I've sat through about 30 of these enterprise security reviews now. Here's exactly what makes security teams lose their shit:
The "Oh Fuck" Moments in Security Reviews
"Where the hell does our code actually go?" Most of these tools vacuum up your code and ship it to OpenAI, Anthropic, or whoever's cheapest that week. Your "proprietary algorithm" just became someone else's training data. Cursor sends your code to like three different AI providers - OpenAI, Anthropic, and I think Perplexity? They don't exactly advertise this shit, and good luck figuring out which provider gets which request. GitHub's own data handling docs are buried in enterprise legal speak, but basically: Microsoft gets your code.
I watched this CISO at a bank literally go white when they realized Cursor was routing their fraud detection code through three different AI providers. The silence lasted like 30 seconds before someone asked "which provider saw our transaction logic?" Nobody in the room knew. That pilot got killed before the meeting ended.
"Can we even audit this nightmare?" When AI-generated code takes down prod at 3am, good luck figuring out what happened. Amazon Q's CloudTrail integration is decent if you live in AWS, but most tools give you fuck-all for audit trails. Microsoft's compliance documentation for Copilot is thick as a phone book, but Cursor's security docs are basically "trust us, we're secure" with some privacy policy boilerplate.
Three weeks ago I'm sitting in this post-mortem, prod was down for 2 hours because of a parseInt() bug - no radix parameter, classic JS footgun. Nobody could figure out if our junior dev wrote it or if GitHub Copilot suggested it. The AI generates code that looks exactly like what a tired developer would write. We're still not sure who fucked up.
"What happens when the startup gets acquired?" Cursor sends code to multiple AI providers without telling you which one. Great until Anthropic or OpenAI changes their terms and suddenly your medical device code is training some random model. The AI provider ecosystem changes so fast that your tool today might use completely different models tomorrow.
Security teams don't reject AI tools because they hate productivity - they reject them because most tools are built like fucking consumer apps with enterprise pricing slapped on top. I've sat through these reviews - it's painful watching security tear apart tools that were clearly designed by people who've never worked at a company with more than 20 employees.
The Bill Shock Reality
The $20/month pricing is complete horseshit once you hit production scale. Here's what actually happens:
The governance theater tax: Companies I've worked with spend $150k-300k/year for compliance tooling nobody uses. Security demands audit logs, so you buy expensive SIEM integrations. Legal wants data classification, so you hire governance consultants to write policies everyone ignores.
I watched one company's legal team spend six weeks arguing about liability clauses while developers were already using ChatGPT for debugging. The horse was already out of the barn, but corporate was still arguing about the barn door.
Usage explosion: Teams I've seen went from a few thousand to $40-60k monthly when developers discovered the AI could refactor entire codebases. GitHub's enterprise pricing starts reasonable until you factor in premium request limits that get burned through in days.
One team burned through their monthly GitHub Copilot Chat quota in 8 days because someone asked it to refactor their entire Express.js 4.18.2 backend to TypeScript 5.1. $1,200 overage charge appeared on the Microsoft 365 bill with zero warning. CFO was not amused. This was August 2025 - GitHub's new quota system caps premium requests at 50/day for Business tier.
Tool chaos: Developers use whatever works - Copilot for autocomplete, ChatGPT for debugging, Claude for complex refactoring. Your "$20 per seat" becomes $100+ per seat across multiple vendors, each with different data handling policies.
What Survives Enterprise Politics
Microsoft shops just use Copilot because it inherits their existing nightmare of Azure AD integration and Microsoft 365 compliance frameworks. IT teams are already dealing with Microsoft's bullshit - adding one more product is easier than managing another vendor relationship. Plus Teams integration means developers can't escape it even if they want to.
AWS addicts pick Amazon Q because it understands their CloudFormation disasters and IAM permission hellscape. When your infrastructure is 90% AWS anyway, having an AI that suggests the right EC2 instance types beats generic code completion. The AWS CLI integration actually works, unlike most third-party tools that break every time AWS changes an API.
Paranoid enterprises pay 3x for Tabnine Enterprise because code never leaves their network. Higher cost, worse AI models, but it passes the "can we run this in our air-gapped environment?" test that regulated industries demand.
Nobody picks tools based on "best AI model." They pick whatever survives the procurement committee and doesn't get killed by security in week three.
Anyway, here's how these tools actually work in the real world instead of marketing fantasy land...
