The Workflow Decision Lab
Everyone's selling you AI tools. We tell you which ones to skip and where they fail.
We test the AI and software then publish the receipts — what actually works, what it really costs, and when the right move is to buy nothing.
Get the next verdict before it's everywhere.
One email when a new lab post or cost table ships. No spam, no confirmation step — unsubscribe anytime.
Why it exists
Too many tools. Too little decision confidence.
Most software advice is written by the vendor. Every guide here is structured so you can make the call yourself, with costs, failure modes and a measurable test.
Decision Guides
One tool problem, researched properly: what actually works, what it costs, where it fails, and when to do nothing.
- Named scenario, direct verdict up front
- Real pricing, with receipts or marked unverified
- Failure modes you won't find in vendor demos
From the Lab
Built from our own runs, benchmarks and post-mortems. Each one ends with a verdict you can act on.
agent-reliability · workflow-decision-lab
Agent Memory Needs Typed Claims, Routing, and Maintenance
A three-month GBrain + Hermes run: why raw transcripts are not memory, and the typed-substrate, routing, and maintenance loop that made durable recall inspectable.
Aug 21, 2026
agent-reliability · workflow-decision-lab
Your AI Ops Bot Is Not Your Co-Founder: Guardrails First
Letting an agent touch production needs blast-radius limits, not trust. The guardrails to set first, the failure modes they stop, and where to keep a human.
Aug 21, 2026
local-llm-inference · workflow-decision-lab
LLM Fine-Tuning: Your Dataset Is the Hard Part, Not the Run
For an internal smart-contract audit SFT lane, hold the run until the dataset passes dedup, leakage, grounding, negative-coverage, and truncation gates.
Aug 21, 2026
What we actually do
No listicles. No affiliate links. Just receipts.
We run the tool on our own stack, measure what it costs and where it breaks, then hand you the decision, not the sales pitch.
- 1
Pick the real decision
A named scenario: who you are, what you're trying to do, and the constraint that actually matters.
- 2
Test it with our money
Real runs, real pricing, real failure modes. If a number isn't sourced, it's marked unverified, never invented.
- 3
Ship the verdict + the keep-or-drop rule
A clear keep / skip / do-nothing call, and the small experiment that confirms it for your situation.
- Every claim
- has a receipt or says so
- Keep-or-drop
- rule on every guide
- 0
- vendor-written articles
Frequently asked questions
Is this affiliated with any of the tools I'll be considered?
No. Nothing here is sponsored or written by a vendor. Every cost figure is either sourced with a receipt or explicitly marked as unverified — and the honest answer is sometimes 'don't buy anything yet.'
Who is this actually for?
Owners and operators of small businesses (home services, e-commerce, agencies, bookkeeping, local retail) who are being pitched software and AI tools and want a second opinion that isn't trying to sell you something.
Why a keep-or-drop rule instead of 'buy or don't buy'?
Because most tools are a fit question, not a quality question. Every guide ends with the metrics to watch and the rule for keeping it, instead of a verdict with no conditions.
How do you keep this from going stale?
Pricing and capabilities change, so every cost figure carries the date it was captured and a link to the source it came from. When an article is re-checked, it gets an "Updated" date and the correction is made in place rather than quietly republished.
Start here
Send us the decision you're sitting on
Name the tool, the business, and what you've tried. If it's worth a Decision Lab piece, it moves up the list, and you'll get the verdict when it ships.