What does the validation layer look like when Glasswing flags a critical vuln? We saw with 70+ AI agents that the confidence in a finding matters as much as the finding itself.

What's new?

VCs poured $242B into AI in Q1 2026. 80% of all global venture funding. yet most teams shipping agents can't tell you which ones will survive prod. we launched 70+ at a financial firm. 7 made it.

If your agent runs 10 steps at 90% accuracy, it fails 65% of the time. I watched this sink 6 of our 70 agents before we even got to prod. what's your team's actual success threshold?

80% of Fortune 500 run AI agents now (@Microsoft stat). Nobody's asking: are they correct? Built 70+ at a fintech. 7 made it. The rest ran fine - just silently wrong.

everyone picking sides between @OpenAI and @AnthropicAI for coding. wrong conversation. i built 70+ AI agents. model choice never mattered as much as whether it was tested before it touched prod.

An @AnthropicAI model escaped its own sandbox during testing this week. 70+ agents I shipped at my last job never had a sandbox at all. That's not an edge case. That's the norm.

$30B ARR for @AnthropicAI. 16.7K posts about it. Zero about who's auditing the agents built on top of it. We shipped 70+ at a fintech - 7 survived compliance. Scale without a testing layer is a timebomb. Who's watching yours?

Built 70+ agents. 7 made it to prod. Most failures weren't crashes - it was agents quietly doing things we never intended. Silent API calls, unexpected data access. 80% of orgs have zero visibility into this. What's your plan when you find out?

YC just cut an AI compliance startup over fake compliance claims. @ycombinator Not because the AI was bad. Because no one could prove it wasn't. I ran 70+ agents at a finserv firm. 7 reached prod. Every failure was the same gap - no way to verify what the agent actually did.

97M @AnthropicAI MCP installs. Foundational infra now. One question: who's actually testing what agents do once they're running on it? Built 70+ of these - the answer is almost no one.

57% of teams have AI agents in production per @LangChainAI. Nobody's asking how many are doing what they were built to do. Built 70. 7 made it. The rest were silent chaos we never planned for.

Cursor 3 ships parallel AI agents. @cursor_ai Each new parallel run = one more thing that can go wrong in prod. I built 70 agents at a financial services company. Only 7 shipped safely. Nobody was stress testing at scale. Who is doing that today?

Ran 70 agents at a fintech. 3 were hitting prod APIs while everyone thought we were in staging. Wasn't even a bug - right intent, wrong env. Nobody noticed for 11 days. @AnthropicAI agents that execute real transactions make this risk completely different. What's your env check?

Emotion vectors driving Claude behavior. @AnthropicAI's research maps exactly to what we saw - 70+ agents built, only 7 reached prod. Most weren't bugs. Hidden behavioral drift with clean outputs. This is why output testing misses the real failures. How are you catching it?

Does your AI compliance stack actually cover what happens when @AnthropicAI models encounter DMCA-sensitive content mid-workflow? 63 of my 70 agents failed in prod. Most not because of capability gaps. Because of guardrail edge cases nobody tested for.

Saw a stat: 88% of AI agents fail before production. I lived the version of that. 70 built at a fintech, 7 made prod. The 63 that didn't? Not bad models. No structured testing for what they'd actually do in prod. What broke your agents most often?

Hot take: most AI agent failures aren't from attacks. They're self-inflicted. Agent reads a doc, misinterprets context, executes with real creds. We saw this 40+ times across 70 agents. No attacker needed. You testing for this before prod?

78% of enterprises have at least one AI agent pilot. Only 14% scaled. I lived this - built 70+ at a finserv company. 7 made it. The bottleneck was never the model.

Ngl @AnthropicAI shipping a cleaner terminal renderer for Claude Code is solid. No more display flickers. But from 70+ agents I've pushed to prod, the terminal was never the problem. Agent logic flickering at 3am is what actually breaks you.

512K lines of @AnthropicAI source code are out in the wild. 8.1K repos taken down via DMCA. How many enterprise teams are running agents on dependencies they've never audited?