Anthropic Predicts Self-Improving AI

Welcome back to The Shift. Let’s get straight to what matters in AI today…

Today we have:

🤖 Anthropic's cofounder just put 60% odds on AI building itself by 2029

💻How to run your business operations on autopilot with Accio Work

📊 Meta and X are both rethinking how advertising works this week

🔨Tools and Shifts you cannot miss

🤖 Anthropic's Cofounder Just Put 60% Odds on AI Building Itself by 2029

Jack Clark published a new essay this week putting 60%+ odds on AI systems training their own successors before 2029, built entirely on public benchmark data showing AI has gone from near-zero to near-perfect on core R&D tasks in under three years.

The Shift:

The Benchmark Evidence Is Hard to Dismiss - SWE-Bench moved from Claude 2 at 2% in 2023 to Mythos Preview at 93.9% today. CORE-Bench for reproducing scientific papers went from 21.5% to 95.5% in 15 months. Both benchmarks are effectively saturated.

AI Can Now Work Independently for 12 Hours - METR data shows AI's independent task capability went from 30-second tasks in 2022 to 12 hours in 2026. Tasks that take AI researchers a few hours now sit comfortably inside the current AI time horizon.

The Core R&D Loop Is Already Being Automated - The vast majority of people at frontier labs now code entirely through AI. MLE-Bench for Kaggle competitions went from 16.9% to 64.4% in 16 months. Researchers are delegating increasingly complex work to AI systems.

What Clark Actually Thinks Happens Next - He does not expect self-improving AI in 2026, but thinks a proof-of-concept model training its own successor is plausible within a year or two. OpenAI is targeting an automated research intern by September 2026.

Clark built this entire case from public papers and benchmarks, no inside information required. If the trends hold, the question is not whether AI systems start building themselves but when. Clark thinks that timeline is now measured in years, not decades.

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📊 Meta and X Are Both Rethinking How Advertising Works This Week

Meta gave brands the freedom to manage campaigns using whatever AI they already trust, while X overhauled its entire ad infrastructure from the ground up using xAI's latest models.

The Shift:

Meta Opens Its Ad Data to Any AI - Meta launched AI connectors, letting brands pipe their Meta ads data directly into Claude, ChatGPT, or any external AI tool of their choice to run queries, generate product catalogs, and manage campaigns.

No Code or Setup Required - Meta's connectors need no developer credentials, API setup, or coding, making them accessible to any agency or brand. The goal is to meet advertisers where they already work rather than pushing Meta AI on everyone.

X Rebuilt Its Entire Ad System - X launched what it calls the biggest ad update in its history, built around simplicity, control, and performance. New AI retrieval and ranking systems now understand user behavior more deeply to deliver more precise and relevant ads in real time.

Musk Wants Full Ad Automation Eventually - The long-term goal is Grok handling the entire ad creation process, uploading an ad, and doing nothing else.

This rebuild is the first real infrastructure step toward that vision as X's subscription business continues to fall short. Meta is betting openness wins advertiser loyalty. X is betting that better AI targeting revives its struggling ad business. Both are using AI to make ads easier to run, just from very different starting points and with very different levels of trust to rebuild.

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🔨AI Tools for the Shift

🎬 AIImageToVideo – Turns any photo into a dynamic video in seconds, making content creation fast and effortless.

🧠 Thinka – Generates unlimited practice questions with instant grading and personalized feedback for exams like AP and SAT.

📊 AIProofMe – Analyzes your career risk against AI disruption and shows what skills to build next to stay relevant.

🎥 Kairval – Converts text prompts into high-quality cinematic videos with realistic motion using advanced diffusion models.

🎓 Honen – Transforms your knowledge or ideas into complete courses with projects, certificates, and an AI tutor built in.

🚀Quick Shifts

⚖️ Google DeepMind employees vote to unionize, opposing the use of AI in military contracts and seeking representation to influence how the company’s technology is developed and deployed.

🏢 OpenAI pauses plans to spin out hardware and robotics divisions, scaling back non-core projects ahead of a potential IPO while keeping the option open to revisit the structure later.

🖼️ Image AI models are driving app growth, generating up to 6.5x more downloads than chatbot updates, as visual features attract users, though most apps struggle to convert that surge into revenue.

⚖️ Elon Musk reportedly texts Greg Brockman and Sam Altman, warning they’ll be “the most hated men in America” if they don’t settle, as part of escalating tensions in the OpenAI lawsuit.

🏢 Anthropic and OpenAI are launching separate enterprise AI joint ventures, raising billions from major investors to deliver customized AI solutions and expand commercial adoption across large organizations.

🧩 Prompt of the Day

Customer Milestone Recognition That Builds Real Loyalty

Most brands reward purchases. The best brands celebrate moments, making customers feel seen and valued beyond transactions.

Turn milestones into emotional connection points.

Paste the prompt: Drop this into ChatGPT, then fill in your brand details.

Prompt to paste

Create a customer milestone recognition plan for [Insert brand or product]. Identify milestone types such as first purchase, repeat orders, anniversaries, or loyalty tiers. Suggest recognition methods like rewards, discounts, exclusive access, or personalized messages. Recommend communication channels including email, SMS, app notifications, or social. Focus on building emotional loyalty, increasing retention, and strengthening long-term engagement.

🤳AI Nugget of the Day

That’s all for today’s edition. See you tomorrow as we track down and get you all that matters in the daily AI Shift!

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