| Tuesday · June 9, 2026 · Issue #035 There's a word that's taken over every AI conversation in the last six months. You've heard it in every newsletter, every podcast, every LinkedIn post from someone wearing a blazer in front of a whiteboard. Agents. Most of the people using the word can't tell you what one actually does. And most of the businesses trying to build one are going to fail. Here's what's actually going on — and the one way to start that doesn't end in a $40,000 mistake. | | ⬡ The Number Nobody Wants to Talk About 80–90% of AI agent projects fail in production. Not in the demo. In real-world deployment. That's not a fringe estimate — it's a RAND Corporation figure, corroborated by Gartner, MIT, and Carnegie Mellon research. Enterprises with full engineering teams, dedicated budgets, and implementation specialists are failing at this. The reason almost never comes down to the wrong model. It comes down to the wrong scope. | | | ⬡ What an AI Agent Actually Is — In Plain English | | | A regular AI tool answers questions. You ask, it responds, done. An AI agent does work. It monitors triggers, makes decisions, takes actions across multiple tools, and handles multi-step tasks — without you telling it what to do at each step. Think of it this way: ChatGPT tells you how to follow up on a sales lead. An AI agent actually sends the follow-up email, logs the interaction in your CRM, checks the prospect's LinkedIn for context, and schedules a task if there's no response in 48 hours. Same underlying technology. Completely different scope. And that scope difference is exactly where most businesses go wrong. | | ⬡ The Three Ways Businesses Get This Wrong | | | ① They start with ambition instead of a problem "We want an AI agent to run our entire customer service department" is not a problem. It's a vision. And it's designed at a scope nobody can actually manage. The businesses that succeed with agents start with one specific, repeatable task: answer these 12 FAQ emails, route inbound leads by industry, schedule follow-up calls for proposals older than 5 days. One task. Bounded scope. Measurable outcome. | | | ② They test in demos, deploy to reality The RAND research is blunt: agents work beautifully in controlled demos and break in messy real-world conditions. Real clients deviate from scripts. Real emails don't follow the format you designed for. Real data has gaps. The businesses that succeed treat the first 30 days as a supervised trial — with explicit checkpoints, override capabilities, and human review built in before anything runs autonomously. The pilot IS the product, until you've proven it handles the edge cases. | | | ③ They automate before they understand the process This is the most expensive mistake. An agent can't understand your business logic if you haven't documented it yourself. Which leads are worth pursuing and which aren't? What makes a customer complaint urgent versus routine? What's the exception rule that everyone on your team knows but nobody's ever written down? If the process isn't clear enough to explain to a new hire in writing, it's not clear enough to automate. Document the process first. Build the agent second. | | | ⬡ Jordan · AI Solutions Director · thepromptory.com Free · No account required · No sales call after | | M | I've been hearing a lot about AI agents and I want to build one for my business. We're a 7-person consulting firm and I'm not sure where to start — or what we'd even automate first. | | J | Good instinct — and good timing. Before we get into tools, let me ask you something most people skip: what's the one task in your firm right now that happens the same way, every time, that you wish didn't require a human touch? That's where we start. Not with "automate everything" — with one repeatable process that already works, so an agent just takes it off your plate. Jordan · thepromptory.com → | | | Find the right first agent for your business → thepromptory.com | | | | ⬡ This Week's Tool · Lindy AI | | | 🤖 | Lindy AI AI Agent Builder · No-code · Free tier / From $19.99/mo · ✦ Vault Pick | Try it → | Lindy is the answer to the question: "How does a small business actually build an AI agent without a developer, a six-figure budget, or three months of implementation time?" It's a no-code platform that lets you build custom AI agents in plain English. You describe what you want the agent to do — and Lindy builds the workflow. No drag-and-drop configuration. No logic gate setup. Just: "When a new lead comes in from the website, research their company, draft a personalized intro email, and create a task in my CRM to follow up in 3 days." Done. The platform integrates with 5,000+ business apps — Gmail, Slack, HubSpot, Notion, Salesforce, and on — and recently updated with Claude Sonnet 4.5 integration, which meaningfully improves how agents handle complex, context-dependent decisions. Five things Lindy actually handles well: | ① |
Email triage and drafting — reads inbound emails, categorizes them, drafts context-aware responses, and waits for your approval before sending. The approval step is not optional and that's a feature, not a bug. | | | ② |
Lead research and enrichment — when a new contact enters your CRM, Lindy automatically researches the company, pulls relevant context, and adds notes before a human ever sees the record. | | | ③ |
Meeting prep and follow-up — 30 minutes before a meeting, Lindy pulls the relevant CRM history, last communication, and open tasks into a brief. After the meeting, it drafts follow-up notes and next-step tasks automatically. | | | ④ |
Customer support triage — resolves routine inquiries from a knowledge base, escalates anything complex to a human, and logs every interaction. Works across chat, email, and with Lindy's Gaia voice agent, phone. | | | ⑤ |
Internal knowledge search — connects to your apps and lets any team member ask "what did we decide about the Henderson account?" or "what's our refund policy?" and get a sourced answer from your actual documents. | | | | | 💰 What It Actually Costs Lindy runs on a credit model — basic automations cost 1 credit per action, AI-intensive tasks like email parsing or web research cost 5–10 credits. The $19.99/month Starter plan is enough credits for most small business workflows. Complex AI-intensive builds run closer to the Pro tier. One honest caveat: if you're running high-volume, always-on workflows, watch your credit consumption weekly until you know your burn rate. Lindy is transparent about this — they're not hiding the usage, it's just a variable model. Start with a clearly bounded use case and scale from there. | | | ⬡ How to Start Without Building a Monster | | | The businesses succeeding with agents right now share one thing: they treat the first agent as a proof of concept, not a transformation. Here's the exact sequence that works: | 1. |
Pick one repeatable task. Not "all our email." One type of email — inbound inquiries, or overdue invoice follow-ups, or meeting scheduling requests. One trigger, one output, defined clearly enough to explain to a new hire in two sentences. | | | 2. |
Write the process before you build the agent. What does a great outcome look like? What are the three most common edge cases? Where does a human need to step in? Write it out. This doc becomes the agent's instructions. | | | 3. |
Build with approval steps. The first version of any Lindy agent should require human sign-off before any external action fires. Email drafted — you approve before it sends. Task created — you review before it notifies anyone. Supervised automation, not unsupervised autonomy. Earn the trust before you remove the guardrails. | | | 4. |
Measure the one metric you defined upfront. Response time? Tasks handled without human input? Hours recovered? You can only know if the agent is working if you defined what "working" means before you turned it on. | | | 5. |
Only then, expand. Once the first agent runs cleanly for 30 days — consistent outputs, minimal overrides, measurable result — you've proven the model works for your business. Now you can build the second one. Not before. | | | | | ✦ Promptory Verdict · Lindy AI The best agent tool for small businesses that want real results without a developer. Lindy passed The Promptory's 5-point vetting standard — transparent pricing, real workflow fit, active development (Claude Sonnet 4.5 integration ships this year), proven SMB adoption, and clean data practices including GDPR, SOC 2, and HIPAA compliance. It's in the implementation stack we deploy for clients specifically because non-technical operators can actually use it. It's not magic. It won't fix a broken process. But if you have a clear, repeatable workflow and you follow the five steps above, Lindy is the fastest path from "we should automate this" to a working agent in your business — without writing a single line of code. | | | 📬 Tomorrow Wednesday Use Case: A business owner who did everything right — picked a clear problem, bought a solid tool, handed it to his team. And then watched it quietly make his biggest operational problem worse. What Jordan found when they finally looked at the actual process underneath the automation. Want Jordan to identify your best first agent use case? Free — no account needed → thepromptory.com | |
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