AI buyer's guides
Guides for the decision before the build
Ten guides for the work that happens before a contract or a commit: evaluating a partner, comparing a tool, deciding what to build in-house, and operating inside regulation. Each one is written from the position of a company that runs its own AI products in production rather than advising on them from a distance.
Choosing a partner
Three guides for the evaluation that happens before a contract: what to ask, what to verify, and what the failure modes look like when a firm cannot deliver.
How to Choose an AI Consulting Partner
What to check before hiring a firm for strategy, architecture, or governance, and how to tell genuine AI infrastructure from a rebrand.
How to Choose an AI Development Partner
How to separate a build partner from a staff-augmentation shop, compare engagement models, and judge what happens after delivery.
How to Choose a Generative AI Partner
How to verify LLM, retrieval, and agent depth against production claims, and how to read reviews that were written by the firm.
Choosing a tool or an approach
Guides for the decision after that: which tool to buy, and which parts of the stack are worth building in-house.
How to Choose a Code Review Tool
How to compare review tools on coverage, automation depth, integration, and pricing, and how to test one against your own repository.
Governed AI vs AI Consultancy
Where a consultancy engagement stops and a governed build starts, across the seven dimensions that decide it, plus five questions to ask any supplier before signing.
Build vs Buy Agentic AI
How to decide what to build in-house and what to buy, with the real first-year costs, the framework tradeoffs, and the governance you cannot skip.
Agentic AI vs Generative AI
How to tell the two apart when vendors sell them in the same sentence, the test that settles which one your project needs, and what each costs when you guess wrong.
Vibe Coding Tools
The three kinds of tool sold under one label, the four questions that decide which belongs on your team, and where the tool stops being the constraint.
AI Code Review vs SonarQube
Rules vs judgment: what a scanner and an agent each see, what SonarQube is in 2026, where each wins, and why most teams run both.
Deploying AI in your environment
Guides for the constraints your environment imposes: regulation, existing systems, and the controls that decide whether AI reaches production at all.
Questions about the guides
How the cluster is written, how current it is, and where to start.
Which guide should I start with?
It depends on the decision in front of you. Choosing who to work with is the consulting, development, and generative AI guides. Choosing a tool is how to choose a code review tool. Deciding what to build in-house is build vs buy. Telling agentic from generative is agentic AI vs generative AI. Choosing an AI coding tool is vibe coding tools. Separating a scanner from an agent is AI code review vs SonarQube. Working inside regulation is AI in regulated industries.
Are these guides independent?
No, and each one says so. They are written by FLYTEBIT, which sells the services they describe. The frameworks are the ones we use with clients, and the vendor-evaluation questions are written so you can put them to us as easily as to anyone else on your shortlist.
How current are the guides?
Each carries a last-updated date, and we revisit them when the underlying facts move, which for these topics means pricing, regulation, and the platforms a buyer is choosing between.
Do the guides cover pricing?
They cover the shapes rather than a rate card: staff augmentation, fixed-scope projects, product-first consulting, and full transformation, with what each one shifts onto you. Our own figures are published too, starting with a feasibility study from $2K, a 2 to 4 week timeline, and 4 to 6 hours of your team's time.
Can we use the frameworks with a different vendor?
Yes. They are evaluation frameworks rather than product pitches, and they work on any shortlist. The comparison tables and red-flag lists are the parts clients use most, including when the shortlist does not include us.
What if none of the guides fits?
Book a and we will look at the decision you are actually facing rather than the one the guides cover. If it falls outside what we do, we will say so rather than stretching a scope to fit.
Not sure which decision you are facing?
Most engagements start with a feasibility study: we examine the workflow, the constraints, the data, and the failure modes, then give you a Go or No-Go verdict. Starting from $2K, with a 2 to 4 week timeline and 4 to 6 hours of your team's time.