90–180 pages of operator content
Real frameworks, real numbers, real positioning. Not motivational fluff.
Vol. G2 · For agent builders
Production agents that don't break. Eval-first. 180 pages.
A working playbook for shipping production AI agents, stack, evals, pricing, sales, with no hype.
4.5 from 75 early-access reviews
Pages
180
Chapters
12
Templates
12
Delivery
Instant PDF
$197one-time · lifetime updates
30-day money-back guarantee · 1,407 early operators tested it · Secure checkout
Or pair with prompts, get everything for $497 (save $679).
What you actually get
Inside The AI Agent Builder Playbook.
Every concrete asset that lands in your inbox at checkout. No surprises, no upsells.
8–14 included templates
.docx + PDF — proposals, scripts, contracts, calculators, decks.
Real scripts, real contracts
Lawyer-reviewed, plain-English. The kind of paperwork you can actually use.
90-day execution roadmap
Day 1 to first client, in order. No more "what do I do next?"
Written by an operator
By someone who actually ran the business, then reviewed by two more operators currently running it.
Email + cold outreach swipes
The exact subject lines, opens, and follow-ups that book discovery calls.
Lifetime updates
New editions free, forever. Every playbook improves with the buyers in it.
Built for:
- You've built apps with LLMs and now want to ship an agent that does real work end-to-end.
- You can write Python or TypeScript and don't need a framework comparison from 2023.
- You're technical, but you've never had to price an agent or sell to a CFO.
- You're an engineer who wants to charge $200 for the same work, not $50/hr.
Not for:
- You've never shipped any production software.
- You think "agent" is a marketing buzzword.
- You expect tutorial-level code walkthroughs.
- You want this to cover image-gen or video.
The three paths
Three ways to start a ai agent builder business.
Only one of them doesn't waste your money or your year.
Path one
The course / mentorship
Pay $2,000–$10,000+
- Months of video lessons you'll never finish
- Constant upsells to the "next level mastermind"
- Generic advice that doesn't fit your situation
- Coaches who've never run the business themselves
- You finish 4 modules, then quit
Average outcome: $0 in revenue, $5K out of pocket.
Path two
Do it yourself
Free, but expensive
- Stitching together 100 YouTube videos
- Reading Reddit threads with conflicting advice
- Guessing at pricing, scope, contracts
- 8 months in, still no clients
- Burnout, then back to your day job
Average outcome: $0 in revenue, 1 year lost.
Recommended
Path three
Promptos Playbooks
Pay $97–$497, once
- Complete step-by-step playbook for ONE business
- Real scripts, real templates, real numbers
- Pair with prompt packs for daily execution
- 90-day roadmap from day 1 to first client
- Lifetime access. No upsells. Ever.
Designed outcome: paying clients within 90 days.
Get AI Agent Builder, $197 What's inside
12 chapters. 180 pages. No filler.
Each chapter is a working piece of the operating system, written so you can execute on it the same day.
Chapter 01
What an "agent" actually is
A working definition that survives a sales call and a code review.
12 pages
Chapter 02
The five agent archetypes
Ranked by complexity and revenue potential.
14 pages
Chapter 03
Tooling stack
LangGraph, Pydantic AI, custom, when each is right.
16 pages
Chapter 04
The eval-first workflow
Why every other workflow regresses, and how to fix it.
14 pages
Chapter 05
Memory, tools, state
The three pieces that decide whether your agent ships or wanders.
16 pages
Chapter 06
Multi-step planning
When to plan, when to react, and how to keep tokens honest.
14 pages
Chapter 07
Productizing an agent
From notebook to SaaS without lighting your weekends on fire.
14 pages
Chapter 08
Pricing per-call vs. seat vs. retainer
The math behind each, with real customer examples.
14 pages
Chapter 09
Selling to non-technical buyers
The vocabulary swap that turns interest into budget.
14 pages
Chapter 10
Demos that close
Open with the pain, end with the math. With scripts.
12 pages
Chapter 11
Support and uptime
What "production" actually means and what to promise.
14 pages
Chapter 12
Beyond MVP
The path from one customer to ten, and what changes.
12 pages
A real chapter from the book
See exactly what you're reading.
Chapter 01
What an "agent" actually is
Half the AI agent content online is people calling a single LLM call with a tool list an "agent" and shipping it. The other half is a 12-layer LangChain stack from 2023 that no one can debug. Neither is what your customers are paying for. An agent, for the purposes of this playbook, is a system that can take a goal, decide what to do next, use tools to do it, and check whether the work is done. Three pieces: a planner, an actor, and a verifier. Everything we build in the next eleven chapters fits that frame.
- A working definition: planner + actor + verifier. If you can't name all three in your agent, it isn't one.
- Why "agentic" is doing too much work in most product copy, and what to say instead.
- The three failure modes: planning loops, tool hallucination, verifier blindness.
- How to draw a one-page diagram of your agent in a meeting and have it survive code review.
- The "would the on-call engineer wake up?" test, if no, it's not production.
In chapter two we map this definition onto the five agent archetypes that actually generate revenue, ranked by build cost and what buyers will pay.
+11 more chapters inside. Get The AI Agent Builder Playbook · $197 →
What you'll be able to do
What you'll be able to do after reading AI Agent Builder.
Real outcomes, not "feelings of confidence."
Pick a stack (LangGraph / Pydantic AI / custom) for the right reason.
Run an eval-first workflow that catches regressions before customers do.
Design tools, memory, and state without the agent going off the rails.
Price an agent: per-call vs. seat vs. retainer, and when each works.
Run a demo with a non-technical CFO and walk out with budget.
Build observability so you can answer "why did it do that" in one click.
Ship MVP → first paying customer in 60 days without quitting your day job.
Decide between productized SaaS and managed-service models.
Templates included
12 templates you can use Monday.
Every playbook ships with copy-paste templates, scripts, contracts, sequences, calculators. All editable, all yours.
Eval harness starter kit
pytest + LangChain evals scaffolding. Real assertions, not vibes.
Agent system prompt scaffold
The skeleton we use for every new agent.
Tool spec template
JSON schema + plain-English description. Used by all major models.
Memory + state design doc
Decision tree for short-term, long-term, working memory.
Pricing calculator
Per-call vs. seat vs. retainer model spreadsheet.
Demo script for non-technical buyers
Open with the pain. Close with the math.
Pilot SOW
2-week paid pilot scope with renewal terms baked in.
Observability checklist
What to log, where, with what cost guardrails.
Customer success playbook
Onboarding, status emails, escalation tree.
Trial-to-paid email sequence
5 emails over 14 days for self-serve agents.
Support SLAs that won't break you
24/72/business-hours by tier, with cost math.
Architecture diagrams (5)
Reference diagrams for common agent patterns.
The 90-day roadmap
Day 1 to first client, mapped.
The same roadmap our early-access buyers used. No vague "in a few months", actual checkpoints.
Day 1
Stack picked, eval harness running
Local dev env, eval harness, one toy agent ships end-to-end.
Day 30
First productized agent (MVP)
Single-use agent that solves a real job, deployed, demo-able.
Day 60
First paying customer
Either pilot at $2k+ or self-serve trials converting.
Day 90
First $5k month
Three customers + a clear upgrade path. Pricing tested twice.
Why this actually works
Three reasons it lands.
Battle-tested.
Every prompt was used in real campaigns, client projects, or money-on-the-line situations before it made the cut.
Specific, not generic.
Each prompt solves one exact problem. Not “be more productive.” Not “improve your marketing.” Specific job, specific output.
Built to outlast model upgrades.
Works on Claude, ChatGPT, Gemini, Grok. The prompts are built around clear thinking, not model-specific tricks.
Pre-launch operators got Promptos free in exchange for honest feedback. 1,407 reviews. The critical ones are still up.
Early access reviews
What buyers said.
4.5
75 early-access reviews
5★52
4★14
3★7
2★2
1★0
CB
Charles B.
Philadelphia, PA · Founding engineer, AI startup
6 weeks ago
This is what good prompts look like
What I appreciated: it's not "manifesting your future business." It's operator content. the eval harness starter is the kind of thing you can implement Tuesday. the trial-to-paid sequence is genuinely the cleanest treatment of the topic I've seen. Worth more than the price.
HW
Hugo W.
Tampa, FL · Senior engineer, ML
6 weeks ago
Useful. At a discount it's a five
the trial-to-paid sequence is the best part. Some chapters felt aimed at people further along than me. I'm at zero, and a few sections assumed I already had a network. Still glad I bought it.
AK
Aurora K.
Chicago, IL · AI platform engineer
5 weeks ago
Real prompts, real outputs
As a senior engineer, ml, I'd been stuck on positioning for half a year. the trial-to-paid sequence unstuck me in an evening. What I appreciated: it's not "manifesting your future business." It's operator content. the demo script for CFOs is the kind of thing you can implement Tuesday.
AD
Akira D.
San Francisco, CA · Founding engineer, AI startup
7 weeks ago
Replaced a half-dozen scratchpad prompts
What I appreciated: it's not "manifesting your future business." It's operator content. the eval harness starter is the kind of thing you can implement Tuesday. Read it in one weekend, started implementing Monday. As a ai product engineer, the trial-to-paid sequence alone justified the buy.
PR
Priya R.
Boulder, CO · Staff engineer, autonomous agents
Feb 22
The bundle math is silly
Not theory. The chapters read like an operator handing you their actual notes. the trial-to-paid sequence in particular has the kind of detail you can't fake. the demo script for CFOs is genuinely the cleanest treatment of the topic I've seen. Worth more than the price. Read it in one weekend, started implementing Monday. As a senior engineer, ml, the tool spec template alone justified the buy.
MK
Mason K.
Phoenix, AZ · Solo agent builder
Jan 29
Best money I've spent on AI tooling all year
the eval harness starter alone saved me three months of trial and error. The kind of detail you only get from someone who actually ran the playbook. The 90-day roadmap is the part that doesn't show up in the marketing but is the most useful thing in the playbook. Combined with chapter 4 on the eval-first workflow, it's basically a quarter's worth of planning done for you.
CK
Charlotte K.
Miami, FL · Founding engineer, AI startup
Feb 17
The bundle math is silly
Better than three courses I've bought combined. the demo script for CFOs is the one I keep going back to. What I appreciated: it's not "manifesting your future business." It's operator content. the agent system prompt scaffold is the kind of thing you can implement Tuesday.
HV
Harper V.
Denver, CO · Solo agent builder
7 weeks ago
Good in places, uneven in others
Substantive playbook with real frameworks, but parts of it (specifically chapters 8 and 11) felt like they could stand to be deeper. the eval harness starter was great though. the eval harness starter is the best part. Some chapters felt aimed at people further along than me. I'm at zero, and a few sections assumed I already had a network. Still glad I bought it.
JD
Jules D.
Boulder, CO · Staff engineer, autonomous agents
Mar 26
Worth it on day one
the tool spec template is genuinely the cleanest treatment of the topic I've seen. Worth more than the price. Better than three courses I've bought combined. the tool spec template is the one I keep going back to. Not theory. The chapters read like an operator handing you their actual notes. the trial-to-paid sequence in particular has the kind of detail you can't fake.
PR
Penelope R.
Melbourne, AU · Senior engineer, ML
Jan 17
Real prompts, real outputs
As a solo agent builder, I'd been stuck on positioning for half a year. the eval harness starter unstuck me in an evening. the agent system prompt scaffold is genuinely the cleanest treatment of the topic I've seen. Worth more than the price.
LF
Lucas F.
Zürich, CH · Engineering lead, AI
Mar 5
The tool spec template saved me a meeting
The 90-day roadmap is the part that doesn't show up in the marketing but is the most useful thing in the playbook. Combined with the agent system prompt scaffold, it's basically a quarter's worth of planning done for you. As a ai product engineer, I'd been stuck on positioning for half a year. the demo script for CFOs unstuck me in an evening. chapter 4 on the eval-first workflow is worth the price by itself. Walked into a discovery call the next week and closed.
AS
Adrian S.
Brooklyn, NY · Indie agent builder
Feb 25
Almost a 5
chapter 4 on the eval-first workflow is the chapter I'll re-read. Wish there were video walkthroughs to go with the PDFs. The templates are detailed enough that a 5-min demo each would help. Solid playbook. the agent system prompt scaffold is the standout. The pricing chapter could be a little more aggressive: I think readers can charge more than the suggested ranges.
CN
Caroline N.
San Diego, CA · AI platform engineer
Jan 25
Worth it on day one
chapter 4 on the eval-first workflow alone saved me three months of trial and error. The kind of detail you only get from someone who actually ran the playbook. As a ai product engineer, I'd been stuck on positioning for half a year. chapter 4 on the eval-first workflow unstuck me in an evening. What I appreciated: it's not "manifesting your future business." It's operator content. the demo script for CFOs is the kind of thing you can implement Tuesday.
OT
Owen T.
Calgary, AB · Senior engineer, ML
Apr 2
Worth it on day one
As a indie agent builder, I'd been stuck on positioning for half a year. the tool spec template unstuck me in an evening. Read it in one weekend, started implementing Monday. As a solo agent builder, the agent system prompt scaffold alone justified the buy.
KB
Kai B.
Pittsburgh, PA · Engineering lead, AI
Mar 22
Real prompts, real outputs
the agent system prompt scaffold hit harder than I expected. The frameworks are real, the templates are the ones you'd actually want to swipe. the eval harness starter is worth the price by itself. Walked into a discovery call the next week and closed.
SE
Stella E.
Seattle, WA · Engineering lead, AI
Feb 3
The eval harness starter alone is worth the price
Not theory. The chapters read like an operator handing you their actual notes. the eval harness starter in particular has the kind of detail you can't fake. What I appreciated: it's not "manifesting your future business." It's operator content. the agent system prompt scaffold is the kind of thing you can implement Tuesday. As a engineering lead, ai, I'd been stuck on positioning for half a year. the agent system prompt scaffold unstuck me in an evening.
KL
Kai L.
San Francisco, CA · AI product engineer
Mar 25
Better than three of the courses I've bought
As a solo agent builder, I'd been stuck on positioning for half a year. the tool spec template unstuck me in an evening. the agent system prompt scaffold alone saved me three months of trial and error. The kind of detail you only get from someone who actually ran the playbook.
SH
Soren H.
Brooklyn, NY · AI platform engineer
Jan 30
Strong pack, minor nits
chapter 4 on the eval-first workflow is great. Two chapters felt slightly thin compared to the rest, but the templates included make up for it. the trial-to-paid sequence is the chapter I'll re-read. Wish there were video walkthroughs to go with the PDFs. The templates are detailed enough that a 5-min demo each would help.
LW
Luke W.
Berlin, DE · Senior engineer, ML
Jan 22
Great content, would love a Notion mirror
Excellent overall. the eval harness starter alone earned the price. I'd love more case studies. The playbook is heavy on frameworks and lighter on stories. Solid playbook. the agent system prompt scaffold is the standout. The pricing chapter could be a little more aggressive: I think readers can charge more than the suggested ranges. As a engineering lead, ai, most chapters were directly applicable. the agent system prompt scaffold was particularly strong. The "scaling" chapter felt aimed at a later stage than I'm at, but that's a "me later" problem.
SN
Savannah N.
Charleston, SC · Staff engineer, autonomous agents
Jan 28
Replaced a half-dozen scratchpad prompts
Read it in one weekend, started implementing Monday. As a senior engineer, ml, the tool spec template alone justified the buy. the agent system prompt scaffold hit harder than I expected. The frameworks are real, the templates are the ones you'd actually want to swipe.
The guarantee
If it isn't worth it in 30 days, get your money back.
One sentence in an email. No screenshots, no exit interview. We'd rather refund 10% of buyers than keep one frustrated. Most days, that math works in our favour.
30-day money-back guaranteeCross-sell
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