bug-bounty527
xss286
rce147
bragging-post119
google118
account-takeover107
exploit100
open-source95
privilege-escalation92
facebook89
authentication-bypass88
microsoft87
csrf85
stored-xss75
malware71
access-control69
web-security68
cve66
ai-agents64
reflected-xss63
writeup63
ssrf55
input-validation55
phishing50
smart-contract49
defi48
cross-site-scripting48
api-security47
sql-injection47
apple47
information-disclosure47
tool46
ethereum45
privacy44
cloudflare40
browser38
vulnerability-disclosure38
reverse-engineering38
llm37
burp-suite37
web-application37
automation36
opinion36
web335
oauth35
html-injection34
dos34
remote-code-execution34
lfi34
responsible-disclosure33
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