Daily Brief agent on Codex with access to my Slack, Gmail, Notion, and Google Drive that checks everything that happened in the last 24 hours on request. It sends me the brief through Slack, and I do maybe 10% of the final manual editing. I also gave it several examples of before/after editing, so now it sends messages in my exact voice and style. Step-by-step: 1. I connected my Daily Brief agent in Codex to Slack, Gmail, Notion, and Google Drive. 2. I told it to review activity from the last 24 hours and pull out the items that actually needed attention. 3. I structured the output as a concise brief and had Codex deliver it through Slack. 4. I manually reviewed the draft and made the final edits before using it. 5. I gave the agent before-and-after examples of those edits so future briefs would sound more like my own voice.

I use Copilot to build an agent that critically reviews my internal audit work. I only need to upload a format. 1. I upload the format to Copilot. 2. I use Copilot to build an agent that critically reviews my internal audit work.

Microsoft is retiring Publisher on October 1, 2026. I have many `.PUB` files that I need to convert to PDFs before then, but I did not want to use online converters. I wanted a solution that would run locally on my computer. I worked with Claude to create a lightweight program that searches for `.PUB` files on a drive of my choice and converts them into high-quality PDF files, placing each new PDF in the same folder as its source file. Opening PowerShell manually and managing permissions was too cumbersome, so Claude also created a batch file to make the process easier. For anyone who wants to create their own mini-program, I asked Claude to create a reusable prompt. I posted that prompt at https://mediumseagreen-seal-177480.hostingersite.com/ along with my two files: the batch file and the PowerShell commands. Step-by-step: 1. I identified the `.PUB` files I needed to convert before Microsoft retires Publisher on October 1, 2026. 2. I decided to use a local solution instead of an online converter. 3. I worked with Claude to create a lightweight program that searches a selected drive for `.PUB` files. 4. I set up the program to convert the files into high-quality PDFs and place each PDF in the same folder as its source `.PUB` file. 5. I used a batch file created by Claude so I would not need to open PowerShell manually or manage permissions each time. 6. I asked Claude to create a reusable prompt for others who want to build their own version and posted it with the batch file and PowerShell commands at https://mediumseagreen-seal-177480.hostingersite.com/.

San Diego County is enormous, and its startup scene is growing rapidly. I wanted a better way to see where companies are located, especially because many of them host networking events and there was no central map or repository. I told Claude what I wanted: an alphabetical directory with an industry selector and a way for people to add their own companies. I also asked it to keep the project as simple as possible, use as few tokens as possible, and wait for my approval before taking any action. Claude helped me design the map, create the Google Form for submissions, set up the Google Sheets workflow for hosting and approving companies, and use Netlify to host the main file. It also guided me through linking the map to a page on my own website: https://sdaimap.michelabood.com/. Claude warned me about the legal issues involved in scraping a list wholesale from other sites, so the map is designed to be populated by people submitting their own companies. I just published it, and 10 companies have already been listed, with more on the way. I have also received great comments on LinkedIn. Now I can see at a glance how far I need to go to find a specific company. I also had Claude create a step-by-step guide, which I am happy to share if people want it. Step-by-step: 1. I described the map I wanted to Claude, including an alphabetical directory, an industry selector, and a way for people to add their own companies. 2. I asked Claude to keep the project as simple as possible, use as few tokens as possible, and wait for my approval before taking any action. 3. I used Claude to design the map and create the Google Form for company submissions. 4. I used Google Sheets to host and approve the submitted companies. 5. I followed Claude's guidance to host the main file on Netlify. 6. I linked the map to a page on my own website: https://sdaimap.michelabood.com/. 7. I avoided scraping a wholesale list from other sites because of the legal issues Claude identified. 8. I published the map and began collecting company listings from people directly.

I had a project that was perplexing me, so I asked an AI for help by simply typing, "I'm a stupid moron." The AI helped me with the issues I was having with my project. 1. I described my project-related difficulties by typing, "I'm a stupid moron." 2. I used the AI's help to address the issues I was having with my project.

I created a website lead workflow that researches each company, scores the opportunity, updates my CRM, drafts a personalized reply, and notifies me on WhatsApp. I had previously built similar workflows with Claude Code, but connecting external applications was often the hardest part. I had to manage OAuth setup, credentials, APIs, and different integration requirements for every app. I also found it difficult to monitor and control completed automations from WhatsApp without building additional infrastructure. To solve this, I created Awish, a tool focused on AI-powered automation. Instead of manually designing every workflow, I describe the result I want in chat. Awish’s agents understand the request, plan the automation in the background, determine which applications and steps are required, and prepare the complete workflow for me. When a new lead submits my website form, the workflow researches the company, evaluates the lead against my criteria, assigns a score, and adds the contact and research results to my CRM. It then drafts a personalized response based on the lead’s company and needs before sending me a WhatsApp notification for review. The application connections are handled through a simple sign-in flow. I connect my personal accounts with a click instead of manually working with OAuth code, API keys, or custom authentication logic. Once the workflow is active, I can monitor it, receive updates, and manage its actions directly from WhatsApp without opening the Awish application. Step-by-step: 1. I open the Awish chat and describe the workflow I want: when someone submits my website form, research the company, score the lead, add it to my CRM, draft a personalized response, and notify me on WhatsApp. 2. Awish’s agents analyze the request and create the application and automation plan on my behalf, including the trigger, research steps, lead-scoring logic, CRM fields, response draft, and notification. 3. I review the proposed plan and sign in to the required applications with my personal accounts to connect them to the workflow. 4. Awish builds the automation so each new website submission triggers company research and collects the information needed to evaluate the opportunity. 5. The workflow scores the lead, creates or updates the CRM record, and stores the contact details, company research, and lead score in the appropriate fields. 6. It drafts a personalized response using the information submitted by the lead and the additional company research. 7. I connect WhatsApp from the Awish chat, and the workflow sends me the lead details, score, CRM update, and response draft there. 8. I review and manage the automation directly from WhatsApp without needing to open Awish or build a separate messaging integration. The result is a lead-management workflow I can create through a conversation, connect to my existing applications without manually implementing OAuth, and control from WhatsApp while the agents handle the planning and execution in the background.

I built an Android mobile app that captures and organizes image photologs. Each photo is automatically saved with its date, time, and GPS location, including a link to Google Maps. I can dictate or type notes about an image, then add to or edit those notes later by typing or dictating. When I finish the notes, I add a tag to the photo. The tag remains persistent until I change it or close the app session. This makes it possible to retrieve all images from a session at a location, event, inspection, or other shared subject—such as a 1957 Ford—within seconds by searching by tag or date. All photos are stored exclusively on the user’s phone. Photos can be shared individually, or an entire set can be exported as a ZIP file. Shared and ZIP images arrive at the recipient’s end with all recorded dates intact. Each ZIP file contains the original raw image, an Excel sheet with one row per image and its date, and a formatted field report with each image and its related date in a single image card. The app works with or without cellular or Wi-Fi service. Step-by-step: 1. I capture an image, and the app automatically records its date, time, and GPS location with a Google Maps link. 2. I dictate or type notes about the image. 3. I add to or edit the notes later by typing or dictating. 4. I add a tag when I finish the notes; the tag remains active until I change it or close the app session. 5. I search for images by tag or date. 6. I share individual photos or export an entire set as a ZIP file containing the original raw images, an Excel date sheet, and a formatted field report.

As a Lutheran pastor, I created a Claude skill to shorten sermon preparation. It gathers each of the readings for a Sunday, adds a brief commentary, highlights key words from the original languages, and suggests three different outlines for each reading. Step-by-step: 1. I use the Claude skill to gather each of the readings for a Sunday. 2. It adds a brief commentary to the readings. 3. It highlights key words from the original languages. 4. It suggests three different outlines for each reading.

I built a tool that makes it easy to collect feedback and reviews for digital products, meetings, YouTube channels, and physical items. Display a custom QR code on your screen or at your point of sale so people can scan it and leave feedback or a review. Users do not need a Google account to submit their responses. You can filter the feedback and share it on social media to help promote your service or product. The easy-to-use dashboard also provides sharing tools and widgets for websites. Step-by-step: 1. I created a custom QR code for the product, meeting, channel, or item. 2. I displayed the QR code on a screen or at the point of sale. 3. I let people scan the code and submit feedback or a review without needing a Google account. 4. I filtered the collected feedback in the dashboard. 5. I shared the feedback on social media and used the available website widgets and sharing tools.

I created a skill that helps me submit a garment reimbursement every month. It handles the long forms and the upload of thousands of different documents required for the reimbursement. Step-by-step: 1. I created a skill for submitting my garment reimbursement. 2. I use it every month to complete the required long forms. 3. I upload the different types of documents needed for the submission.

I wanted to see what Awish would automate first if I gave it a real client business instead of a predefined workflow. I used Martolia Marble, one of my previous clients, and gave Awish the website. I asked it to analyze the business, suggest automations that could support growth, and build them only after I approved them. Awish analyzed the website and proposed several opportunities. I chose two: a lead generation and email outreach workflow, and an Instagram workflow that tracks relevant trends, plans content, creates posts, and publishes them. Step-by-step: 1. I gave Awish the Martolia Marble website and asked it to analyze the business. 2. Awish identified areas where automation could support growth and suggested workflows. 3. I approved a lead generation workflow that finds relevant prospects and prepares personalized email outreach. 4. Awish selected the required apps, I connected the accounts, and the agents built the workflow. 5. I also approved an Instagram workflow that analyzes relevant trends, plans upcoming content, creates the posts, and publishes them. 6. Once the accounts were connected, both automations were ready to run without me manually building each step. What I liked most was starting with the business rather than with an automation idea. I gave Awish the website, reviewed its suggestions, and approved only the workflows that made sense for the client.

I conducted a workflow experiment with Awish, the product I built, and the results surprised me. I think this approach could be useful for anyone who wants to automate more of their business but is not sure where to start. I gave Awish my website, and it identified the automations my business was missing. The difficult part was not always building a workflow; it was figuring out which tasks were worth automating first. I opened Awish and asked: “Analyze my business from awish.ai, suggest automations that could improve how I work, and only build them after I approve.” Awish’s agents analyzed the website to understand what the business does, how customers interact with it, and where repetitive work could be automated. Instead of asking me to design a workflow from scratch, Awish suggested several automations based on the business. One suggestion was a lead workflow that finds relevant prospects and automatically prepares and sends personalized outreach emails. Another was a website inquiry workflow that analyzes new customer requests, identifies what they need, and sends me the important details as a WhatsApp notification. It also suggested a content workflow that creates and publishes posts for Instagram, X, and LinkedIn based on the business and its content strategy. I chose the lead generation and automated email workflow. Step-by-step: 1. I opened the Awish chat and asked it to analyze my business from awish.ai, suggest automations that could improve it, and only build something after I approved it. 2. Awish’s agents analyzed the website and identified repetitive sales, customer communication, and content tasks that could be automated. 3. Awish suggested a lead generation and email outreach workflow, a website inquiry analysis and WhatsApp notification workflow, and a social content workflow for Instagram, X, and LinkedIn. 4. I selected the lead generation and automated email workflow. 5. Awish’s agents understood the request and created the workflow plan, including how leads should be found, what information should be collected, and how personalized outreach should be prepared. 6. Awish selected the applications needed for the workflow and showed me the connections before anything was built. 7. I approved the plan and connected my personal accounts to the required applications through the sign-in flow instead of manually setting up each integration. 8. Awish built the automation within minutes, so new leads could be identified, researched, and contacted through the workflow without me having to design each step manually. What I like about this approach is that I do not need to know the exact automation I want before I start. I can begin with the business itself, let the agents identify useful opportunities, choose the one that makes sense to me, and then approve the build.

I configured Claude to review my calendar every two weeks for scheduled VIP meetings. 1. I configured Claude to review the calendar biweekly. 2. I set it to identify scheduled VIP meetings.

I built an Opportunity Intelligence app with Claude Code for our sales team. Team members select the state and industry they want to target, and the app pulls live signals, such as whether a company is hiring for a specific role or opening a new facility, among others. The app then produces a top 10 list for further research, including a company overview, how our products work within that organization, battlecards, a custom LinkedIn introduction message, and a custom email message. From there, the team can research specific people at each organization. The app produces a top 10 list of targets with their LinkedIn profiles, phone numbers, and email addresses. Step-by-step: 1. I built an Opportunity Intelligence app with Claude Code for our sales team. 2. Team members select the state and industry they want to target. 3. The app pulls live signals, including whether companies are hiring for specific roles or opening new facilities. 4. The app generates a top 10 list of companies to research, with a company overview, how our products work within each organization, battlecards, a custom LinkedIn introduction message, and a custom email message. 5. Team members use that information to research specific people at each organization. 6. The app generates a top 10 list of targets with their LinkedIn profiles, phone numbers, and email addresses.

Most days, I want one capable general AI agent. The failure mode appears with higher-stakes questions in security, finance, law, or medicine: my main chat is already full of project context, the agent may answer confidently outside its depth, and a “specialist” prompt in the same thread still inherits the assumptions and tools that session has already loaded. I set up Hermes Agent with a consultation workflow that cold-starts an isolated specialist profile for a one-shot answer. I keep four advisors ready: security, financial, legal, and medical. Each call starts a separate process with its own model, tools, and skills. The specialist has no access to my parent conversation, so I have to write a self-contained prompt. It takes anywhere from a few seconds to a couple of minutes—not instantly—which is fine because I only use it when the stakes justify the wait. The gate is the part I care about most. Nothing runs until I explicitly name the profile, approve the exact prompt, and confirm. There is no silent auto-routing. When I want a second opinion, I draft my own take first, send the same question to the specialist, and compare where we agree and differ. This keeps the general agent honest and prevents specialty advice from becoming the default for routine work. I also keep the scope tight. I limit the medical profile to personal or educational questions, or fully de-identified material—not identifiable patient care. Routine work that my main agent already handles well never goes through consultation. I reserve the specialist profiles for deliberate second opinions or questions I do not want the default session answering alone. Step-by-step: 1. I work through the problem in my main Hermes session and write my own answer first when I want a second opinion. 2. If the question is high-stakes in security, finance, law, or medicine—or I simply want a deliberate second look—I choose the specialist profile to use. 3. I write a self-contained prompt with every fact and constraint the specialist needs because it cannot see the parent chat. 4. I name the profile, approve the prompt, and confirm before anything runs. 5. I let Hermes cold-start that profile as a separate process and return a one-shot answer. 6. I compare my draft with the specialist’s response: where we agree, where we differ, and what still needs a human professional. 7. I skip consultation for routine work and keep medical use limited to personal, educational, or de-identified material.