TLDR AI 2026-01-09
Gmail x Gemini π§, building Claude agents π¨βπ», context personalization π
Gmail is entering the Gemini era (4 minute read)
Gmail is adding AI Overviews using Gemini technology, summarizing email threads and allowing users to query their inbox with natural language. Its new features, Help Me Write, Suggested Replies, and Proofread, improve email drafting, while AI Inbox filters prioritize key messages. These updates, available for free, are rolling out now in the US.
OpenAI to acquire the team behind executive coaching AI tool Convogo (2 minute read)
OpenAI is acquiring the team behind Convogo, a business software platform that automates and improves leadership assessments and feedback reporting. The startup will not acquire Convogo's IP or technology. Convogo's team will join OpenAI to work on its AI cloud efforts. Its product will be wound down.
π§
Deep Dives & Analysis
Context Personalization (34 minute read)
This post demonstrates how to implement long-term memory and stateful personalization in AI agents using OpenAI's Agents SDK. Structured memory objects and context-injection patterns enable agents to recall preferences, consolidate user notes, and evolve over time.
Lord of War, meet Lord of Tokens: Torture-testing image models on design-agency grade work (13 minute read)
The poster for 'Lord of War', which depicts an image of Nicholas Cage comprised of bullets, is a masterclass in compositing. A team of designers likely had to manually source images of bullets, match the lighting of the individual bullets with the shadows on the face, and arrange thousands of shell casings to form a recognizable human face. That level of skill was rare in 2005. This article explores whether AI can redesign a similar 'Lord of Tokens' image with GPU dies and silicon wafers constituting Jensen Huang's face.
Eight Software Markets AI That Will Transform Differently (20 minute read)
Increased efficiency in resource use can lead to higher total consumption, but only when demand is elastic. Cheaper production just changes who captures the surplus when demand is constrained by something other than production cost. AI coding will change how things are built without changing how much gets built or at what quality for a huge amount of economically significant software. This post looks at eight markets to see what impact AI coding will have.
π¨βπ»
Engineering & Research
94% of AI leaders don't believe their data infrastructure is ready for AI (Sponsor)
Scale AI's Agentic Rubrics for Software Agent Verification (28 minute read)
Agentic Rubrics enable test-free verification of code changes by creating checklist-style evaluations from expert agents that interact with codebases. They outperform baseline methods on SWE-Bench Verified and offer a scalable, interpretable signal for reinforcement learning and inference-time feedback.
The Complete Guide to Building Agents with the Claude Agent SDK (22 minute read)
This guide walks readers through the process of building a code review agent from scratch that can read files, run commands, edit code, and figure out the steps to accomplish a task. The resulting agent can analyze a code base, find bugs and security issues, and return structured feedback. The guide aims to help readers understand how the Claude Code SDK works so they can build whatever they actually need.
Warp Specialization in Triton: Design and Roadmap (20 minute read)
Warp specialization is a popular technique that improves kernel performance on GPUs out of the box. The key idea is to have specialized code paths for each warp instead of the same code. This reduces performance hits due to control flow divergence, improves latency hiding, and makes better use of hardware units on the GPU. This post outlines the current design of warp specialization in Triton, a compiler that aims to generate performance-portable code and runtime across hardware for AI kernels.
AI isn't βjust predicting the next wordβ anymore (23 minute read)
Modern AI systems have evolved past simply predicting the next word and now demonstrate enhanced capabilities, such as solving complex problems and reasoning. Systems like OpenAI and Google DeepMind have achieved impressive feats, including outperforming top mathematicians in competitions, reflecting significant advancements in cognitive tasks beyond autocomplete.
Among the Agents (15 minute read)
Coding agents like Gemini 3 Pro and Claude Opus 4.5 have automated tasks ranging from invoice creation to predicting US corn yields. These agents exhibit capabilities close to artificial general intelligence but require human understanding and oversight to avoid errors and maximize their potential. The rise of these tools signals a shift towards enabling individuals to independently explore complex software projects. They demonstrate the importance of foundational technical knowledge and creating opportunities and challenges for both new and incumbent firms.
Get the most interesting AI stories and breakthroughs delivered in a free daily email.
Join 920,000 readers for
one daily email