bug-bounty526
xss286
rce146
bragging-post119
account-takeover106
google105
open-source95
exploit95
privilege-escalation92
authentication-bypass88
csrf85
facebook79
microsoft75
stored-xss75
access-control69
web-security68
cve65
ai-agents64
reflected-xss63
writeup63
malware62
ssrf55
input-validation55
smart-contract49
phishing49
cross-site-scripting48
defi48
information-disclosure47
api-security47
sql-injection47
tool46
ethereum45
privacy44
cloudflare40
vulnerability-disclosure38
reverse-engineering37
apple37
web-application37
burp-suite37
llm37
opinion36
automation36
web334
remote-code-execution34
dos34
html-injection34
oauth34
lfi34
smart-contract-vulnerability33
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