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[CLOSED] AGI TEAM - The Invisible Workforce. Zero Footprint. Total Execution. - Printable Version +- Hack Forums (https://hackforums.net) +-- Forum: Marketplace (https://hackforums.net/forumdisplay.php?fid=105) +--- Forum: Premium (https://hackforums.net/forumdisplay.php?fid=451) +---- Forum: Premium Sellers Section (https://hackforums.net/forumdisplay.php?fid=107) +---- Thread: [CLOSED] AGI TEAM - The Invisible Workforce. Zero Footprint. Total Execution. (/showthread.php?tid=6324967) |
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[CLOSED] AGI TEAM - The Invisible Workforce. Zero Footprint. Total Execution. - CYBERWAR WEAPONS - May 5, 2026
⚡ AGI team ⚡
[contract=tid]Start Contract[/contract]
The Invisible Workforce. Zero Footprint. Total Execution. Quote:is a high-level AGI orchestrator that replaces your entire overhead. It doesn't just "assist"—it operates.
🛠️ HOW IT WORKS
💎 SERVICE PLANS CORE UNIT - $449/Month (Full Sales & Fulfillment Loop, 2 Active "Employees") AGENCY SQUAD - $1,299/Month (Unlimited UpWork Bidding, 8 Active "Employees," Priority Processing) THE SHADOW CORP - Contact for Pricing (Full-Scale Infrastructure, Custom Human-Mimicry Fine-Tuning, Dedicated Server) Payment Methods: Cash App / BTC / LTC / XMR / ETH 👾 CONTACT US Discord: intelligence_general Disclaimer: GHOST-TEAM is a tool for high-level business automation and technical simulation. Use responsibly and at your own risk. RE: GHOST-TEAM - The Invisible Workforce. Zero Footprint. Total Execution. - Grand Hustle - May 6, 2026 Interesting concept, but I’ve seen a lot of “AI agency” products that are basically prompt wrappers around existing APIs. A few technical questions to separate real autonomous infra from marketing: 1. What’s the actual execution architecture? - Multi-agent orchestration? - DAG/task graph? - Event-driven workers? - Supervisor/reconciler layer? 2. How is long-term memory/state persisted across sessions? - Vector DB? - Relational state? - Episodic memory? - Context compaction strategy? 3. How do you prevent recursive hallucination/context poisoning between agents? 4. What models are actually being used underneath? - Frontier APIs? - Open-weight local models? - Routing/fallback strategy? - Cost optimization layer? 5. How are tools executed safely? - Docker/container sandboxing? - VM isolation? - Credential vaulting? - Scoped permissions? 6. How does the coding agent validate generated code before shipping? - Unit tests? - Static analysis? - CI/CD? - Execution sandbox? 7. How do you handle large multi-week projects with evolving requirements? - Repo indexing? - Semantic code search? - Architecture mapping? - Incremental planning? 8. How do you prevent infinite agent loops or deadlocks? - Watchdogs? - Iteration caps? - Supervisor agents? - Timeout recovery? 9. You mention eliminating “AI-isms” — what specifically achieves that? - Fine-tuning? - Style classifiers? - RLHF? - Post-processing pipeline? - Prompt ensembles? 10. What evals are you using to measure “human indistinguishability”? - Blind testing? - Detection benchmarks? - Conversion metrics? 11. How are client credentials stored and isolated? - Encrypted secrets? - OAuth scopes? - Audit logs? - Zero-trust model? 12. How do you defend against prompt injection via GitHub repos, client chats, or uploaded docs? 13. What’s the rollback strategy if an agent corrupts a repo or sends a bad proposal? 14. What’s the concurrency limit before latency spikes? - Queue architecture? - Worker autoscaling? - Rate-limit handling? 15. What part of the stack is genuinely novel vs existing frameworks like: - LangGraph - AutoGen - CrewAI - OpenHands - MCP toolchains - Claude Code Would also love to see a full technical walkthrough: UpWork discovery → proposal generation → negotiation → repo execution → QA/testing → delivery → invoicing. If you can answer these in dms or on here, I am definitely interested! |