Greg Isenberg

AI Agents are the new SaaS

In this solo episode I lay out why I believe building agents is the new SaaS: software is shifting from helping you do the work to doing the work with you. I walk through a full playbook — find a niche, pick a workflow with a paycheck attached, shadow the human, spec the agent, build the minimum useful version, sell a pilot like labor, then productize the repeatable parts. I share live market examples like Slang AI for restaurants and Same Day for home services, plus pricing models and a distribution strategy built on workflow teardowns. I close with a 30-day, zero-to-100 plan for launching an agent-first business. This one is for anyone eager to build with AI or simply become more productive. Timestamps 00:00 – Intro 01:38 – Building Agents is the new SaaS 04:11 – Pick a valuable workflow 06:12 – Shadow the Human First 09:34 – Build the Minimum Useful Agent 12:50 – The wrapper makes it SaaS 15:50 – Sell the Pilot Like Labor (and Pricing) 18:37 – Own the workflow 21:45 – The Zero-to-100 Plan in 30 Days 24:14 – Closing Thoughts Key Points * Agent SaaS sells work as a service; the product is the job itself, priced like labor. * Start with a workflow that already carries a paycheck: high frequency, clear finish line, existing software, learnable edge cases, and felt pain. * Shadow a human across 10–20 real jobs before you write a single prompt — the detail is the product. * Ship the minimum useful agent — draft-and-approve, triage, coordinator, or bounded action — and earn autonomy over time. * The wrapper (logs, approvals, evals, analytics) creates trust and turns automation into real SaaS. * Win distribution with workflow teardowns: show the old way, show the agent way, sell the painkiller. Numbered Section Summaries 1. The Product Is the Job I frame the core mental model: SaaS sells software, while agent SaaS sells work. I want you to package a job your customer's team hands off entirely, then sell that outcome as a service. The shift feels small, yet it changes how the buyer and the builder think. 2. Real Examples: Slang AI and Same Day I share Slang AI as an AI super host that answers restaurant calls, manages reservations, routes VIPs, and alerts staff. I add Same Day for home services, selling AI dispatchers and receptionists that answer calls, book jobs, and reschedule. These examples make the pattern concrete: handle one annoying job better than a junior hire, faster than an agency, and cheaper than new headcount. 3. Pick a Workflow With a Paycheck I teach you to start with money that already flows to a receptionist, coordinator, or dispatcher. A strong workflow shows five traits: high frequency, a clear finish line, existing software to touch, learnable edge cases, and pain the buyer feels. My first rep: pick one niche, list 20 jobs people complain about, and score each on frequency, pain, clarity, tools, and budget owner. 4. Shadow the Human First Before any prompt or code, I watch a real person run the job across 10–20 cases, screen recording and narrating along the way. I hunt for the hidden workflow — what they check, where mistakes happen, and what makes a case weird. Then I spec the agent with seven parts: trigger, context, tools, allowed actions, approval points, escalation, and success. 5. Build the Minimum Useful Agent I keep the first version tiny and pick one of four shapes: draft-and-approve, triage, coordinator, or bounded action. I echo Anthropic's guidance that many agent problems begin as predictable workflows, and founders earn autonomy by adding judgment only where it creates value. 6. The Product Wrapper and Evals The agent does the work, and the wrapper — logs, approvals, controls, handoff rules — creates the trust customers pay for. I build an eval set from 50 real examples, mark the right answers, and run the system against them like a gym for the agent. 7. Sell the Pilot Like Labor, Then Productize I start with three customers in one niche, sell the outcome, and charge a simple setup fee plus a monthly fee. As I learn the value, I move toward usage or outcome pricing, which I believe is the future for agent-first software. 8. Distribution and the 30-Day Plan I win attention with workflow teardowns: show the painful old way, then the smooth agent way, and sell the painkiller. I commit to one platform, publish checklists, benchmarks, and 50 example posts, then put paid ads behind the winners. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com/ LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/