bug-bounty526
xss286
rce147
bragging-post120
google115
account-takeover107
exploit100
open-source96
privilege-escalation92
authentication-bypass88
facebook87
microsoft86
csrf85
stored-xss75
access-control69
malware69
web-security68
cve66
ai-agents64
writeup63
reflected-xss63
ssrf55
input-validation55
phishing50
smart-contract49
cross-site-scripting48
defi48
information-disclosure48
api-security48
sql-injection47
apple46
tool46
ethereum45
privacy44
cloudflare40
browser38
vulnerability-disclosure38
reverse-engineering38
llm37
web-application37
burp-suite37
automation36
opinion36
web335
oauth35
dos34
html-injection34
lfi34
remote-code-execution34
machine-learning33
0
2/10
This essay critiques claims that AI agents will replace software engineers by analyzing cognitive ability gaps between humans and AI across 12+ dimensions (output speed, working memory, long-term memory, confidence calibration, etc.). The author argues that task proficiency on isolated benchmarks does not translate to real-world autonomy due to AI's fundamental inability to perform causal modeling, calibrate confidence accurately, and operate reliably outside controlled environments.
ai-capabilities
autonomous-agents
cognitive-abilities
benchmark-limitations
software-engineering
ai-limitations
working-memory
long-term-memory
confidence-calibration
ai-autonomy
Max Trivedi
SignalBloom AI
DeepMind Gemini v2.5
John Von Neumann
Miller's Law