Guides
Guides
Find practical guides with worked examples, help using our products, and engineering notes from experiments we have run. The labels distinguish instructions from product documentation and dated observations.
Browse a topic below, find a product and watch its demo, or compare prices. Each article links relevant tools or further reading where useful.
27 articles in 4 topics, by Steven Michael Barber.
Radiation safety math
Understand gamma-source units, dose rate, distance, shielding and decay through worked examples. These are educational estimates, not operational safety decisions.
Radiation units explained: Sv vs rem, Gy vs rad, Bq vs Ci
Practical guide
What activity, absorbed dose and equivalent dose each measure, the exact SI and traditional unit conversions, and where the roentgen and weighting factors fit.
Gamma dose rate, distance and shielding
Practical guide
How the point-source formula, the inverse-square law and half-value layers of lead, steel and concrete set the dose rate from a gamma source, worked out.
Distance is the cheapest shield: the inverse-square law in practice
Practical guide
Use inverse-square estimates to compare distance and shielding, understand model limits and distinguish calculated contours from surveyed boundaries.
Half-value layers compared: lead, steel and concrete for Cs-137, Co-60 and Ir-192
Practical guide
Half-value and tenth-value layers of lead, steel and concrete for the common industrial gamma sources, by thickness and by weight, with a worked shield.
Stay time and dose budgets: working from dose rate and time
Practical guide
Work through illustrative dose budgets and rate-times-time examples, with federal limits and the measurements and procedures that govern real work.
Radioactive decay and half-life
Practical guide
The decay law in plain terms: how to work out the activity left after a given time, how long a source takes to fall to a given level, and the mistakes to avoid.
Portable nuclear gauges explained: the sources inside, the leak test and the license
Practical guide
What is inside a moisture-density gauge, how it measures, how its cesium and americium sources age, and the dated duties of the license and every trip to a job.
Personal and small-business costs
Work out machine, labor and job costs, or forecast your personal cash flow before payday.
Labor burden: what an employee hour really costs
Practical guide
The payroll taxes, insurance and benefits on top of a wage, built line by line for one worker's year, and why to estimate with the cost per productive hour.
Forecasting your cash flow before payday
Practical guide
Build a running daily balance from your bills and paychecks, find the lowest day before it arrives, and keep recurring dates and a cushion right.
Job costing for small trades
Practical guide
Price a job from labor with burden, materials, equipment hours, overhead and margin, and see why a 15 % markup is not a 15 % margin.
What a machine really costs per hour
Practical guide
Owning and operating cost per hour for a skid steer, loader or excavator: depreciation, interest, insurance, fuel and repairs, worked through for one machine.
Computing costs and local AI
Whether renting out a GPU or server pays, running AI models on hardware you already own, and cutting what your build pipeline costs.
When trimming CI was not enough: moving the jobs to a desktop we already owned
Engineering note
Why more pipeline trims could not reach our GitHub Actions target, four paths compared on cash, and the two-hour setup of a self-hosted runner on a desktop.
How we audited GitHub Actions cost and run time
Engineering note
How we audited repeated CI work, separated waiting time from runner minutes and chose simpler checks with measurable trade-offs, with a worked example.
We split one AI model across two home computers. In our tests, it got slower
Engineering note
We split Llama 3.1 8B and 3.3 70B across a desktop and 2017 iMac over Wi-Fi. All splits generated text more slowly; bottleneck causes need more tests.
Our 2017 iMac couldn't run Ollama on macOS. On Linux it reached 70% of a modern desktop
Engineering note
In our October 2026 test, Ollama needed macOS 14; on Ubuntu, a 2017 iMac ran 3B and 8B models at about 70% of our Dell’s speed.
We built a private AI server without a dedicated GPU. Here's what our first benchmarks showed
Engineering note
Three local models on a Windows desktop with no dedicated graphics card, run with Ollama: 15.67, 7.67 and 4.26 tokens per second, and how we measured.
Utilization: the number that decides whether a rented GPU pays
Practical guide
What the share of rented hours does to one GPU's net income and payback, the three utilization thresholds that matter, and the payout trade-off.
Is renting out a spare GPU or CPU worth it?
Practical guide
How power draw, electricity price, utilization, payout and platform fees combine into net income per hour and a break-even date for a rented GPU or server.
Building software with AI agents
How we use two AI coding agents, capture decisions in QnA MD and connect assistants to our tools.
How we gave every app an MCP interface, and what an AI assistant can do with it
Product help
Why each of our apps has a Model Context Protocol server, how one is made from the app's own functions, a shielding question worked through it, and the rules.
Batch questions with QnA MD and the agentic development life cycle
Product help
How agents compile open questions into one QnA MD file, an owner answers them in one sitting, and the answers are applied and recorded before the next round.
How we first set up Claude and Codex in one repository
Engineering note
The first arrangement: Codex built, Claude reviewed, the owner merged, signed and deployed. Verification records, handoff reports and one merge queue.
QnA MD file format: tags, fields, statuses and log lines
Product help · Format reference
The QnA MD tag grammar (spec v0.1 draft): six item types, ids, fields, options and (rec), status values, log verbs, timestamps, escaping and our conventions.
QnA MD use cases: six ways to use a question file
Product help
Agent questions to an owner, approval chains and quorum decisions, an idea-to-brief interview, a skill brief, a team sign-off, and answering with no signal.
Two AI models, one repository: early speed and quality data
Engineering note
Measured results from the first 25 hours of Claude and Codex reviewing each other: pull requests, review findings and test counts. Early, thin data.
What we changed after a day of two-model development
Engineering note
The 2026-10-19 changes: approvals delegated to the other model, what the owner keeps, automation held to the same rules, and the build-review flip.
Why we built QnA MD: agent questions that outlive the chat
Product help
Why an AI agent's questions and decisions belong in a Markdown file as hidden HTML-comment tags: git-friendly, invisible when rendered, offline and phone-first.
Why we use two AI models to build and review each other's work
Engineering note
One model reviewing its own work misses things. We had Claude and Codex check each other's work and batched the owner's decisions to what matters.