It is very important to understand that AI models are not deterministic and they cannot be made deterministic without severely restricting the environment they run in. Fixing seeds doesn’t help. Setting temperature to 0 doesn’t help. Every small floating point rounding error can ultimately lead to drastically different results.

The complex models are, in essence, chaotic systems and should be treated as such.

AI coding agents are just another tool in a good developer’s toolbox. They start with a slab of stone, and use those agents as a metaphorical sledgehammer to give it the rough form they envision. Then, they reach for AI-assisted coding tools, such as GitHub Copilot, to work with more precision, akin to a smaller hammer. And finally, they use the smallest chisel to carve out the finest details by hand.

How funny it is to hear that the art of programming is dead because we no longer carve the slabs with those small chisels alone.

A funny thing: Gemini Deep Research is programmatically discouraged from finishing early. I found that out when I tried to use it to extract information from unstructured text and fill in a template. Despite its being a research tool, it has everything necessary for such a task: access to Google Docs, ability to create long-form documents and the meticulous agentic flow. Of course, if we want to just restructure the document, it is important that the model does not use internet search at all.

The agent did the work quite well and quickly. However, when it was about to finish, it received several “continue research” urges from the programmatic orchestrator, and guess what? It started browsing the internet for the missing information.

The moral is: you can be creative with such systems, but you should expect the scaffolding to throw a wrench in the works.

After Weeks of Markey Raising the Alarm, Senate Strikes AI Moratorium from Budget Reconciliation Bill Overnight in Overwhelming 99-1 Vote

So, no moratorium on state-level AI regulations. Those developing AI systems, get ready to learn and implement compliance measures for 50 different states. Woe to us.

Cloudflare Just Changed How AI Crawlers Scrape the Internet-at-Large; Permission-Based Approach Makes Way for A New Business Model

Cloudflare makes a large step towards data monetization for AI training. Now all new data hosted on Cloudflare is inaccessible to AI crawlers by default. There is also a new option for the page to return code HTTP 402 (“Payment required”) and charge for access. Of course, Cloudflare will be an intermediary, which gives it significant control and financial power.

Moreover, it could spark an era of “dark crawling”, which will undoubtedly lead to cat-and-mouse games of crawer detection.

AI-assisted coding for teams that can’t get away with vibes

A very nice guide to using AI agents for coding efficiently. It’s brief, but it gives the idea where to dig.

Google search head reveals “game system” approach as AI mode begins advertising rollout

Google will show ads in its AI mode. An entirely expected move from the search giant, given that AI search and other features break the traditional ads model. It will be interesting to see how those new ad integration techniques will evolve, and what the new generation of ad blockers will look like.

How Long Contexts Fail

How to Fix Your Context

Long context is your friend… when we are talking about summarization and retrieval. For agentic workflow it is often detrimental due to reasons such as:

1. Context poisoning, where the model hallucinates and messes with its own context. The ripples are powerful and they die slowly;

2. Context distraction, where the model starts to repeat itself instead of trying new strategies;

3. Context confusion, which happens when one gives the model too many tools (sometimes 2 is too many);