bug-bounty545
xss379
exploit255
google204
rce179
facebook161
writeup134
microsoft129
web3122
open-source91
csrf89
cve84
account-takeover78
apple75
browser71
sqli65
malware64
ai-agents63
ssrf56
tool46
privacy44
dos44
cloudflare43
oauth41
pentest41
privilege-escalation40
ctf40
lfi39
llm37
aws36
idor35
supply-chain35
opinion35
phishing33
react33
automation33
auth-bypass33
cors32
machine-learning32
clickjacking31
reverse-engineering31
infrastructure31
code-generation31
cloud30
node30
race-condition29
access-control27
wordpress25
subdomain-takeover25
postmessage24
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