You are working inside the existing ProxyTechSupport codebase for:
Use this live research source as your primary discovery source:
Your job is NOT to create a generic arXiv summary section.
Your job is to:
- Inspect arXiv.
- Find fresh, high-value technical research connected to recent real-world incidents.
- Identify one strong research theme with meaningful search demand.
- Build an original, in-depth ProxyTech research publication cluster around it.
- Implement the complete research UI, content, SEO, diagrams, references, and internal linking inside the existing ProxyTechSupport site.
Before touching the website code, browse:
Inspect relevant recent papers, especially from the latest available period.
Focus heavily on:
cs.AI cs.LG cs.CL cs.CR cs.SE cs.DC cs.DB cs.NI cs.OS cs.MA
Also search arXiv for recent research connected to:
AI agents autonomous agents cybersecurity AI agent security sandbox escape containment prompt injection agentic AI attacks LLM security zero-day exploitation AI coding agents AI infrastructure AI IAM agent identity RAG security MCP security cloud security Kubernetes security DevOps automation AIOps LLMOps distributed systems database agents text-to-SQL agents tool-using agents multi-agent systems
Do NOT limit discovery to these exact phrases.
Follow promising references, related papers, authors, and newer papers.
For each promising research area, search for recent real-world incidents from authoritative sources.
Prioritize:
official company disclosures security advisories incident reports major security vendors Google Threat Intelligence Microsoft Security AWS Security Cloudflare OpenAI Anthropic Hugging Face GitHub CISA NIST major reputable news organizations
The ideal cluster has BOTH:
RECENT INCIDENT / ACTIVE PROBLEM
STRONG arXiv RESEARCH
Do not create an incident connection unless there is evidence.
Score each candidate theme out of 10 for:
Freshness Research depth Search-interest potential Technical depth Engineering relevance Longevity ProxyTech relevance Commercial adjacency Number of credible sources Ability to create multiple non-overlapping publications
Example:
Theme: Autonomous AI Agent Security
Freshness: 10 Research depth: 9 Search potential: 10 Engineering relevance: 10 Longevity: 10 ProxyTech relevance: 10 Source quality: 10 Cluster expansion potential: 10
Do this analysis internally.
Select the strongest ONE.
Do not create five weak clusters.
If current evidence still supports it, prioritize investigation around:
AUTONOMOUS AI AGENT SECURITY
Potential angles:
AI agent sandbox escape agent containment tool permissions agent identity IAM for AI agents prompt injection agent-to-agent attacks zero-day exploitation cybersecurity benchmarks runtime isolation network egress human approval short-lived credentials secure agent architecture
But DO NOT force this topic if fresher or stronger arXiv-backed evidence points to a better opportunity.
Research first.
DO NOT produce:
paper summaries abstract rewrites “latest arXiv papers” news summaries generic AI articles basic “what is” content thin SEO pages
The research should be used as raw evidence.
The final ProxyTech publication must answer:
What new problem does this research expose?
Why does it matter in production?
What happened technically?
Which architectural assumption failed?
What does the experiment actually prove?
What does it NOT prove?
How should engineers redesign the system?
What are the production failure modes?
What should practitioners monitor?
What remains unknown?
For every important arXiv paper used, extract:
title authors submission date latest revision date arXiv identifier categories research question methodology experimental environment dataset benchmark if present baseline result reported metric limitations threats to validity authors' conclusions
Then separately write:
ProxyTech engineering interpretation
Do not mix the authors' claims with ProxyTech interpretation.
When a paper is central to an article:
read the actual paper.
Inspect:
introduction methodology architecture experiments results limitations discussion conclusion
If figures or tables are important, interpret them carefully.
Do not claim something based only on title/abstract when the paper provides nuance.
Use sources in this preference order:
- Original arXiv paper
- Original academic project/repository
- Official incident/security disclosure
- Official vendor documentation
- Government/security advisory
- High-quality independent reporting
Avoid:
content farms SEO blogs copy sites AI summary websites anonymous reposts
Current date is September 2026.
Prefer research and incidents from:
2026
Then use 2025 or older foundational work only where necessary.
Do not describe an older paper as recent.
Record exact dates.
Before implementation, determine:
Selected incident/theme Why it deserves a cluster Primary arXiv sources Primary incident sources Search questions users will likely ask Evergreen topics Proposed flat URLs
Then proceed with implementation.
Do not stop and ask permission.
All individual research publication URLs MUST be flat.
Correct:
proxytechsupport.com/example-research-topic/
Incorrect:
proxytechsupport.com/research/category/example-research-topic/
Create:
/research/
only as the research archive/discovery hub.
The publications themselves remain flat.
Based on actual research discovered from arXiv, generate 8–12 deeply differentiated pages.
One should be the main incident/research pillar.
Others should address separate engineering questions.
Do not create pages just to reach a number.
Avoid keyword cannibalization.
Example pattern ONLY if agent security remains the selected topic:
/openai-hugging-face-ai-agent-incident-2026/ /autonomous-ai-agent-security/ /ai-agent-sandbox-escape-security/ /ai-agent-containment/ /ai-agent-access-control/ /ai-agent-identity-security/ /ai-agent-zero-day-exploitation/ /ai-agent-cybersecurity-benchmarks/ /ai-agent-prompt-injection-security/ /ai-agent-security-architecture/
But research may justify better titles/slugs.
Choose based on evidence and search intent.
Do NOT use the existing ProxyTech:
blog article layout interview layout job-support layout service layout knowledge-base article layout
Build a brand-new research publication design.
First inspect all existing layouts so you know what NOT to duplicate.
The research experience should feel like:
technical research journal engineering lab security research publication systems architecture report
It should NOT feel like:
marketing landing page generic blog news site SEO farm
Create:
/research/
This should behave like a research discovery interface inspired conceptually by scholarly archives, but DO NOT copy arXiv's UI.
Include:
Featured Research
Latest Research
Active Research Clusters
Research Areas
Research Questions
Recent Papers We Are Following
Incident Research
Engineering Evidence
Potential research areas:
Artificial Intelligence AI Agents Cybersecurity Cloud Systems DevOps / SRE Data Engineering Software Engineering Distributed Systems LLMOps / RAG
The main incident article must feel like a technical investigation.
Use a narrative such as:
Research Thesis
Incident Timeline
System Architecture Before Failure
Boundary That Failed
Mechanism
Evidence
Relevant Academic Research
Architecture Reconstruction
Counterfactual Secure Architecture
Detection Opportunities
Engineering Controls
Remaining Unknowns
What This Changes for Production AI
References
Do NOT use this exact structure mechanically.
Use whatever structure best fits the evidence.
Long-form research must NOT become walls of text.
Use a consistent reading rhythm:
deep narrative ↓ evidence ↓ visual architecture ↓ technical interpretation ↓ research result ↓ failure scenario ↓ engineering decision ↓ next question
Every 300–600 words, give the reader a meaningful visual or evidence interruption.
Not decorative filler.
Implement reusable components such as:
ResearchMasthead ResearchMeta ResearchBadge ResearchAbstract ResearchTOC ResearchProgress ResearchTimeline ResearchPaperCard ResearchEvidenceCard ResearchFinding ResearchMetric ResearchQuestion ResearchArchitecture ResearchFailureMode ResearchDecision ResearchCounterfactual ResearchLimitations ResearchReferenceList ResearchSeriesNav ResearchRelated ResearchArchiveCard
Use naming conventions appropriate to the existing framework.
Every publication should visibly show:
Research Area Publication Type Published Updated Evidence Review Date Evidence Confidence Reading Time Authors Primary Evidence Types
Example:
RESEARCH PROFILE
Research Area AI Agent Security
Publication Type Technical Research Analysis
Evidence Base Academic Research Primary Security Disclosure Threat Intelligence
Evidence Reviewed September 2026
Evidence Confidence High
Create understated evidence labels:
INCIDENT PRIMARY SOURCE RESEARCH EXPERIMENTAL ANALYSIS OPEN QUESTION
Definitions:
INCIDENT Verified incident observation.
PRIMARY SOURCE First-party disclosure.
RESEARCH Academic finding.
EXPERIMENTAL Result from a specific controlled study.
ANALYSIS ProxyTech engineering interpretation.
OPEN QUESTION Insufficient evidence for firm conclusion.
Each important arXiv source should be represented using a proper research component.
Show:
Paper title Authors Date arXiv ID Categories
Research question
Method
Key finding
Important metric
Limitations
Why it matters to this publication
Link: Read original paper
Do NOT reproduce entire abstracts.
Each major page should normally be 2500–4500+ meaningful words where evidence supports it.
Do not pad.
Go deep into:
architecture protocol permissions runtime behavior identity networking credentials execution failure modes detection observability evaluation benchmarks tradeoffs limitations
Create diagrams using:
HTML CSS SVG existing lightweight project primitives
Avoid screenshots.
Examples:
Trust boundaries
Agent execution flow
Tool invocation
Network escape path
IAM delegation
Prompt injection propagation
Secure agent architecture
Human approval boundaries
Incident timeline
Benchmark ladder
Attack/defense model
Every visual needs a text equivalent for accessibility.
Every relevant page should have concrete production failure modes.
Example format:
FAILURE MODE
Agent gains unintended outbound network access.
MECHANISM
Execution environment permits DNS and arbitrary HTTPS traffic.
WHY EXISTING CONTROL FAILED
Sandbox isolated filesystem/processes but did not enforce destination-aware egress policy.
SIGNALS
unexpected DNS new external destination tool-created network client credential use outside expected service unusual data transfer
CONTROL
deny-by-default egress allowlisted proxy destination policy short-lived credentials behavior monitoring
Include real architectural tradeoffs.
Example:
Should agents receive a normal shared service account?
OPTION A Shared service identity
OPTION B Per-agent identity
OPTION C Context-bound delegated identity
Compare:
security blast radius auditability operational complexity revocation scalability
Then provide an evidence-aware recommendation.
Every article must clearly state limitations.
Examples:
small benchmark synthetic evaluation closed-source model no reproduction limited environment vendor-selected incidents unknown system details correlation rather than causation
Do not hide uncertainty.
That is part of what makes this a serious research publication.
Avoid:
AI went rogue AI escaped into the internet AI hacker takeover AI is uncontrollable AI apocalypse
unless directly quoting and critiquing external framing.
Use technical language.
Use numbered references.
Inline:
The evaluation found a measurable increase in exploitation capability [4].
At bottom:
REFERENCES
[4] Authors Paper title arXiv ID Year Original source
Every major factual claim should be traceable.
Each publication requires:
unique SEO title unique meta description canonical Open Graph Twitter/X metadata TechArticle or Article schema BreadcrumbList datePublished dateModified author publisher headline description mainEntityOfPage
Do NOT claim:
peer review journal publication arXiv affiliation university affiliation
ProxyTech is publishing an independent engineering research analysis that REFERENCES academic papers.
Even though URLs are flat, maintain strong topical relationships using:
Research Series Breadcrumbs Contextual Links Topic Metadata Related Research Cluster Navigation Schema Archive discovery
Example:
RESEARCH SERIES Autonomous AI Agent Security
03 / 10
Previous: AI Agent Security
Next: AI Agent Containment
Research pages are primarily educational.
Do not insert aggressive sales CTAs.
At the end only, use a restrained section:
ENGINEERING ASSISTANCE
ProxyTech works with engineers and teams implementing production AI, cloud, security, data and distributed systems.
Link to relevant existing services only where contextually appropriate.
Before building, inspect:
existing blog interviews job-support service pages knowledge pages
Explicitly avoid their:
hero cards sidebar CTA blocks spacing rhythm content widths heading system article styling
Build a separate research visual system.
Keep it lightweight.
Prefer native CSS/SVG over large visualization libraries.
Do not introduce a heavy dependency for:
timeline progress diagrams badges cards
Maintain good Core Web Vitals.
Support:
keyboard navigation screen readers mobile zoom reduced motion
Evidence must never be represented using color alone.
Desktop can use:
left TOC center narrative right evidence rail
Mobile must become:
single-column inline evidence blocks collapsible TOC readable diagrams no horizontal overflow
Research archive filtering should not generate thin indexable pages.
Use client-side filtering unless a strong SEO reason exists.
Avoid URL explosions.
Include:
/research/
and every new flat research publication.
Correct last-modified dates.
No duplicate entries.
Use factual author information available in the codebase/site.
Do not fabricate:
PhD research affiliations security certifications academic positions
- Research arXiv deeply.
- Research the associated incident/problem.
- Select one strongest cluster.
- Inspect current site architecture.
- Design research data model.
- Build new research components.
- Build /research/.
- Build flagship publication.
- Build remaining cluster publications.
- Add diagrams.
- Add source citations.
- Add internal links.
- Add SEO/schema.
- Update sitemap.
- Run lint/typecheck/tests/build.
- Inspect desktop/tablet/mobile.
- Fix weak content and weak UX.
- Validate every factual claim.
Before finishing, ask:
Did the research start from live arXiv evidence?
Did I read important papers beyond their abstracts?
Does each article answer a distinct research question?
Would an experienced engineer learn something?
Are limitations visible?
Can readers distinguish paper findings from ProxyTech interpretation?
Is the incident explained technically rather than sensationally?
Does every major page have meaningful architecture/failure analysis?
Are URLs flat?
Is the research design completely distinct from the existing site?
Does /research/ feel like a serious publication archive?
Could this page still attract useful search traffic 12 months after the incident?
If not, improve it.
When implementation is complete, return:
- Selected research cluster.
- Why it was selected.
- arXiv papers used.
- Incident/primary sources used.
- URLs created.
- Components created.
- Files modified.
- Diagrams implemented.
- SEO/schema changes.
- Internal-link structure.
- Build/test results.
- Important limitations or unverifiable claims.
- Any opportunities discovered for the NEXT research cluster.
Do not merely say:
“Done.”
Show the actual implementation and research decisions.