The ToolNest Blog — Playbooks & the Bootcamp
Two series share this journal. Playbooks are practical, numbers-first guides for the situations the site's calculators were built for — setting payment terms, finding a break-even point, dividing a small ad budget — each with a worked example end to end and the tools linked inline.
AI Agent Bootcamp is a 180-day bootcamp on AI agent engineering, published one article per day: what to learn, why it matters, a hands-on task with a verifiable output, and the interview questions that topic invites. The path in one line: Python and the LLM API, tool calling, RAG, graph-based agents, memory, evaluation, observability, safety, production.
Every article follows the same shape, because predictability is what makes a series usable. A short answer states the core idea in one paragraph. The middle sections explain the concepts, walk a worked example and name the mistakes almost everyone makes. Figures and examples keep to tools that run in the browser, and the ToolNest tools are linked wherever a lesson uses them.
Playbooks
What mutual versus one-way agreements should cover, the clauses that do real work, and the situations where signing one is a mistake instead of a protection.
Carriers bill space, not weight. Dimensional weight, freight class and pallet math explained with worked numbers, plus the packing fixes that cut quotes.
Salary is one line of an offer. Compare hourly, salaried and 1099 offers on what matters: PTO-adjusted value, benefits worth, overtime eligibility and the tax gap.
The 28/36 rule worked on a real salary: housing ratio, debt ratio, down-payment effects, and the closing-cost and property-tax lines buyers forget to include.
What to put in a refund and return policy so customers self-select honestly: time windows, condition rules, who pays return shipping, and the chargeback math.
Turn a target annual salary into an hourly and daily freelance rate: billable-hours reality, overhead, taxes, and the sanity check most freelancers skip.
A weekly framework for a $1,000 monthly ad budget: how much to reserve for testing, which metrics to read before scaling, and when to move money between campaigns.
The break-even formula worked end to end on a realistic small business: fixed costs, contribution margin, and the three mistakes that make the answer useless.
Net 30, 2/10 net 30, deposits and milestones compared, with the cash-flow math for each option and a payment-terms clause you can paste into your next invoice.
Month 1 · LLM Applications
How text becomes vectors, why cosine similarity measures meaning, a twenty-line sanity check for an embedding model, and the selection criteria that matter.
What a token really is, why Chinese costs more, how context windows overflow and what to do about it, and the arithmetic that prices an API call before you run it.
Day 1 of a public AI Agent Engineer bootcamp: what the job actually is, the six layers of an agent system, and a working Python lab with your first LLM API call.
Frequently asked questions
- What is the Playbooks series?
- Practical, numbers-first guides for the people the calculators are built for: which payment terms to put on an invoice, how to find a break-even point, how to divide a small ad budget. Every playbook walks a worked example end to end and links the on-site tools that repeat the arithmetic.
- What is the AI Agent Bootcamp?
- A public learning journal on AI agent engineering, published one article at a time: the concepts, a hands-on task with a verifiable output, the common mistakes, and the interview questions each topic invites. The path runs from the first LLM API call through tool calling, RAG and evaluation to production concerns.
- Do the bootcamp days need to be read in order?
- The sequence is deliberate — tool calling before frameworks, retrieval before agents, evaluation before production — so reading in order builds the strongest foundation. Each article still stands alone well enough to be useful if you jump straight to a topic you need right now.
- How is the blog different from the guides?
- Guides are evergreen references behind the site's calculators — rules, rates and formulas. The blog is scenario-driven: playbooks make the actual calls the calculators support, and the bootcamp is a separate series about building AI systems, linked to the developer tools it uses.