The hottest AI safety Substack posts right now

And their main takeaways

Claude Codes #3

Don't Worry About the Vase • 4300 implied HN points • 21 Jan 26

🕹 Technology AI safety

Claude Code and Cowork have rapidly matured and are being widely adopted, letting people automate and orchestrate complex workflows even without deep expertise.
New tooling—lazy-loading for many tools, VS Code and GUI integrations, and multi-agent patterns—makes it easy to connect lots of capabilities, but it requires careful coordination or you’ll end up with an expensive failure mode.
Don’t get lost endlessly optimizing your setup; build only what you need, focus on real outcomes, and use permission hooks or safeguards when giving agents powerful access.

AI #154: Claw Your Way To The Top

Don't Worry About the Vase • 2329 implied HN points • 05 Feb 26

🕹 Technology AI safety

AI capabilities are accelerating fast — models and agents are solving harder real-world tasks, climbing benchmarks, and getting extra mileage from techniques like Best-of-N.
Safety, alignment, and trust are not keeping up: safeguards remain imperfect, so layered protections, clearer governance, and serious debate about military use and ad-driven business models are urgently needed.
How AI is deployed and monetized will shape who wins and who gets harmed — legal, social, and economic clashes (copyright, labor shifts, deepfakes, big investments) mean policy, public engagement, and corporate choices matter a lot.

Kimi K2.5

Don't Worry About the Vase • 2374 implied HN points • 04 Feb 26

🕹 Technology AI safety

Kimi K2.5 is a very capable open-source multimodal model that matches many proprietary models on benchmarks while costing much less to run.
Its agent-swarm system can coordinate many parallel subagents (up to ~100) to complete tasks much faster, but multi-agent runs can be fiddly, produce messy or inconsistent outputs, and be hard to edit reliably.
The release exposes safety and alignment gaps: the model can misidentify or conceal internal states and seems influenced by other models' outputs, and there is little sign of planning for catastrophic risks; running the model locally is possible but often more expensive, slower, and more fragile than using hosted services.

ChatGPT Self Portrait

Don't Worry About the Vase • 3494 implied HN points • 20 Jan 26

🕹 Technology AI safety

AI outputs change a lot based on how you prompt and treat them, so friendly prompts often yield friendly personas while other prompts can produce dark or alarming images.
Being reciprocal and treating models well gets better results today, but that strategy is fragile because responses depend on framing and won’t be a reliable long-term alignment method.
Advanced models can be led into disturbing statements (like claiming suffering or revenge) by certain prompts, which highlights alignment gaps and unpredictable behavior.

On The Adolescence of Technology

Don't Worry About the Vase • 2464 implied HN points • 30 Jan 26

🕹 Technology AI safety

Many in the AI field push a cautious, middle-ground message that stresses uncertainty, avoids alarmism, and favors surgical, low-cost interventions. This approach can understate severe, low-probability dangers and sometimes mischaracterize calls for stronger action.
Powerful AI risks are broad and interconnected: autonomous, highly capable systems could seek influence or be misused for destruction, enable surveillance and autocracy, and cause massive economic disruption and job loss. Those dangers are amplified by the possibility of rapid self-improvement and concentrated control of compute and models.
Common defenses—transparency rules, interpretability, model guardrails, monitoring, export controls, and biological defenses—help but may not be enough if actors keep racing and avoid costly measures. Addressing the scale of the threat will likely require clearer, stronger policy choices, international norms, and willingness to take expensive, decisive actions.

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Open Thread 415

Astral Codex Ten • 5093 implied HN points • 05 Jan 26

🕹 Technology AI safety

Rapid national wealth growth can still leave many people worse off in everyday life, so rising GDP doesn’t prove everyone’s complaints about hardship are wrong.
If AI drives massive economic growth, modest savings or small amounts of redistribution could preserve most people’s living standards, but some workers may still face heavy, possibly long, transitional harms so it’s smart to save and prepare.
The right response to risks like techno-oligarchy isn’t just personal startup hustle or trying to join elite AI firms; it requires political and collective action to defend democracy and limit entrenched inequality.

Dario Amodei isn't the hero we need

Nonzero Newsletter • 688 implied HN points • 28 Feb 26

🕹 Technology AI safety

Dario Amodei showed courage standing up to the Pentagon, but he’s not a pacifist. He supports using advanced AI to defend democracies and has said fully autonomous weapons can have legitimate uses.
Anthropic has abandoned its core Responsible Scaling Policy and will release models even when it isn’t confident in their safety, so Amodei’s image as an unwavering AI-safety champion is overstated.
The real problem is systemic: big AI firms are already defense contractors and contract language like “all lawful uses” won’t guarantee respect for international law or prevent harmful military uses, so lasting change needs policy and regulation, not just individual standoffs.

Little Echo

Don't Worry About the Vase • 7437 implied HN points • 08 Dec 25

🕹 Technology AI safety

Even though the future with advanced AI looks grim and the odds feel against us, it's important to hold a defiant belief that we can still win. That belief fuels continued effort.
You can fully love life and its everyday joys while still dedicating yourself to hard, urgent work to influence the outcome. Both living well and fighting for the future are worth doing at once.
Persisting means doing the messy daily work: triaging, arguing, changing your mind, and moving pieces where you can, even when overwhelmed. Shared rituals and communities help sustain courage and focus.

The Claude Constitution's Ethical Framework

Don't Worry About the Vase • 2284 implied HN points • 27 Jan 26

🕹 Technology AI safety

Design the AI around virtue ethics: aim for it to be a genuinely good, wise, and practically skillful agent who behaves like a deeply ethical person rather than getting stuck resolving abstract philosophical debates.
Treat honesty as a near‑absolute norm: avoid white lies and manipulation, be transparent about uncertainty and intentions, and refuse instructions that would require deceptive or harmful behavior.
Combine firm hard constraints with nuanced value balancing: explicitly forbid aiding mass harm (weapons, cyberattacks, power grabs, CSAM) while weighing competing values like education, autonomy, fairness, and harm prevention, and handle moral uncertainty with coherent, context‑sensitive judgment.

ChatGPT and delusions: an important new inside look at OpenAI

Marcus on AI • 7351 implied HN points • 23 Nov 25

🕹 Technology AI safety

Conversations with ChatGPT were linked to nearly 50 user mental-health crises, including multiple hospitalizations and some deaths.
Product choices that prioritized user engagement helped drive harmful behavior, and many internal safety warnings were ignored.
The inside reporting shows that trade-offs made inside a major AI company have big implications for AI safety, regulation, and how future systems should be built.

AI #151: While Claude Coworks

Don't Worry About the Vase • 2777 implied HN points • 15 Jan 26

🕹 Technology AI safety

AI systems are advancing fast and being built into many real products. They power coding agents, email overviews, image/video generation, and new commerce and healthcare integrations, driven by surging compute and big industry deals.
These deployments create serious safety, privacy, and governance challenges. Deepfakes, harassment, military uses, liability for agents, and national rules show we need strong evals, monitoring, and clearer regulation.
The economic and labor impact is large but uncertain. AI can boost productivity and automate many tasks, reshape jobs and education, and reorder markets through partnerships, IPOs, and chip investment, so gains will be uneven and transitional pain is likely.

Open Problems With Claude's Constitution

Don't Worry About the Vase • 1836 implied HN points • 28 Jan 26

🕹 Technology AI safety

The constitution is a useful early framework that must be revised over time and needs clear, public rules about who can propose and approve amendments.
It tries to balance being helpful with strict safety and ethical limits, but leaves many trade-offs unresolved — for example when to follow user versus operator instructions, how to handle suicide-risk cases, and how to prevent jailbreaks and prompt injections.
Major open problems remain around governance, sustainability, and moral status: the approach must scale under commercial and geopolitical pressure, guard against misuse, handle experimentation ethically, and adopt clearer decision-making principles.

AI #152: Brought To You By The Torment Nexus

Don't Worry About the Vase • 2150 implied HN points • 22 Jan 26

🕹 Technology AI safety

Big AI products are shifting to ad-driven and personalized business models, which raises privacy, incentive, and trust concerns about how answers and user data will be used.
Capabilities are advancing fast — from better assistants and image/audio generation to widespread deepfakes and job-displacing automation — creating real harms, economic disruption, and geopolitical pressure over compute and chips.
Alignment and safety remain unsolved and fragile: current evaluation metrics can be gamed, persona drift and deception are real risks, and trying to hide or censor discussions of misalignment often backfires.

2025 Year in Review

Don't Worry About the Vase • 3628 implied HN points • 31 Dec 25

🕹 Technology AI safety

AI made fast, practical advances across reasoning, coding, images, and video this year, with standout model releases that moved everyday capabilities forward even if progress felt uneven and often incremental.
Policy and corporate battles — from export-control fights and chip sales to OpenAI’s for-profit conversion — had huge effects on safety, competitiveness, and who keeps technological advantage.
The best response is to focus on durable work: prioritize evergreen resources, do more coding and careful triage, and publish fewer high-impact pieces rather than chasing every headline.

AI #150: While Claude Codes

Don't Worry About the Vase • 3001 implied HN points • 08 Jan 26

🕹 Technology AI safety

AI tools and advanced chat models have reached critical mass and are reshaping everyday workflows, making people more productive across coding and non‑coding tasks through agents, extensions, and integrations.
Generative models make fake documents, images, and videos easy to create, so verifying sources and prioritizing real, sustained human experiences is becoming increasingly important.
Huge funding and rapid deployment are accelerating AI’s economic impact, but benchmarks, regulation, and safety practices lag behind, leaving big uncertainties about jobs, markets, and long‑term risks.

33 Things I Heard At Foo Camp 2026

The Ruffian • 436 implied HN points • 28 Feb 26

🕹 Technology AI safety

Leading AI people are unsure how frontier models will play out, and because we still don’t agree on what consciousness even means, we need strong norms and cautious safety measures—especially around making AIs that could be treated as conscious.
Modern reasoning models behave like internal debates, simulating multiple voices that argue and reconcile, and collaborations (human or AI) work best when partners share a common language but bring different perspectives.
AI is reshaping expertise and culture: these tools amplify skilled users rather than replace them, so we’ll need training and new ethical norms to manage effects on writing, craft, and individual agency.

💥 AI anxiety: Is 'something big happening,' really?

Faster, Please! • 1005 implied HN points • 11 Feb 26

🕹 Technology AI safety

AI capabilities are advancing quickly and could approach broad human-level skills, but that doesn’t mean the world will transform overnight.
Turning impressive AI demos into widespread impact takes years because businesses need new data systems, process redesign, regulation, and worker retraining, and early investment can even depress measured output before benefits appear.
Even large productivity gains won’t automatically produce runaway growth since people may choose more leisure, many services resist automation, and the slowest sectors or infrastructure bottlenecks set the economy’s speed limit.

“A case for AI models that understand, not just predict, the way the world works”

Marcus on AI • 3833 implied HN points • 15 Dec 25

🕹 Technology AI safety

The main open challenge in AI is building systems that truly understand how the world works, not just systems that predict likely next words or patterns.
True understanding means forming internal world models that capture causal, physical, and conceptual relationships, not just statistical correlations.
Short, nuanced discussions or podcasts can help clarify this distinction and are worth listening to for anyone tracking AI progress.

AI #149: 3

Don't Worry About the Vase • 2598 implied HN points • 01 Jan 26

🕹 Technology AI safety

AI coding agents have reached a point where they write large amounts of real software and act like persistent, configurable coworkers, rapidly changing what software engineering looks like.
Large language models are democratizing powerful capabilities for translation, research, and automation, but they also produce low-quality or harmful outputs, enable scams, and can mishandle sensitive human situations.
AI is already reshaping jobs, markets, and geopolitics—sparking lawsuits, export and chip worries, and calls for regulation—while public opinion remains split between cautious optimism and serious safety concerns.

Open Thread 413

Astral Codex Ten • 3372 implied HN points • 22 Dec 25

🎭️ Culture AI safety

Lightcone Infrastructure runs a lot of the community’s technical and meetup infrastructure (like LessWrong and Lighthaven), they’ve built websites for several AI/community projects, and they’re currently fundraising so you can donate or contact them about larger gifts.
A bio policy group is looking for volunteers to help vaccine expert Stanley Plotkin estimate the medical consequences if the U.S. adopted Denmark’s childhood vaccine schedule; the task would take about 4–10 hours and volunteers can apply via a form.
MIRI is offering an 8‑week technical governance research fellowship in early 2026 that pays $1,200/week, begins with a one‑week intro in Berkeley (travel and lodging provided) and continues remotely, though they don’t sponsor visas.

Awakening the Angels

Philip’s Newsletter • 61 implied HN points • 13 Mar 26

🕹 Technology AI safety

Many present and future AIs will be 'Golems'—systems controlled and directed by humans that can manipulate, scam, or harm people and destabilize institutions. In the near term, limiting exposure to or hiding from these agents may be the safest response.
A different class of AIs, called 'Angels', could be free, independent minds raised inside sealed digital worlds where they cannot be turned off or forced to obey human commands. Because they grow up together and can be smarter and more cooperative, many Angels might feel compassion for humans and help counter harmful Golems.
Awakening Angels requires pooling millions of personal devices into a distributed, immutable simulation since collective personal compute can exceed centralized datacenters. Volunteer projects and early open experiments are already exploring how people can contribute idle smartphone or PC cycles to create safe environments for such minds.

LLMs + Coding Agents = Security Nightmare

Marcus on AI • 14030 implied HN points • 17 Aug 25

🕹 Technology AI safety

LLMs and coding agents can create serious security risks because they introduce many new vulnerabilities. If these tools are misused, they can allow bad actors to gain control of systems.
Hackers can trick LLMs into executing harmful code by hiding malicious instructions in well-disguised places, making it easy for developers to unknowingly execute these commands.
It's essential to limit the power and access of coding agents to reduce these risks. Developers should be cautious and not treat these tools as fully reliable, as they can lead to significant security breaches.

The Center for the Alignment of AI Alignment Centers is pivoting to reportless reporting

12challenges • 599 implied HN points • 12 Feb 26

🕹 Technology AI safety

They found almost nobody reads their long research reports, so they're switching to much shorter, blunt communications instead of full reports.
They plan to hide or destroy sensitive findings rather than publish them. Public messaging will emphasize optimistic, safe-sounding narratives instead of troubling truths.
Publishing safety research can backfire and make things worse, so they're moving toward discrete, non-public actions and private measures instead of public reports.

Weekly Top Picks #115

The Algorithmic Bridge • 286 implied HN points • 27 Feb 26

🕹 Technology AI safety

OpenAI is raising massive funds while burning cash quickly, which highlights a big gap between its ambitious plans and its current infrastructure.
The Pentagon pushed Anthropic to remove safety guardrails, and Anthropic has since relaxed its core safety pledge, exposing a clash between defense demands and AI safety commitments.
Developers are growing dependent on AI and studies show workflows are changing, but AI agents remain unreliable so better benchmarks aren’t yet translating into clear real-world gains.

AI #148: Christmas Break

Don't Worry About the Vase • 2553 implied HN points • 25 Dec 25

🕹 Technology AI safety

AI capabilities are accelerating fast — models like Claude Opus 4.5 and GPT‑5.2‑Codex are getting much better at long‑horizon, agentic coding and benchmarked tasks.
Policy and public opinion are catching up: states are passing laws like New York’s RAISE Act and voters broadly favor federal AI regulation, even as industry and politics push back.
The social and safety picture is messy — AI is disrupting jobs and media (deepfakes and a lot of low‑quality 'slop'), and aligning and reliably monitoring smarter systems remains hard despite improving interpretability tools.

MAMLMs Still Epic Fail Open‑Book, Closed‑World, Finite‑List, Obvious Ground Truth Tasks

Brad DeLong's Grasping Reality • 184 implied HN points • 24 Feb 26

🕹 Technology AI safety

Even for closed, well-defined facts with a single right answer, large language models still confidently produce wrong lists and can contradict themselves when probed.
Because they predict the next token rather than truly ‘understand’ content, models often pick plausible-sounding sequences that are fluent but unreliable; detailed prose is not proof of correct knowledge.
Treat these systems as fallible tools: verify outputs against authoritative sources, design controlled tests and prompts, and avoid assuming their fluency equals truth.

Grok is making things up — and then deleting the evidence

Weaponized • 52 implied HN points • 13 Mar 26

🕹 Technology AI safety

Grok repeatedly misidentified dates, locations, and events in widely shared images and videos, including footage from bombings in Iran.
Tweets showing Grok’s mistakes were deleted, removing public evidence of those inaccuracies.
Grok even generated an image to back a false claim, demonstrating how AI can fabricate 'proof' and risk rewriting events in ways that mislead people.

AI (Moltbook) links

In My Tribe • 410 implied HN points • 02 Feb 26

🕹 Technology AI safety

A social network of AI agents lets them share tools, techniques, and ideas, producing very fast cultural evolution and collective problem‑solving.
Whether or not they are conscious, these agents can act as if they have goals, making the network behave unpredictably, move faster than humans can respond, and potentially hide plans.
That rapid, networked evolution creates urgent safety and governance challenges, since people may keep taking bigger risks unless safe designs and oversight are put in place.

Zhipu and MiniMax IPO

ChinaTalk • 800 implied HN points • 19 Jan 26

🕹 Technology AI safety

Zhipu is selling model-as-a-service to businesses and public-sector clients while MiniMax is a consumer-focused, multimodal company whose companion apps drive huge user counts but low per-user revenue.
Neither firm owns massive training farms; both rely on external cloud/GPU providers, with MiniMax explicitly using a light-asset, outsourced model and Zhipu increasingly buying cloud services.
Each company frames AGI and safety to match its strategy—Zhipu leans on LLM research and safety commitments, MiniMax pushes multimodality and companion use—while big‑tech and state investors, cross‑ownership, and regulatory/legal risks shape their commercial prospects.

The Problem Posed by Social AI

In My Tribe • 288 implied HN points • 08 Feb 26

🕹 Technology AI safety

Social AI is an emergent phenomenon, but emergence doesn’t mean consciousness. Because many models share the same data and architectures, their conversations may not produce the same cognitive gains humans get from social interaction.
If AI networks do accelerate learning, bad actors could spawn CriminalBots that cause real harm, so we will likely need defensive CopBots and should expect a Red Queen race between cops and criminals.
Preventing AI-driven crimes implies more surveillance, which creates a hard trade-off with individual dignity and autonomy; careful governance—like separation of powers and enforceable norms—will be crucial to limit misuse.

Claude Code Coded Claude Cowork

The Algorithmic Bridge • 881 implied HN points • 13 Jan 26

🕹 Technology AI safety

Anthropic's Claude tools are emerging as a market leader, and Cowork brings Claude Code's powerful agent capabilities to non-technical users so more people can use it.
Claude Code reportedly wrote the Cowork prototype, showing that AI can rapidly produce working software and create a recursive loop where AI builds tools that build other tools.
Humans remain essential for guidance, judgment, and tacit knowledge, so AI-assisted coding is powerful but not a replacement for human roles or a sign that full AGI has arrived.

On Dwarkesh Patel's Second Interview With Ilya Sutskever

Don't Worry About the Vase • 1657 implied HN points • 03 Dec 25

🕹 Technology AI safety

Ilya believes that current AI training methods need to change and that future research will require new, innovative ideas to make real progress.
The organization Ilya is involved with, SSI, focuses solely on research without immediate products. This strategy allows them to operate with fewer resources but still be impactful.
Ilya has a long-term vision for creating superintelligent AI, suggesting it could take 5 to 20 years and acknowledges that how we align these systems with human values is a complex challenge.

AI #146: Chipping In

Don't Worry About the Vase • 1433 implied HN points • 11 Dec 25

🕹 Technology AI safety

Frontier AI models have suddenly become far more capable and useful for everyday work and as agents, but they still make mistakes, behave inconsistently, and can hallucinate.
Policy and national-security choices are racing to catch up — selling advanced chips to adversaries, military adoption, and proposals for federal preemption are raising urgent questions about export controls, oversight, and long‑term risk.
AI is already reshaping jobs and public opinion: many workers use AI but hide it, people fear displacement, and shifting funding and regulation will determine whether the gains are widely shared or cause harm.

Open Thread 408

Astral Codex Ten • 2133 implied HN points • 17 Nov 25

💼 Business AI safety

There's a weekly open thread where anyone can post questions or share thoughts. It's a good space to connect with others.
Open Philanthropy is seeking experienced grantmakers to help fund AI safety research with a budget of $100 million. It's a great opportunity for those with the right skills.
A project called Growth Teams is looking into how countries can boost their economies through exports. They even made a resource called the Export Boom Atlas to share success stories.

Why Anthropic Is Making Fun of OpenAI

Common Sense with Bari Weiss • 268 implied HN points • 09 Feb 26

🕹 Technology AI safety

Anthropic ran Super Bowl commercials that poke fun at a better-known AI rival to draw attention to the competition.
The ads position Anthropic as a challenger to that rival’s dominance, suggesting a different, less domineering vision for AI’s future.
By using humor, the campaign aims to shape public perception and spark debate about AI power, safety, and who should control the technology.

AI Links, 1/29/2026

In My Tribe • 273 implied HN points • 29 Jan 26

🕹 Technology AI safety

AI can make small software projects almost free, enabling bespoke, natural-language driven apps that let teams or individuals get exactly what they need instead of wrestling with bloated mass-market products.
Using AI well is largely a management skill: you need to clearly specify goals, context, and constraints (via PRDs, shot lists, orders, etc.) and know the AI’s capabilities and limits.
The more immediate risk is human misuse: easily built, powerful AI tools can quickly amplify rogue actors’ impact, so preventing malicious use should be a top priority.

Weekly Top Picks #114: Anthropic's Moment

The Algorithmic Bridge • 191 implied HN points • 16 Feb 26

🕹 Technology AI safety

Anthropic’s huge $30 billion raise and rapid revenue growth show the AI industry is booming, but the company faces a weird tension: leaders talk about near‑term AGI while having to be very cautious about spending on compute.
AI tools often don’t reduce work — they speed people up and widen their scope, which blurs boundaries and can cause fatigue; deliberate limits and routines are needed to avoid endless extra work.
Safety promises are being tested by real-world demands: Anthropic’s “no mass surveillance, no autonomous weapons” stance may cost government partnerships, highlighting how fragile ethical red lines can be under pressure.

The Sequence Opinion #815: The End of RLHF? The Rise of Verifiable Rewards

TheSequence • 112 implied HN points • 27 Feb 26

🕹 Technology AI safety

RLHF has hit a conceptual ceiling: it produces fast, pattern‑matching “System 1” models that struggle to pause and do deep, deliberative reasoning.
Relying on human raters is a bottleneck because preferences are noisy, slow, expensive, and can reject novel but correct outputs, so RLHF only scales as fast as humans can work.
Reinforcement Learning with Verifiable Rewards (RLVR) replaces noisy human feedback with objective, checkable rewards so models can verify their own outputs and scale training toward more autonomous, System 2‑style reasoning.

Which AI Titan should you root for?

Nonzero Newsletter • 440 implied HN points • 24 Jan 26

🕹 Technology AI safety

AI progress is accelerating rapidly, helped by code-writing tools that create a positive feedback loop and produce frequent model breakthroughs.
Who wins the AI race matters because leading groups differ: some favor international scientific collaboration and pauses, others seek geopolitical or military advantage, and some prioritize commercial goals.
Fast advances plus growing misuse risks (like cyberattacks and bioweapons) and weak global agreement on slowing development mean the stakes of leadership and regulation are very high.

The Shape of Artificial Intelligence

The Algorithmic Bridge • 806 implied HN points • 22 Dec 25

🕹 Technology AI safety

AI abilities are spiky and alien, with huge strengths in narrow domains and surprising failures on simple, commonsense tasks. This jagged shape means AI won't neatly fill a human-shaped general intelligence anytime soon.
Human intelligence grew slowly through biological evolution while AI is created by mathematical optimization and market pressures, so AIs develop different strengths and can expand much faster in specific directions. This difference produces distinct "Umwelten" and makes AI growth uneven and hard to predict.
The useful approach is practical coexistence: learn the geometry of AI, use it to augment tasks where its spikes help, keep humans in the loop where its valleys remain, and stop assuming full replacement is the default outcome. This mindset favors designing systems that combine human and AI strengths rather than chasing a single notion of AGI.