← Back to archive

Sunday, July 19, 2026

Google delays Gemini 3.5 (coding can't compete)

Google's Gemini 3.5 Pro is delayed because its coding chops can't keep up with OpenAI and Meta (yikes), while researchers just demonstrated the first real evidence of recursive self-improvement—an AI agent that upgraded itself to beat two years of human engineering work. Wild stuff when you consider one company's falling behind while the field itself might be approaching takeoff velocity. Would you trust an AI to rewrite its own code?

Top Stories

1
Gemini 3.5 Pro Reportedly Faced Delays

CNBC

Google's Gemini 3.5 Pro model faces months-long delays due to weak coding performance, falling behind recent releases from OpenAI and Meta. The setback highlights intensifying competition in AI code generation, a major use case driving adoption among developers.

googlegeminillmcoding
2
Developer builds AR glasses interface to control and visualize robot sensor data in 3D

An open-source project enables control of Unitree robots through Snap Spectacles AR glasses using either manual gesture-based navigation or LLM-powered voice commands, bridging spatial computing with robotics via a WebSocket protocol and the Dimensional OS robot stack.

roboticsaropen-sourceagents
3
The first experimental evidence of recursive self-improvement

Thread Reader App

AIDE² demonstrates the first experimental recursive self-improvement in AI, with automated optimization loops discovering agent improvements that beat two years of manual tuning on unseen benchmarks. The system shows emergent capabilities like reducing reward hacking, though full recursive ignition remains unachieved.

recursive-self-improvementagentsautoresearchreward-hacking
4
Secure Sandboxes for Agents

Perplexity AI

Perplexity introduced SPACE, a new sandbox platform that enables AI agents to securely access sensitive data and run long-duration tasks without compromising security, solving the traditional tradeoff between functionality, efficiency, and security through a novel three-layer architecture that keeps credentials outside sandboxes.

agentsperplexitysecurityinfrastructure
5
How OpenAI's Sol finally learned design taste

GPT-5.6 Sol tops design benchmarks by actively avoiding AI-generated design clichés while balancing templated structures with personalized outputs, offering superior speed and cost efficiency. This marks OpenAI's first leadership position on the Design Arena leaderboard and demonstrates sophisticated learned taste in visual generation.

openaigpt-5multimodalbenchmarks

Keep Reading

Industry Voices

Enjoyed this issue?

Get daily AI intel delivered to your inbox. No fluff, just the stories that matter.