AI will give you a confident answer whether it’s right or wrong. that’s the problem.
there’s no hesitation. no “i’m not sure about this.” just a well-structured, fluent, convincing response — that may or may not be accurate. discernment is the competency that stops you from treating confident-sounding output as correct output.
in SOC work, this isn’t a minor inconvenience. a wrong answer about a threat actor, a misattributed CVE, a hallucinated IOC in an investigation report — these have real consequences.
what discernment actually is#
discernment is the ability to thoughtfully evaluate what AI produces, how it produced it, and how it behaved during the process.
it’s the flip side of description. description shapes what goes in. discernment evaluates what comes out.
and just like description, it has three dimensions.
product discernment — evaluate the output itself#
the most obvious layer. look at what AI actually produced and ask:
- is this accurate? can i verify the key claims?
- is it appropriate for the audience and context?
- is it coherent? does the logic hold together?
- is it relevant to what i actually asked?
- what’s missing that should be there?
for Security analysts — your domain expertise is your primary discernment tool here. you know what a good investigation summary looks like. you know when a threat description doesn’t match what you’ve seen in the environment. trust that knowledge.
the dangerous moment is when you’re evaluating output in a domain where you have less expertise. that’s when confident-sounding wrong answers slip through. slow down in those moments.
process discernment — evaluate how AI got there#
not just what AI produced, but how it arrived at it. the reasoning path matters.
look for:
- logical errors or jumps in reasoning
- gaps in analysis — what did AI overlook or ignore?
- inappropriate reasoning steps — did it make assumptions it shouldn’t have?
- whether it considered multiple possibilities or locked onto one early
SOC example — you ask AI to assess whether a series of events constitutes lateral movement. it says yes. product discernment checks the conclusion. process discernment asks — did it consider the legitimate admin activity baseline? did it account for the scheduled task that runs at that time? did it look at the full sequence or just the flagged events?
the conclusion might be right. the reasoning might still be flawed. both matter.
performance discernment — evaluate how AI behaved#
the most overlooked dimension. was AI’s behavior during the interaction actually helpful?
consider:
- did it stay focused on your actual question or drift?
- was the communication style appropriate for your needs?
- did it ask clarifying questions when it should have?
- did it push back when something didn’t add up — or just agree?
- was it concise when you needed concise, detailed when you needed detail?
this matters because performance issues compound across a long conversation. an AI that agrees with everything you say isn’t a thinking partner — it’s an echo chamber. an AI that stays vague when you need precision is wasting your time.
if the behavior isn’t serving you — name it and redirect. “you’re being too generic, i need specific examples” is a valid performance discernment response.
the description-discernment loop#
these two competencies work together continuously.
you describe → AI produces → you discern → you refine your description → AI produces again → you discern again.
this loop is how good collaborative work actually happens. not one perfect prompt and one perfect output. iterative cycles where each round gets closer to what you need.
the loop also means discernment isn’t just evaluation — it’s input for the next description. what you notice in the output shapes how you communicate next.
a practical discernment habit for SOC work#
before using any AI output in an investigation or report, ask three questions:
- can i verify the key facts independently?
- does the reasoning hold up against what i know about this environment?
- would i be comfortable explaining this conclusion without the AI output to back me up?
if the answer to any of these is no — the output needs more work before it goes anywhere.
next up — diligence. the competency that asks not just “is this good?” but “am i using this responsibly?”
what’s the most dangerous type of AI error in your SOC context — wrong facts, flawed reasoning, or misaligned behavior?
took ai help to clean up typos. my brain works faster than my fingers. xd
next up: AI Series #23 — “accountability doesn’t disappear when AI helps you” AI Fluency Cheat Sheet back to series index
