2025-08-23 06:24:54
ChatGPT release notes: Project-only memory
The feature I've most wanted from ChatGPT's memory feature (the newer version of memory that automatically includes relevant details from summarized prior conversations) just landed:With project-only memory enabled, ChatGPT can use other conversations in that project for additional context, and won’t use your saved memories from outside the project to shape responses. Additionally, it won’t carry anything from the project into future chats outside of the project.
This looks like exactly what I described back in May:
I need control over what older conversations are being considered, on as fine-grained a level as possible without it being frustrating to use.
What I want is memory within projects. [...]
I would love the option to turn on memory from previous chats in a way that’s scoped to those projects.
Note that it's not yet available in the official chathpt mobile apps, but should be coming "soon":
This feature will initially only be available on the ChatGPT website and Windows app. Support for mobile (iOS and Android) and macOS app will follow in the coming weeks.
Via @btibor91
Tags: ai, openai, generative-ai, chatgpt, llms
2025-08-23 06:07:25
The latest model from DeepSeek, a 685B monster (like DeepSeek v3 before it) but this time it's a hybrid reasoning model.
DeepSeek claim:
DeepSeek-V3.1-Think achieves comparable answer quality to DeepSeek-R1-0528, while responding more quickly.
Drew Breunig points out that their benchmarks show "the same scores with 25-50% fewer tokens" - at least across AIME 2025 and GPQA Diamond and LiveCodeBench.
The DeepSeek release includes prompt examples for a coding agent, a python agent and a search agent - yet more evidence that the leading AI labs have settled on those as the three most important agentic patterns for their models to support.
Here's the pelican riding a bicycle it drew me (transcript), which I ran from my phone using OpenRouter chat.
Tags: ai, prompt-engineering, generative-ai, llms, drew-breunig, pelican-riding-a-bicycle, llm-reasoning, deepseek, llm-release, openrouter, coding-agents, ai-in-china
2025-08-23 05:36:24
Mississippi's approach would fundamentally change how users access Bluesky. The Supreme Court’s recent decision leaves us facing a hard reality: comply with Mississippi’s age assurance law—and make every Mississippi Bluesky user hand over sensitive personal information and undergo age checks to access the site—or risk massive fines. The law would also require us to identify and track which users are children, unlike our approach in other regions. [...]
We believe effective child safety policies should be carefully tailored to address real harms, without creating huge obstacles for smaller providers and resulting in negative consequences for free expression. That’s why until legal challenges to this law are resolved, we’ve made the difficult decision to block access from Mississippi IP addresses.
— The Bluesky Team, on why they have blocked access from Mississippi
2025-08-23 01:30:34
too many model context protocol servers and LLM allocations on the dance floor
Useful reminder from Geoffrey Huntley of the infrequently discussed significant token cost of using MCP.Geoffrey estimate estimates that the usable context window something like Amp or Cursor is around 176,000 tokens - Claude 4's 200,000 minus around 24,000 for the system prompt for those tools.
Adding just the popular GitHub MCP defines 93 additional tools and swallows another 55,000 of those valuable tokens!
MCP enthusiasts will frequently add several more, leaving precious few tokens available for solving the actual task... and LLMs are known to perform worse the more irrelevant information has been stuffed into their prompts.
Thankfully, there is a much more token-efficient way of Interacting with many of these services: existing CLI tools.
If your coding agent can run terminal commands and you give it access to GitHub's gh tool it gains all of that functionality for a token cost close to zero - because every frontier LLM knows how to use that tool already.
I've had good experiences building small custom CLI tools specifically for Claude Code and Codex CLI to use. You can even tell them to run --help to learn how the tool, which works particularly well if your help text includes usage examples.
Tags: github, ai, prompt-engineering, generative-ai, llms, model-context-protocol, coding-agents, claude-code, geoffrey-huntley
2025-08-22 05:44:19
Most classical engineering fields deal with probabilistic system components all of the time. In fact I'd go as far as to say that inability to deal with probabilistic components is disqualifying from many engineering endeavors.
Process engineers for example have to account for human error rates. On a given production line with humans in a loop, the operators will sometimes screw up. Designing systems to detect these errors (which are highly probabilistic!), mitigate them, and reduce the occurrence rates of such errors is a huge part of the job. [...]
Software engineering is unlike traditional engineering disciplines in that for most of its lifetime it's had the luxury of purely deterministic expectations. This is not true in nearly every other type of engineering.
— potatolicious, in a conversation about AI engineering
Tags: ai, hacker-news, software-engineering, generative-ai
2025-08-22 00:49:14
I was at a leadership group and people were telling me "We think that with AI we can replace all of our junior people in our company." I was like, "That's the dumbest thing I've ever heard. They're probably the least expensive employees you have, they're the most leaned into your AI tools, and how's that going to work when you go 10 years in the future and you have no one that has built up or learned anything?
— Matt Garman, CEO, Amazon Web Services
Tags: ai-ethics, careers, generative-ai, aws, ai
