Build AI Workflows for Revenue Teams with Agent Studio

1. Start with the business, not the stack One principle I try to follow at Void Studio is simple: Understand the business before touching the technology. Before thinking about AI, frameworks, architecture, or features, I want to know what is actually holding the company back. Is it slow operations? Poor conversion? Too much manual work? Bad customer experience? Disconnected systems? Once the real problem is clear, the technical decisions usually become much easier. Sometimes the answer is AI. Sometimes it is automation. Sometimes it is just better software. I think good technology starts with knowing what should change in the business first.

Browser Extension of the Day: Guidde 🎥 Turn any web workflow into a professional video tutorial and step-by-step guide in seconds. Guidde is the AI platform that helps teams capture, edit, and share knowledge 11x faster than manual recording. ⭐ Captures your workflow naturally and builds the video plus a written SOP from a single pass ⭐ Repairs verbal mistakes and generates flawless voiceovers in over 50 languages automatically ⭐ Lets you update scripts or design elements later without needing to re-record anything Check it out here: https://lnkd.in/gd2kJkhn

Our audio and video team at Gamma Tech used to spend a lot of time preparing plans in PlanGrid. We had adapted it to our process, but marking up drawings and creating wire schedules still took a lot of manual work. We built our own application called Plan A around the way our team works. It helps us create more detailed plans and produces the wire schedules we used to put together by hand. Some planning work that used to take us 40 hours now takes a couple of hours at most. Over the past year, we've been using AI to help build custom applications for our own business. Plan A is one example, and this video walks through how we use it to prepare a plan.

Building a working demo with modern AI tools takes an afternoon. Turning that demo into a secure, enterprise-grade production asset still takes real engineering discipline. Here is the breakdown of software effort that AI demos don't reveal: 10%: Core feature logic and happy-path UI (The Demo). 90%: Edge-case handling, data privacy, tenant isolation, scalable infrastructure, automated testing, and long-term maintainability (Production). Demos win applause on pitch decks. Robust production systems protect company valuation and build long-term enterprise trust. Accelerate your prototyping with modern tools, but never mistake a working demo for a completed product. How does your team bridge the gap between fast initial prototypes and production-ready deployments?

Most teams I know have their work spread across six different tools.Issues in one. Docs in another. Chat somewhere else. Calls in a fourth. Then there’s a roadmap, automation, and everything else you need to keep the work moving. The problem isn’t really the number of tools. It’s the context you lose moving between them. So we built Lattice(https://lnkd.in/dmDyrhZ9). Lattice is one workspace where teams can plan, build, and ship together. You can manage issues across list, board, table, calendar, timeline, gallery, and split views. Plan with cycles, roadmaps, goals, and dashboards. Write docs, collaborate on whiteboards, chat, and jump on calls, all while keeping everything connected to the work. There’s also a visual automation builder and forms that can turn requests directly into issues. And then there’s Lattice AI. It understands your workspace, works within your permissions, and asks for approval before making changes. Everything is real-time, so when someone changes something, everyone sees it immediately. Lattice is available on desktop and mobile, with an experience designed to feel native on each. We’ve also connected it with Claude Code, so commits and branches can link directly to the issues they belong to.Lattice is built by CitaTech on our own full-stack TypeScript framework. One workspace instead of six. Try it out: https://lnkd.in/dmDyrhZ9 #ProductManagement #SoftwareEngineering #Productivity #AI #CitaTech

As a small business owner, my tech stack is always adjusting. I've tested most AI notetakers and calendars and i'm on the verge of building my own but before that happens, I've decided to give the hyped Granola AI notetaker a try. Day 3 using it and I must say my favorite thing so far is the simplicity and subtlety of the platform. Quick download to my desktop (no web browser only = noice) The UI is super simple to understand and if you're a Notion user you'll know exactly why I say that. Let's see if I keep it.

Caught the Manus 2.0 announcement video today, and whether or not you use their platform, the product shift they're pitching is interesting to watch. Most early agent tools focused on an all-or-nothing model: you type a prompt, the agent works behind the scenes, and it hands you a finished output in a closed sandbox. The problem with that approach has always been control. The moment you want to change one detail, re-prompting often scrambles the rest of the work. Looking at their 2.0 breakdown, the focus seems to be shifting toward giving users manual control back: • Moving from one-shot outputs to editable workspaces. Instead of just exporting a locked video or prototype, they're introducing multi-track timelines and inspectors so creators can manually tweak audio, swap footage, or adjust code. • Bridging cloud sandboxes with local workflows. Agents are starting to interact with local files and persistent servers rather than staying trapped inside a single browser tab. • Tackling the "first cut" rather than the whole finish line. The pitch is about letting AI generate the rough 80% foundation, while leaving the final 20% of craft, polish, and tuning to the user. As these platforms mature, the competition seems less about who has the cleverest chatbot and more about who builds the best hybrid workspace—combining fast generative scaffolding with deterministic, granular controls. For developers and designers: When you see tools like this, do you prefer full autonomy from an agent, or do you always want a timeline and inspector to fine-tune the output yourself? #GenerativeAI #CreativeTechnology #SoftwareEngineering #DevTools #ProductDesign #TechLeadership

⚡As solopreneurs and builders, our stack is our circuitry. If every task routes manually through you, the board overheats. Here is how I plug the latest Grok into my daily workflow engine: Real-Time Pulse via X Integration: While standard LLMs query static archives, Grok monitors live trends, sentiment, and breaking updates across the web and X in real time. DeepSearch for Research Sprints: Instead of opening 20 tabs, I use Grok’s DeepSearch to cross-examine multiple sources and map complex topics with source attribution in minutes. Deep Reasoning (Think Mode): For breaking down multi-step logic, edge cases in automations, and structural workflows before execution. Visual & Code Translations: Uploading schematics, process flows, or wireframes to generate direct, production-ready logic without starting from scratch. Don’t just add more tools—optimize how the signals route. How are you integrating live intelligence into your AI stack? #AIWorkflows #Grok #SystemsThinking #Automation #OneManArmy #TechLeadership

A small creative team can easily lose 6 to 8 hours a week just moving files, renaming assets, and updating trackers. Here's the workflow I build to remove that: 1. A brief arrives through a form or Slack 2. Make.com turns it into a structured ticket in Airtable 3. The OpenAI API drafts first-pass ad variations 4. The assigned owner gets notified and the asset is tagged automatically In setups like this, teams typically get back roughly 5 to 8 hours a week, and turnaround on ad variations drops from about two days to the same day. The lesson: automate the handoffs, not the creativity. The design still needs a human. Everything around it doesn't. I'll share a diagram of the scenario in the comments. #Make #Airtable #WorkflowAutomation

Most whiteboards end as a screenshot. Someone posts it in the channel after the meeting, and that's the last time anyone opens it. The decisions were on the board. Who does what, by when, was not. Here is one piece of work on Kaavit, from the first sentence to the plan. It starts as one sentence, and the AI drafts the flow onto the board as ordinary shapes, so the team has something to argue with in ten seconds. Everyone adds their options, then a vote nobody sees until it closes. The architecture is already on a board. Claude Code reads the code and the diagram and proposes the change. It can't just make it: a teammate reviews it like a pull request. The AI then writes the plan from what is on those boards, as tasks. Every task gets a name and a date, and turns up on that person's home page. End a session with names and dates before anyone leaves the board. Everything in the video is on the Free plan. The team and their booking app are made up for the demo. Your team's whiteboard, from idea to plan. https://kaavit.com #productmanagement #engineeringmanagement #teamwork