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Actually, AI makes crypto better. Ethlabs Week 16.
Ethlabs' 16th weekly update argues that advancing AI is an opportunity for Ethereum rather than only a threat, pointing to Francesco D'Amato's formal verification research and the promise of pairing agents with formal models. It also covers Gnosis Chain's bridges going live with the Fast Confirmation Rule, Quick Slots being Considered for Inclusion in the Hegotá upgrade, and Frame Transactions and FOCIL scheduled for Hegotá.
6 min · 1,482 words
Cendyne recounts being the last engineer at a company that bet on marketed LLM intelligence to replace engineering headcount, reflecting on confidence theater, M&A incentives, and what "Fable/Mythos tier" AI meant for the job.
4 min · 912 words
Ollie Green argues that after AI companies got away with large-scale IP use for training, AI's ability to decompile, understand and recompose software and other knowledge work is now driving the value of prior work toward zero, collapsing the scarcity that intellectual property was built to protect.
2 min · 442 words
Rich Whitehouse argues that "artificial intelligence" is a poor label for frontier generative models, criticizes large language models and the companies building them on grounds including copyright, labor and societal harm, and urges readers to stay aware of what they are participating in.
14 min · 3,304 words
Nish Tahir explains "system one" decision models like TypeSafe AI's Jev, which answer in a single forward pass by masking the vocabulary to a fixed set of options, then walks through fine-tuning a small model on multiple-choice data and calibrating its confidence with temperature scaling, with a companion GitHub repo.
4 min · 1,019 words
Taylor Swift or Beyoncé? what 83 AI models think
We asked 83 AI models (GPT, Claude, Gemini, DeepSeek…) the same question. 89% picked Beyoncé. See every answer, who searched the web, and who dissented.
10 min · 2,392 words
Please Stop the Slop: What AI Slop Is and How to Spot It
Tejas Kumar defines AI slop—cheap machine-generated content with no human value—after it showed up in the comments under his own post, explains how to spot it, cites the research behind its spread, and argues being human still wins, closing with a petition.
16 min · 3,572 words
Last weekend marked the four-year anniversary of Ludicon. I started Ludicon because I believed that working independently would let me do my best work. Building software on my own, I can move fast, take risks, and focus on problems others don’t consider practical, or slow down and go deep into rabbit holes without having to justify myself. I’m happy with the quality of the work I’ve produced, excited about what is yet to come, but disappointed with its commercial success so far. In retrospect, 2022 was not a particularly good time to start a game middleware business. In…
4 min · 854 words
What I've been seeing lately (in software)
A personal survey of software culture amid generative AI: normalizing pro-human discussion, exacting design and organizing, the job question, beautiful work, and a growing European push toward self-hosted and public-sector open source.
4 min · 848 words
Which programming language should a beginner learn in 2026? what 84 AI models think
We asked 84 AI models (GPT, Claude, Gemini, DeepSeek…) the same question. 100% picked Python. See every answer, who searched the web, and who dissented.
9 min · 2,175 words
Attack of the Vibe Coded Photoshop Clones
Shokunin Studio tracks the dozen-plus AI 'vibe coded' clones of Photoshop and other Adobe, Microsoft, Avid and Autodesk apps, compares them to earlier waves of automated cloning, and argues vibe-cloned piracy undermines the incentive to build original creative software.
7 min · 1,496 words
Geoffrey Huntley argues that teams who cannot make time to experiment with AI agents and loop engineering are effectively preparing themselves to be replaced by those who do.
10 min · 2,250 words
Harness²: Recursive Agent Harnessing for an Open WorldRecursive Agent Harnessing for an Open World — Google Cloud AI Research & Northwestern
Google Cloud AI Research and Northwestern introduce Harness², an open-source framework that recursively improves an AI agent's execution harness (prompts, tools, memory) via Propose–Probe–Compose without ground-truth verifiers, gaining up to 11.5 points on WorkBuddy-Bench.
13 min · 3,004 words
Who Taught the Machines Mathematics?
Nisheeth Vishnoi reflects on OpenAI releasing more than seven hundred AI-produced mathematical manuscripts: on the human knowledge these systems were built from, credit and attribution, and what becomes of mathematics as a human practice.
10 min · 2,194 words
What Is poppy.json? The /.well-known File That Tells AI Agents How to Work With Your Company
A walkthrough of poppy.json, the Personal Agent Protocol (PAP/Poppy) discovery file at /.well-known/poppy.json: required fields for organization, OAuth, agent/API/web interfaces and extensions, plus a fictional worked example of Draft 0.1.
4 min · 888 words
The Feasibility of a Hardwired Pause of Frontier AI Training
A 26-member Working Group on AI Pause Feasibility, organized by UC Berkeley's William Fithian and Wesley H. Holliday, assesses whether a decade-long, mutually verified international pause of frontier AI training is feasible by halting production of training-capable chips and phasing in inference-only chips, and concludes it could be implemented if world leaders wanted to pause.
11 min · 2,635 words
Prime Intellect describes how Prime Agent orchestrated a swarm of over 2,000 agents across 10,000+ Prime Sandboxes and 200 billion tokens to rewrite itself from TypeScript to Rust in two weeks, covering why Rust, finite-state-machine orchestration, architecture redesign, and cold start, memory and install-size gains.
9 min · 2,133 words
What mathematicians should know about the Lean Theorem Prover: questions of reliability and AI
In a guest post on Terence Tao's blog, Thomas Hales explains how formal proof in the Lean theorem prover works, what can and cannot go wrong with its trusted kernel, axioms, definitions and autoformalized statements, and what mathematicians should check before trusting AI-assisted formal proofs.
16 min · 3,614 words
Fernando Borretti argues that individual intellectual activity can only be sustained inside a community of other humans, and that AI is dissolving those communities in software engineering and beyond, making private intellectual work, from reading papers to writing essays and open source, feel superfluous.
6 min · 1,414 words
Microsoft-Decision-1: Our model for fast decision-making
Microsoft introduces Microsoft-Decision-1, a decision-scoring model in Foundry built to return structured outputs software can act on immediately, and reports that it leads on latency and quality across structured decision tasks against LLMs and other decision models.
6 min · 1,358 words