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willmarquis

24 karma · joined August 29, 2024

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willmarquis··on Ex-GitHub CEO launches a new developer platform for AI agents
The thread is missing the forest for the trees. The interesting bet here isn't git checkpoints—it's that someone is finally building the observability layer for agent-generated code.

Most agent frameworks (LangChain, Swarm, etc.) obsessed over orchestration. But the actual pain point isn't "how do I chain prompts"—it's "what did the agent do, why, and how do I audit/reproduce it?"

The markdown-files-in-git crowd is right that simple approaches work. But they work at small scale. Once you have multiple agents across multiple sessions generating code in production, you hit the same observability problems every other distributed system hits: tracing, attribution, debugging failures across runs.

The $60M question is whether that problem is big enough to justify a platform vs. teams bolting on their own logging. I'm skeptical—but the underlying insight (agent observability > agent orchestration) seems directionally correct.

willmarquis··on Claude 4
Do you know when this will be available on Basalt? They didn't communicate on it yet
willmarquis··on Claude 4
Waiting for the ranking on the lmsys chat arena! The only source of truth
willmarquis··on 32 bits that changed microprocessor design
Bellmac-32 went 32-bit CMOS when everyone else was still twiddling 8-bit NMOS, then got shelved before the afterparty. IEEE giving it a milestone in 2025 is basically a lifetime achievement trophy for the domino-logic DNA inside every phone SoC today late, but deserved
willmarquis··on The Future of Flatpak
Flatpak’s biggest bug isn’t in the code, it’s the bus factor.

> Tons of features are stuck in merge-request limbo because there just aren’t enough reviewers, and if we don’t swap some “+1”s for actual PR reviews (or funding), we’ll be shipping apps in 2030 with a sandbox frozen in 2024 while everything else rides OCI.

willmarquis··on For algorithms, a little memory outweighs a lot of time
This is just a reminder that memory isn’t just a constraint, it’s a resource.
willmarquis··on DDoSecrets publishes 410 GB of heap dumps, hacked from TeleMessage
Exposing unauthenticated /heapdump endpoints in production is a rookie mistake-especially for a service handling sensitive government comms. The presence of MD5 hashes and legacy tech like JSP just adds to the picture of poor security hygiene. This breach is a textbook case of why defense-in-depth and regular audits are non-negotiable.
willmarquis··on Have I Been Pwned 2.0
Really impressive evolution of a crucial service. The architectural and UX improvements are well thought out, especially the focus on resilience and scalability. Love the transparency around the decision-making process, too-Troy’s commitment to keeping HIBP fast, free, and useful is a great example of public-interest software done right. The migration to .NET 8 and use of Cloudflare for caching shows how mature and modern the stack is becoming.
willmarquis··on Is-even-ai – Check if a number is even using the power of AI
Finally, someone had the courage to disrupt the tyranny of the modulo operator. Who needs n % 2 === 0 when you can invoke a large language model and incur network latency, token limits, and API costs to answer the age-old question: is this number even? Truly, we’re living in the future.
willmarquis··on A shower thought turned into a Collatz visualization
Interesting take. The visualization of the inverse tree highlights just how sparse the “preimage space” is under Collatz iterations. The idea that this sparsity contributes to the apparent randomness is compelling. I’m curious whether modeling the process modulo powers of 2 and 3, or via 2-adic analysis, could formalize some of these heuristic observations. Also, the assumption that most numbers “fall off” rapidly aligns with empirical behavior, but it’s still not clear how to bound exceptional trajectories.
willmarquis··on Score your prompt quality – Below 50% should not go in production
I got 45% I absolutely must improve it.
willmarquis··on Useful handbook for building AI features (from OpenAI, Microsoft, Mistral etc.)
Hey guys!

I just launched “The PM’s Handbook for Building AI Features”, a comprehensive playbook designed to help product managers and teams develop AI-driven features with precision and impact.

The guide covers: • Practical insights on prompt engineering, model evaluation, and data management • Case studies and contributions from companies like OpenAI, Microsoft, Mistral AI, Gorgias, PlayPlay and more • Tools, processes, and team structures to streamline your AI development

Here is the guide (no sign in required) : https://handbook.getbasalt.ai/The-PM-s-handbook-for-building...

If you’re building with AI or planning to, this playbook is packed with actionable advice and real-world examples.

Check it out and let us know what you think!