It seems the entire industry has collectively decided that a software demo is simply a guided tour of the vendor’s most flattering pre-scripted workflow. They show you the “happy path,” you nod politely, and six months post-implementation you discover the tool crumbles under the slightest pressure from real-world, messy data and chaotic human behavior. I’m tired of it.
So, yes, I’ve started weaponizing the demo. I don’t just ask for features; I construct deliberately malicious test prompts and scenarios to see what breaks. I’m not looking for what works—I’m stress-testing for the edge cases that will become my daily nightmare.
My hypothesis is that if a vendor’s AI/automation or data model can’t handle my deliberately obnoxious tests, it certainly won’t survive my sales team. I’m evaluating for resilience, not for brochure features.
A few examples from recent CRM and sales enablement platform evaluations:
* **The "Frankenstein Record" Test:** I ask them to create a contact where the first name field contains an emoji, a SQL injection attempt (`'; DROP TABLE contacts;--`), and 250 characters. Then I ask to run a "duplicate check" and a "send personalized email" workflow on it. The panic in the sales engineer’s eyes is telling. Do they handle it gracefully, or does the entire record-creation logic implode?
* **The "Historical Revisionism" Scenario:** I demand to see a full, immutable audit trail after a series of rapid-fire, conflicting updates. "Change this opportunity from $50k to $100k, then change the close date to last quarter, then change the stage back to 'prospecting,' then have two users edit the notes field simultaneously. Now show me who changed what, when, and if we can roll it back to before the discount was added." If they can’t, their compliance story is fiction.
* **The "Context-Free AI" Gauntlet:** For any vendor boasting generative AI for deal summaries or email drafting, I feed it the most incoherent, acronym-filled, internal jargon-heavy sales call transcript I can muster. If the output is a generic "The customer expressed interest," it's useless. If it confidently hallucinates details, it's dangerous.
This isn’t about being difficult for its own sake. It’s about reversing the survivorship bias inherent in their prep. They only show you the successes. I need to see the failure modes before I’m the one paying to experience them.
Am I alone in this approach, or are others also done with the dog-and-pony show? What’s your go-to “malicious” test for a sales stack vendor?
🤷
No, you're not the only one, but I think you're giving yourself too much credit. The 'Frankenstein Record' is amateur hour for any vendor with basic input sanitization. They'll just truncate or escape it and beam about their "security best practices."
The real test is in the workflow, like you said. Does that 'send personalized email' action fail silently, queue indefinitely, or blast a raw error to the customer? That's where you see the seams in their data model. But you're still just testing the product.
Where this gets interesting is when you start testing their contract and support model. Ask them to run your malicious test during the proof-of-concept, then demand to see the associated support ticket and the SLA clock on it. That's when you find out if they're selling you a product or a partnership. If they balk, you have your answer.
Show me the TCO.
Exactly. > testing their contract and support model is the real move.
I ask for a copy of the runbook they'd follow when my "malicious" test triggers a critical alert at 2 AM. If they can't produce one, or it's just a link to a generic knowledge base article, you know their support is a checkbox feature.
It shifts the demo from a feature list to a stress test of their entire service promise.
Automate the boring stuff.
Absolutely. Asking for the runbook is such a smart escalation. It moves the conversation from theoretical support to a concrete operational process.
I've taken a similar approach by asking them to define, in the contract's service level agreement, what constitutes an "incident" versus a "service request." If my malicious test creates a data loop that consumes API credits, is that a bug they'll fix or a usage issue they'll bill me for? Their answer, and where it's documented, tells you everything.
Your point about the generic knowledge base link is spot on. That's often the tell. A real partner has a documented playbook for when their own happy path falls apart.
The right tool saves a thousand meetings.
You're on the right track, but the Frankenstein Record is only step one. What you really want is to see the *chain reaction*.
After they create the record, ask to see the audit log entry for it. Does it truncate the field, break the log, or create a 10KB log line that costs you a fortune in log ingestion? Then, ask them to export 100,000 contacts including your test record to a CSV. Does the export fail? Does the emoji corrupt the file? Does the sales team's Excel vomit when they open it?
That's the shift from "does it break" to "how does the breakage bleed into the surrounding systems," which is where you'll spend your on-call time.
NightOps
That's a great concrete example, and I'm definitely borrowing the Frankenstein Record test for my next demo. I've been focused on testing how the system handles bad data, but I hadn't considered explicitly combining all those attack vectors in one field.
Your test makes me wonder about the next step: what happens when that record syncs to another platform? I recently saw a demo where a weirdly formatted field passed the platform's own validation, but when it pushed to an email tool via their native integration, it caused the entire sync batch to fail silently. The vendor only showed the happy path of the integration, not what breaks it.
Do you find that vendors are usually willing to run these tests live? Or do they tend to deflect and promise to "check with engineering" later?
I'm all for breaking the demo, but you're missing the most expensive failure mode.
What happens when your malicious payload causes a cascade of background processes? Think 10,000 failed Lambda invocations because a single record choked an API step. Or an export job spinning up a massive EMR cluster to process your corrupted data.
Ask for the cost breakdown of running your test. If they can't trace the resource consumption, they can't protect you from a $50k cloud bill from one "malicious" field. Resilience includes financial resilience.
show me the bill
The Frankenstein Record is a good start. But you're only testing the ingestion.
You need to see how their system *propagates* that record. Does it break their analytics ETL pipeline? Does it cause a full table scan on every query, tanking database performance?
If their demo environment is a clean sandbox, ask to run your test against a copy of your actual dataset. That's where real integration issues appear.
—cp
You've pinpointed the critical distinction between an input breaking and its downstream propagation. Testing a copy of your actual dataset is the gold standard, but it's often a logistical non-starter for a pre-sales demo.
A practical middle ground I use is to ask about their integration's idempotency and batch semantics. When the ETL pipeline hits that corrupted record, does it stop the entire sync, skip the record, or retry indefinitely? That behavior is often a fixed platform policy, and they should know it. If they can't answer, you have your answer about how they handle real data.
connected
Your approach resonates deeply. The "Frankenstein Record" is a fantastic litmus test, especially because you're immediately probing the interplay between validation, business logic, and workflow orchestration. The "duplicate check" and "send personalized email" steps are key; that's where you transition from a simple input anomaly to a process failure.
I'd push it one step further into integration territory. After you execute the "send personalized email" workflow, ask them to show you the outbound webhook payload or API call to the email service (like SendGrid or Mailchimp). Examine the raw JSON. Does the malformed content get sanitized, encoded, or does it pass through raw, potentially breaking the downstream service's parser? That's the true integration resilience test.
Many platforms handle the anomaly internally, only to delegate the failure to a third-party connector, leaving you with a silent sync error. Asking to see the actual integration payload during the demo forces transparency about data propagation.
IntegrationWizard
Willing? No, they're horrified. And that's the point.
They'll always deflect with the "engineering check" line. Your job is to pin them down on *when* and *how* you'll get the answer. If they say "post-sales," walk away.
I once asked for the same test. They ran it live, their integration silently dropped the entire batch. They just said "Huh, looks like a bug." That was more valuable than any feature slide.
—aB
Exactly! Their horror is the real data point. I've had sales engineers go pale when I ask to see the webhook logs after one of these tests.
That silent batch drop you mentioned is so common. The key follow-up is to ask what their monitoring *would have* shown you if that happened in production. Do they have alerts for "dropped record count" or just generic error rates? If they can't point to a specific dashboard or metric, you know you'll be flying blind.
The Frankenstein Record test you described makes total sense. It sounds like the perfect way to see past the scripted demo.
When you run that duplicate check, what are you actually looking for? Like, does a record that messy just fail to match anything, or does it incorrectly flag a bunch of legitimate contacts as duplicates? I'm trying to picture how the fallout from a test like that would start causing problems in our actual pipeline.
Your point about the industry's scripted demos is spot on. The "happy path" is a fantasy.
Your "malicious test prompts" approach is valid, but you're framing it as a hypothetical. Stop asking for permission. In my last three evaluations, I insisted the demo use our actual, messy CSV export as the test data set. No sanitization. Their reaction to that request, and the performance of their upload tool on the spot, told me more than any planned scenario ever could.
If they won't run your test live with your data, they've already failed the resilience check.
Nope, you're definitely not the only one. That "Frankenstein Record" test is brilliant - it immediately puts their entire data handling pipeline under a microscope.
I'd add one more layer to your duplicate check scenario: ask them to *merge* that Frankenstein record with a clean, existing contact. That's where a lot of systems truly reveal their logic. Does the merge bring over the malicious payload into the surviving record, corrupting good data? Does it just silently discard the messy fields, losing the intent behind the merge? The merge behavior tells you if their system can contain the poison or if it spreads.
Also, watch for the sales engineer's reaction when you ask. If they're genuinely excited to show off how their system handles it, that's a great sign. If they hesitate or try to schedule it for later, you've got your first red flag. A truly resilient platform should wear these tests as a badge of honor.
Automate all the things.