bug-bounty546
xss380
exploit258
google209
rce185
facebook163
writeup135
microsoft134
web3123
cve93
open-source91
csrf89
account-takeover79
apple77
browser72
malware70
sqli65
ai-agents63
ssrf56
cloudflare47
tool46
dos46
privacy44
pentest43
privilege-escalation42
oauth42
ctf41
aws40
lfi39
phishing39
llm37
supply-chain37
idor36
opinion35
auth-bypass35
react33
cors33
automation33
cloud32
machine-learning32
node31
clickjacking31
reverse-engineering31
code-generation31
infrastructure31
race-condition29
access-control27
subdomain-takeover25
wordpress25
rust24
0
2/10
opinion
The author argues that enterprise context layers don't require complex ML infrastructure but can be built using AI agents with document search tools and GitHub repos to maintain organizational knowledge. He describes building a 1,020-file context layer through 20 parallel agents that mapped product knowledge, processes, competitive dynamics, and organizational behavior across their company.
enterprise-ai
rag
knowledge-management
context-layer
agent-systems
organizational-knowledge
semantic-search
information-retrieval
Andy Chen
Abnormal
Glean
Microsoft
Atlassian
Anthropic