the output is yours. regardless of who helped create it.
that’s the core of diligence. not a checkbox. not a disclaimer. a genuine commitment to owning what you produce — even when AI did significant work to get there.
three dimensions of diligence#
creation diligence — be thoughtful about which AI you use
not all AI systems are equal. before you work with one, consider:
- how was it built and trained?
- what data are you sharing with it?
- does it align with your organisation’s security and privacy policies?
for Security analysts — sharing sensitive incident data with an unchecked external AI tool is a security risk. know your platform before you use it.
transparency diligence — be honest about AI’s role
different contexts have different expectations. academic work, professional reports, client communications — each has its own standards for disclosure.
the question isn’t just “should i disclose?” it’s “who needs to know, and how much detail do they need?”
a simple diligence statement goes a long way: “this report was drafted with AI assistance. all content has been reviewed and verified. i take full responsibility for its accuracy.”
deployment diligence — verify before you share
before any AI-assisted output leaves your hands:
- verify key facts independently
- check for bias or gaps in the analysis
- ensure it meets the required standard for its purpose
- confirm you can stand behind every claim in it
if you wouldn’t be comfortable defending it without the AI output to reference — it’s not ready.
the 4Ds as a complete system#
this is where it all connects.
- delegation — you decide what AI handles
- description — you communicate clearly
- discernment — you evaluate critically
- diligence — you take responsibility for what goes out
none of these work in isolation. fluency is applying all four together, consistently, across every meaningful AI interaction.
the goal isn’t perfection. it’s intention. deliberate, thoughtful human-AI collaboration that produces better outcomes than either could achieve alone.
for Security analysts specifically#
the stakes are real. investigations inform decisions. reports shape responses. incorrect outputs don’t just waste time — they can misdirect an entire incident response.
AI fluency in a SOC context means:
- delegating intelligently based on task risk
- describing with enough precision that output is actually usable
- discerning with the skepticism you’d apply to any unverified source
- taking full ownership of everything that carries your name
that’s the series. six posts. from what AI fluency means to how all four competencies work together.
the cheat sheet is below — bookmark it. every term from the framework in one place.
how are you currently doing on diligence — creation, transparency, or deployment? which one needs the most attention?
took ai help to clean up typos. my brain works faster than my fingers. xd
