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Effective context management is crucial in agentic coding to avoid confusing the agent and driving up token costs.

A large part of human memory is learning to forget. If our brain remembered everything perfectly, it would get stuffed with irrelevant facts, making it harder to retrieve relevant information. This is what makes implementing memory for AI agents so hard - the ability to differentiate what is truly relevant is absolutely needed or else the memory just fills up with junk.

We are already there. I was listening to a talk yesterday and the first question was "how long before we are allowed to install and run local coding models?"

Axios, one of the most widely used JavaScript libraries, has been compromised in a supply chain attack.

The $200/month pricing for Claude Code may seem expensive, but it's actually heavily subsidized compared to the true cost of running AI models.

Claude Code may end up becoming the personal agentic framework that I've been looking for.

In the past when I needed some agentic behaviour (example: answer questions based on some documents), I used to look at hand rolling a solution. It's time consuming and not particularly easy to build and …

The LiteLLM Python package was compromised in a supply chain attack, with a malicious file targeting developers' secret keys.

Whoa, whoa, whoa. The darling of the Python ecosystem, the team that brought us ruff, uv, ty and pyx and forever changed the python tooling landscape is now joining OpenAI.

Pretty sure all these tools will be deeply integrated into Codex, which is good news for python developers.

Also a …

Sometimes old is gold.

One of the key aspects of agentic coding is to have a good validation harness in place. Now, I've really seen three levels that developers go through when it comes to validation harness:

First, many devs simply not have a validation harness. You ask the agent …