# Why might dependable AI coworkers take longer? | AGI

Karpathy describes agents as a decade-long engineering effort, pointing to gaps including continual learning.

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## Source-linked future guide

You can read all sources and guides without JavaScript. Enable it to filter, save or export your own plan. Future guide (/future-guide) / Capability is not reliability Capability is not reliability Why might dependable AI coworkers take longer? Karpathy describes agents as a decade-long engineering effort, pointing to gaps including continual learning. Andrej Karpathy · Dwarkesh Podcast Interview: 2025-10-17 Source review: 2026-10-03 Dwarkesh Podcast · Video · 00:00:00 Andrej Karpathy Return to the original context. ▶ Load original video Connects to YouTube only after you click. Watch from this chapter ↗ (https://www.youtube.com/watch?v=lXUZvyajciY&t=0s)Publisher’s original page ↗ (https://www.dwarkesh.com/p/andrej-karpathy) Source, interpretation and uncertainty What does this actually establish? Source status Publisher chapter at 00:00:00 · Not an independently verified outcome Speaker context AI researcher · discussing agents and education What remains open This is a view recorded in October 2025, not a current capability test or a resolved AGI deadline. AGI editorial interpretation Two ways this could unfold If reliability improves slowly, supervised workflows remain useful. If agents handle unfamiliar tasks well, your test should reveal that change. These are conditional scenarios, not the speaker’s words or a probability estimate. Read alongside: How should we prepare if powerful AI arrives sooner? (/future-guide/fast-ai-progress) Different framing, dates and definitions; not a direct head-to-head forecast. Where do I stand for now? Lean toward agreement Lean toward disagreement Need more evidence This is your private, device-only record. No public vote count or collective probability is implied. Turn a view into a small experiment What is my next step? A simple plan you can test and revise. Your notes stay in this tab until you save them. What matters to me Understand the change Adapt my work Choose what to learn Explore income ideas Think about education Test my judgment The task or question in my life One action I will try Use the editorial starting point ↗ What would change my view? My review date (optional) I have tried this action Save my next step Export plan Add to calendar Saved on this device. You control the plan and review date; these are not model predictions. Read the interview and evidence on AGI ↗ (https://agiscorecard.com/future-guide/agents-take-time) Embed the free action planner Video and context stay on this source page. <iframe src="https://agiscorecard.com/future-guide/agents-take-time?embed=1" title="AGI action planner" width="100%" height="950" loading="lazy"></iframe> ← Return to my next steps (/future-guide#notebook) ✳ JARVIS Research guide What would make me trust an agent with this task? Try an unfamiliar task with explicit acceptance criteria. Record where a person still needs to intervene. Make my next step ↗ (#plan) Based on published sources and editorial guidance. This is not an AI-generated forecast or a personal capability assessment. A useful reading path A view in its original context A reason to stay open-minded An action you can try No account required. When you want to keep the work Your next step deserves a place to return to. Reading, video access, local saves and exports are free. Use the same plan on another device with AGI’s existing cloud workspace and version history. No paid interview collection or automated personal-report subscription is offered here. AGI cloud membership 9 USDT / 30 days Plus the order-matching decimal and network fees. 50 workspaces, 10 versions per workspace, 64 KB per workspace and 5 MB in total. No auto-renewal or extra AI allowance. Open my plan in membership The member page checks availability. Opening it does not upload your plan or start a purchase; save there explicitly. USDT payment only.
