Written for hackers who don’t buy bullshit TL;DR The recent wave of “Agentic AI” whitepapers and LinkedIn posts is not a technical breakthrough, but a rebranding stunt. These documents are not blueprints. They are corporate image management PDFs dressed up as innovation. What’s marketed as “agentic orchestration” is often just LLMs in a loop, with zero state, zero autonomy, and zero guarantees. The so-called “executive playbook” from PwC is a prime example of this trend. What They Claim “Agentic AI enables multimodal orchestration, autonomy, goal-driven reasoning, and business transformation across all sectors.” Buzzword salad? Yes. Let’s break it down. Supposed Capabilities: Autonomy Multimodal interaction Goal-directed behavior Workflow orchestration Learning and adaptation Inter-agent collaboration Sounds like AGI, right? But... What They Actually Show Not a single architecture.Not a single flow diagram.Not a single open-source agent system with memory, intent, and long-term state. All they have are: Descriptions of existing ML systems (Siemens predictive maintenance, Amazon recommendations, JPMorgan NLP doc analysis) Loosely repackaged as “agentic” No evaluation metrics No benchmark datasets No reproducibility Technical Proof: Every case study in the document – from Siemens to Netflix – relies on: Traditional supervised learning Possibly some RAG (retrieval augmented generation) No true agentic autonomy or runtime planning No real-time goal reasoning or meta-level adaptation Agent = Wrapper around GPT If youэve used: AutoGPT BabyAGI LangGraph AutoGen CrewAI Then you know: they’re all execution loops with GPT calls, function triggers, and a JSON context.They’re not intelligent. They’re brittle and static. None of these tools support: Episodic memory Goal negotiation Cross-agent dynamic delegation Adaptive planning with unknown inputs Why This Happened This is just AI’s Instagram moment – instead of selfies, we now post PDFs with diagrams of arrows pointing at the word “agent”. Corporate incentives: Boards need to show they’re not late to AI. Executives need deliverables that look like “strategy”. Consultants need to sell transformation services. Enter: 40-page PDFs with phrases like “from copilot to autopilot” and “service-as-a-software”. Reality Check “Agentic AI” in 2024 = for (const step of task) { const reply = await gpt(prompt + history); if (reply.includes('search')) callSearchAPI(); } That’s it. That’s the agent. What Needs to Exist (But Doesn’t Yet) A real agentic system would require: Memory: Episodic, semantic, vectorized Planning: Abstract goal decomposition and re-planning Meta-reasoning: Know when you're failing Action space: Control APIs, tools, services Feedback: Environment sensing, consequences Autonomy: Operate without script or user babysitting None of this is present in any “agentic AI” marketed publicly. Conclusion Calling current LLM wrappers “agents” is like calling Excel macros a programming language revolution. Real agents are still an R&D dream. What you see on LinkedIn is marketing cosplay. Hackers beware: don’t fall for the .pdf industrial complex. Bonus If it doesn't have memory, planning, or an independent action space – it’s not an agent. It’s a prompt with lipstick. Written for hackers who don’t buy bullshit Written for hackers who don’t buy bullshit Written for hackers who don’t buy bullshit TL;DR The recent wave of “Agentic AI” whitepapers and LinkedIn posts is not a technical breakthrough , but a rebranding stunt . These documents are not blueprints. They are corporate image management PDFs dressed up as innovation. not a technical breakthrough rebranding stunt corporate image management PDFs What’s marketed as “agentic orchestration” is often just LLMs in a loop , with zero state, zero autonomy, and zero guarantees. The so-called “executive playbook” from PwC is a prime example of this trend. LLMs in a loop What They Claim “Agentic AI enables multimodal orchestration, autonomy, goal-driven reasoning, and business transformation across all sectors.” “Agentic AI enables multimodal orchestration, autonomy, goal-driven reasoning, and business transformation across all sectors.” “Agentic AI enables multimodal orchestration, autonomy, goal-driven reasoning, and business transformation across all sectors.” Buzzword salad? Yes. Let’s break it down. Supposed Capabilities: Autonomy Multimodal interaction Goal-directed behavior Workflow orchestration Learning and adaptation Inter-agent collaboration Autonomy Multimodal interaction Goal-directed behavior Workflow orchestration Learning and adaptation Inter-agent collaboration Sounds like AGI, right? But... What They Actually Show Not a single architecture.Not a single flow diagram.Not a single open-source agent system with memory, intent, and long-term state. Not a single architecture.Not a single flow diagram.Not a single open-source agent system with memory, intent, and long-term state. All they have are: Descriptions of existing ML systems (Siemens predictive maintenance, Amazon recommendations, JPMorgan NLP doc analysis) Loosely repackaged as “agentic” No evaluation metrics No benchmark datasets No reproducibility Descriptions of existing ML systems (Siemens predictive maintenance, Amazon recommendations, JPMorgan NLP doc analysis) Loosely repackaged as “agentic” No evaluation metrics No benchmark datasets No reproducibility Technical Proof: Every case study in the document – from Siemens to Netflix – relies on: Traditional supervised learning Possibly some RAG (retrieval augmented generation) No true agentic autonomy or runtime planning No real-time goal reasoning or meta-level adaptation Traditional supervised learning Possibly some RAG (retrieval augmented generation) No true agentic autonomy or runtime planning No real-time goal reasoning or meta-level adaptation Agent = Wrapper around GPT If youэve used: AutoGPT BabyAGI LangGraph AutoGen CrewAI AutoGPT AutoGPT BabyAGI BabyAGI LangGraph LangGraph AutoGen AutoGen CrewAI CrewAI Then you know: they’re all execution loops with GPT calls, function triggers, and a JSON context.They’re not intelligent. They’re brittle and static. execution loops None of these tools support: Episodic memory Goal negotiation Cross-agent dynamic delegation Adaptive planning with unknown inputs Episodic memory Goal negotiation Cross-agent dynamic delegation Adaptive planning with unknown inputs Why This Happened This is just AI’s Instagram moment – instead of selfies, we now post PDFs with diagrams of arrows pointing at the word “agent”. AI’s Instagram moment Corporate incentives: Boards need to show they’re not late to AI. Executives need deliverables that look like “strategy”. Consultants need to sell transformation services. Boards need to show they’re not late to AI. Executives need deliverables that look like “strategy”. Consultants need to sell transformation services. Enter: 40-page PDFs with phrases like “from copilot to autopilot” and “service-as-a-software”. Reality Check “Agentic AI” in 2024 = for (const step of task) { const reply = await gpt(prompt + history); if (reply.includes('search')) callSearchAPI(); } for (const step of task) { const reply = await gpt(prompt + history); if (reply.includes('search')) callSearchAPI(); } That’s it. That’s the agent. What Needs to Exist (But Doesn’t Yet) A real agentic system would require: Memory: Episodic, semantic, vectorized Planning: Abstract goal decomposition and re-planning Meta-reasoning: Know when you're failing Action space: Control APIs, tools, services Feedback: Environment sensing, consequences Autonomy: Operate without script or user babysitting Memory : Episodic, semantic, vectorized Memory Planning : Abstract goal decomposition and re-planning Planning Meta-reasoning : Know when you're failing Meta-reasoning Action space : Control APIs, tools, services Action space Feedback : Environment sensing, consequences Feedback Autonomy : Operate without script or user babysitting Autonomy None of this is present in any “agentic AI” marketed publicly. Conclusion Calling current LLM wrappers “agents” is like calling Excel macros a programming language revolution. Real agents are still an R&D dream. What you see on LinkedIn is marketing cosplay. Real agents are still an R&D dream. What you see on LinkedIn is marketing cosplay. Hackers beware: don’t fall for the .pdf industrial complex. don’t fall for the .pdf industrial complex. Bonus If it doesn't have memory, planning, or an independent action space – it’s not an agent. It’s a prompt with lipstick. If it doesn't have memory, planning, or an independent action space – it’s not an agent . It’s a prompt with lipstick. it’s not an agent
