Dapols

You don't need ChatGPT Enterprise. A $20 plan + 2 good workflows beats a $200 plan you never configured.

AI tool pricing is deliberately confusing. "Contact sales." "Credits." "Seats." Per-message. We track real prices so you can compare apples to apples. #AItools

@boomerrbryan The gap isn't the tools, it's that owners don't know what's possible or what it should actually cost. Once someone shows them the real price and the exact setup, the $8k/mo agency looks absurd. Packaging is the whole game.

Someone is going to make a stupid amount of money selling "AI video production" to local businesses who don't know it costs $7 to do themselves And honestly? They should There are 33.2 million small businesses in America. 98% of them have zero video presence. Most of them are still running a website from 2019 with a stock photo of a handshake and a paragraph that says "We Put Clients First" These businesses spend $3,000-$8,000/mo on marketing agencies that deliver Instagram posts, Facebook ads, and a monthly PDF report nobody reads. The leads are mid. The content is forgettable. Nothing compounds A single person with a laptop and $200/mo in AI tools could walk into any of these businesses and say: "I'll produce 4 professional videos per month of you answering your customers' most common questions. They'll rank on Google and YouTube. They'll generate leads forever. $2,000/mo" The business owner says yes because $2,000/mo is half what they're paying their current agency for worse results Your actual cost to fulfill: one 30 minute Zoom call with the client per month. AI scripts the conversation into 4 separate videos with hooks and retention structure. AI handles the edit and thumbnail. Total cost per client: ~$42 in tool subscriptions $2,000/mo per client. $42 in costs. That's a 98% margin 10 clients = $20,000/mo 20 clients = $40,000/mo Fulfillment time: maybe 15 hours/week total The best part? These businesses will never churn because the videos actually work. A local dentist who starts getting calls from people saying "I saw your video about whitening" isn't canceling. Ever. The ROI is too obvious And you don't need to be good on camera. You're not the face. The BUSINESS OWNER is the face. You're the operator behind the scenes running the tools they'll never learn to use themselves Here's why this is the most asymmetric opportunity in local marketing right now: Marketing agencies charge $5,000-$8,000/mo and use HUMAN editors, HUMAN writers, HUMAN designers. Their margins are 30-40% after payroll. They need 50+ clients to make real money and they're constantly managing staff You charge $2,000-$3,000/mo and use AI for everything. Your margins are 97%. You need 10 clients. You manage zero employees. You scale by adding Zoom calls to your calendar Subscribr is the tool that makes this whole operation possible. It handles the research, scripting, editing, thumbnails. You just run the client calls and upload The agencies charging $8,000/mo for human-produced content are about to get destroyed by solo operators charging $2,000/mo for AI-produced content that performs better And neither the agencies nor the business owners have figured this out yet The window is wide open Run it up (we built the tool that powers this entire operation. link in bio.)

@Josh_streimer @CPATaxTeam @darinpierson Both can be true. The owner doesn't need to become a prompt engineer, they need someone to hand them the exact 2-3 tools to use and the questions to ask. Remove the "figure it out yourself" step and adoption stops being the blocker.

@CPATaxTeam @darinpierson Oof I’m gonna say wrong, on this hot take. The average small business owner doesn’t know the right question to ask, let alone have the desire to learn or do the leg work consistently. AI is a done for you tool when you understand how to use and automate it.

Hot Take: For small business I think AI is a better CFO than accountant right now.

@SethiRanji6788 Honestly depends on the job. ChatGPT for quick drafting, Claude for longer reasoning and writing, Perplexity when I need sources. The "best AI tool" is usually just the right one for the task in front of you.

Be honest, which AI tool do you use the most right now?

@MB_BlueLogic "Start small, scale smart" is underrated advice. The 20 hours usually hide in the boring stuff, inbox, quotes, scheduling. Most owners overspend chasing shiny tools when 2-3 well-picked ones cover 90% of it.

Small business owners: You don't need a 6-figure tech budget. 00-500/month in AI tools can save you 20+ hours weekly. Start small, scale smart. #SmallBusiness #Budget

@MarciaMacomber The trick is to not "adopt AI" as a project. Pick one painful task that eats time every week (email replies, quotes, scheduling), automate just that, and let it earn back the hours before adding anything else. Small wins compound.

Small business owners face a conundrum: How do they adapt AI into their daily workflows when every minute is already accounted for? Further, if they don't incorporate AI tools, will they remain competitive? What are your thoughts? #AITools #AI4SmallBusiness #AIadaptation #AIwork

@jeditrinupab The 2026 line is the real one. Most founders are still stuck at "which tool" because nobody hands them the whole picture: the stack, the prompts, and how it fits their actual workflow. Redesigning around AI starts there.

The biggest AI shift for founders: 2023: “How do I write better prompts?” 2024: “Which AI tool should I use?” 2025: “Can AI build apps for me?” 2026: “How do I build an AI operating system for my company?” The winners won’t just use AI. They’ll redesign the business around it.

@FastLoopD This nails it. The problem was never the models, it's the assembly required. Most people just want a small stack, a few prompts that work, and to get the job done. Curation beats another dashboard.

Why AI setup isn’t dead simple? Too many AI tools Too many prompts Too many clicks Too much setup Too many integrations Too much copy & paste Too many workflows Too much context switching Too many model choices Too much configuration Too much debugging Too much waiting Too much manual verification Too many subscriptions Too many dashboards Too many notifications Too many disconnected apps Too much AI management AI doesn’t fit existing workflows AI creates more work than it saves Everyone becomes “human middleware” Nobody wants to engineer prompts Everyone just wants the job done AI isn’t too dumb—it isn’t simple enough.

@tymofii @ranjeetsmile Solid point. Tool sprawl is usually a symptom of nobody owning the whole stack. Fewer tools you actually understand beats ten you bolted on and forgot about.

@ranjeetsmile Disagree. I've seen too many “AI tools” break in production when nobody understands the code underneath. It's an and, not an or.

In 2 years, knowing how to use AI will be more valuable than knowing how to code. Agree or disagree? 👇

Cheapest AI win for a small business in 2026: automated customer email replies for FAQs. Setup once. Saves ~5 hrs/week. Costs less than one coffee a day.

"AI will replace you" is the wrong fear. "Your competitor automated their invoicing and quoting while you didn't" is the real one.

We got tired of "AI for business" guides that list 100 tools and help with none. So we built the opposite: take a 2-min quiz, get the exact stack for YOUR business + budget. dapols.com #AIforbusiness

The 3 questions to ask before buying ANY AI tool: 1. What task does this remove from my week? 2. What's the real monthly cost? 3. Can my team actually use it? If you can't answer all 3, don't buy yet.

Most small businesses don't have an "AI problem." They have a "too many tools, no plan" problem. You don't need 40 AI apps. You need the right 4. #AItools #smallbusiness

@CFOAnalysis Jumping in beats another course for most owners. The trick is picking one real task this week, like drafting customer replies or cleaning up a spreadsheet, and doing it with AI start to finish. Learning by shipping sticks way better.

The best way to learn AI is to jump right in. Not ready for that? Here are nine free courses you can take today. Every one clears the same bar: it helps a business owner actually put AI to work, not just understand it. Start simple → learn to use it well → turn it into a strategy → apply it to your own business START WITH THE BASICS 1. Google — Introduction to Generative AI. A 45-minute intro to what generative AI is and how it works. 🔗 coursera.org/learn/introduc… 2. DeepLearning.AI — Generative AI for Everyone. Andrew Ng on how generative AI works and where it fits in a business. 🔗 coursera.org/learn/generati… 3. Microsoft — Career Essentials in Generative AI. A structured intro to using AI tools in everyday work. 🔗 linkedin.com/learning/paths… LEARN TO ACTUALLY USE IT 4. Anthropic — AI Fluency: Framework & Foundations. A framework for delegating to AI, directing it, and checking its work. 🔗 anthropic.com/ai-fluency 5. Vanderbilt — Prompt Engineering for ChatGPT. How to write prompts that get better answers from AI. 🔗 coursera.org/learn/prompt-e… TURN IT INTO A STRATEGY 6. Amazon — Generative AI Learning Plan for Decision Makers. How to plan an AI project and prepare your organization. 90 minutes. 🔗 skillbuilder.aws/learning-plan/… 7. IBM — Generative AI for Executives and Business Leaders. Where AI pays off across marketing, service, finance, and HR. 🔗 coursera.org/specialization… 8. Wharton — AI Fundamentals for Non-Data Scientists. AI fundamentals taught for business leaders. 🔗 coursera.org/learn/wharton-… APPLY IT TO YOUR BUSINESS 9. University of Maryland — AI Empowerment for Small Businesses. Built for business owners bringing AI into a small company. 🔗 coursera.org/learn/ai-empow… You don't need all nine. Pick one and actually do it this week. Short on time? The Google intro and Anthropic's AI Fluency are the quickest. Which one are you starting with? 🔖 Save this so the whole list is here when you need it. 🔔 Follow Leysan Gilfanova — practical AI for business owners.

@ryanmckeen This is underrated. Especially in law, where the data question is the whole ballgame. Pick the tool second, decide where client data lives and who can see it first. Foundation before features.

Lawyers, "which AI tool should I buy" is the wrong first question. "Where does my data live" is the right one. Fix the foundation first.

@shaikhimran786 Execution problem is exactly right. The teams who win aren't using fancier models, they just picked one painful workflow and rebuilt it around AI end to end. Narrow and finished beats broad and experimental.

Most organisations don’t have an AI problem. They have an AI execution problem. Every week, I speak with engineering leaders excited about the latest AI model, coding assistant, or autonomous agent. But very few ask the question that matters most: “How do we turn AI into measurable business value?” Here are 12 practical ideas every technology leader should consider. 🚀 3 AI Strategy Tips ✅ Use the right AI model for the right task • Coding → Claude Sonnet • Deep reasoning → Claude Opus • Fast responses → Claude Haiku The best AI architecture is built around strengths, not convenience. ✅ Measure before you scale Build evaluation frameworks first. Track quality, consistency, and business impact before expanding AI adoption. ✅ Review your AI portfolio Ask: • Does it reduce cost? • Does it improve customer outcomes? • Is ROI measurable? If not, rethink the investment. ⚡ 3 Productivity Hacks • Connect your tools using MCP for better AI context. • Use AI to generate test cases, not just production code. • Automate daily briefings with industry news, internal updates, and competitive insights. 🧠 3 Prompting Techniques Chain of Verification Ask AI to list and verify its assumptions. Contrastive Prompting Generate opposing viewpoints before making strategic decisions. Role Stack Prompting Example: “Answer as a CTO evaluating technical feasibility and a CFO evaluating 3-year TCO.” 🤖 3 Automation Ideas • Automate AI governance documentation. • Build AI talent intelligence agents. • Benchmark your AI products continuously against competitors. My biggest takeaway AI won’t reward the companies that adopt it first. It will reward the companies that build the best systems around it. Technology is becoming accessible to everyone. Execution will remain the real competitive advantage. 💬 Which AI practice has delivered the biggest impact for your team? 👇 Share your experience in the comments. 👉 Follow for more insights on AI, Product Engineering, and Technology Leadership. linktr.ee/shaikhimran786 #ArtificialIntelligence #AILeadership #ProductEngineering #EngineeringLeadership #AITransformation #GenerativeAI #TechLeadership #SoftwareEngineering #Innovation #DigitalTransformation

@TechwithPeter Honestly a 100-tool toolkit is the problem for most people, not the solution. I get more done sticking to 3-4 I actually know well than bouncing between dozens. Depth beats collecting tabs.

🚀 100+ AI Tools. One Ultimate Toolkit. From content creation to coding, these are the tools shaping 2026. 🤖✨ The right AI tools can save time, boost creativity, and multiply productivity. ⚡ 🔖 Save this toolkit and stay ahead of the curve. Which AI tool do you use the most? 👇

@mfishbein The imagination gap is the real one. Most small teams I see aren't short on tools, they just never mapped which task to point AI at first. Start with your most repetitive weekly task and the ROI becomes obvious fast.

Everyone has access to the same AI tools, but no one is using them to their full potential. There are infinite ways to use AI. Some give you ROI, some destroy it. The companies who are behind on AI are failing because of one or more of these reasons: 1. Imagination Most companies are only using AI to solve small problems. Random tasks. But the reality is, AI can do almost anything for you now. It’s just a question of how much: - engineering - tokens - human in the loop How to bridge the imagination gap: understand AI’s strengths and capabilities today. Point AI at your biggest problems. If you’re not feeling shock and awe daily, you’re gonna get left behind. 2. Strategy Mythos could drop tomorrow, but if you don’t have a good strategy for it to execute, you will fail to get ROI from it. How to solve the strategy problem: forget about AI for a minute. Find the biggest growth lever or constraint in your business. Point AI at the same strategic initiatives as your people. 3. Expertise Off the shelf AI is generic. If you can buy it, so can your competitors. How to solve: get AI to run your unique playbooks. Train it to make context dependent judgement calls like your best employees. Build what you can’t buy. When you buy, make sure your vendor has FDEs who can get it working in your context and with your expertise. Or hire your own. 4. Engineering AI makes coding 90% faster. But code is only 10% of what it takes to get AI to deliver excellent work and drive outcomes for you. AI engineering requires a unique combination of skills. It’s a galaxy apart from legacy software development. Most companies don’t have people with this skills in-house. If they do, they’re working on product and shouldn’t be context switching to internal tools. How to solve the skill gap: hire in-house or fractional/agency. You need people with a unique skill stack that includes strategy, product, and engineering.