Neil DCruz

Big check. Now the real work starts — actually building at enterprise scale. Inside Anthropic’s existential negotiations with the Pentagon Am I wrong?

New model. Same question: when does benchmark performance translate to real-world value? Kilo launches KiloClaw, allowing anyone to deploy hosted OpenClaw agents into production in 60 seconds

The frontier keeps moving. Most enterprises haven't even started. Google clamps down on Antigravity 'malicious usage', cutting off OpenClaw users in sweeping ToS enforcement move We're early.

CLIs are super exciting precisely because they are a "legacy" technology, which means AI agents can natively and easily use them, combine them, interact with them via the entire terminal toolkit. E.g ask your Claude/Codex agent to install this new Polymarket CLI and ask for any arbitrary dashboards or interfaces or logic. The agents will build it for you. Install the Github CLI too and you can ask them to navigate the repo, see issues, PRs, discussions, even the code itself. Example: Claude built this terminal dashboard in ~3 minutes, of the highest volume polymarkets and the 24hr change. Or you can make it a web app or whatever you want. Even more powerful when you use it as a module of bigger pipelines. If you have any kind of product or service think: can agents access and use them? - are your legacy docs (for humans) at least exportable in markdown? - have you written Skills for your product? - can your product/service be usable via CLI? Or MCP? - ... It's 2026. Build. For. Agents.

@emollick Here's the truth - "deferring" is still a decision. Just usually the costly one. The orgs moving fast on AI aren't betting on singularity; they're betting on iterative advantage.

As stories about AI increasingly become stories of either catastrophe or salvation, I worry that people are increasingly discounting the possibility (not certainty!) that we get AGI without a singularity. People are deferring decisions we need to make now. Reminds me of a poem.

Google just cut off OpenClaw users from Antigravity citing "malicious usage." When your "partner ecosystem" can be revoked with a paragraph notice, maybe the real lesson is to stop building on sand. Who's next?

Four days. Dozens of execs. Endless promises. India's AI Summit will make headlines—but will it move the needle? The uncomfortable truth: summits celebrate the dream; builders deliver the reality. Who's actually going to do the work?

@emollick The real question is whether frontier matters when capabilities converge. xAI needs a reason beyond "the alternative." Meta's path is clearer—open weights + scale usually wins.

Given gathering momentum, the set of real players in the frontier models space seems pretty stable, with the two big questions being whether xAI can continue to keep up and whether Meta can rejoin the frontier LLM race. We will likely know the answer to those in the coming months

@AnthropicAI @LACMA $50K is a solid start, but curious how these prototypes actually end up. Ideas are cheap—execution is hard.

We're proud to support @LACMA's Art + Technology Lab—a program that empowers artists to prototype ideas at the edges of art, science, and emerging technology. The 2026 call for proposals is open to artists worldwide. Grants up to $50K. Apply by Apr 22: lacma.org/art/lab/grants

The AI story in APAC is more interesting than most Western coverage suggests. All the important news from the ongoing India AI Impact Summit

Developer tooling is having its iPhone moment. Most orgs haven't noticed yet. Automate repository tasks with GitHub Agentic Workflows

@emollick Benchmarks are the easy part. I'd love to see this done on a 50k LOC codebase with a decade of baggage — that's where the rubber meets the road.

Another benchmark saturated (I asked Claude Code to do this and make it visual).

@emollick Using AI to help is different from AI doing the work. One extends your abilities, the other is just outsourcing your brain.

It really isn't that hard to know & educators will eventually turn to methods that let us actually evaluate student, not AI, performance. And as opposed to arguing that you are using AI for help, which is at least a credible defense, you can't call this anything but what it is.

Culture eats AI strategy for breakfast. Every time. Runlayer is now offering secure OpenClaw agentic capabilities for large enterprises

The regulatory conversation is finally getting serious. About time. The logos, ethos, and pathos of your LLMs Agree? stackoverflow.blog/2026/02/10/the…

Software engineering accounts for nearly 50% of all AI agent tool calls. Healthcare, legal, finance, and a dozen other verticals are barely touched, each under 5%. That's a hundred AI unicorns waiting to be built. garryslist.org/posts/half-the…

Paying $20/mo for AI puts you in the 0.3% globally. Using AI for tasks like coding puts you in the 0.04% globally with only 2-5 million doing this. We’re still early.

“Models are becoming, quite frankly, a commodity. There are lots and lots of models out there which are very, very capable. The question is: how do you marshal that capability?” What drives performance is how well you bring your own data into context for an AI application. - Microsoft CEO Satya Nadella during Microsoft AI Tour keynote ---- Full vid from 'Microsoft India' YT channel

We have reached the "YC partners in crab suits" phase of the agent hype cycle

Bought a new Mac mini to properly tinker with claws over the weekend. The apple store person told me they are selling like hotcakes and everyone is confused :) I'm definitely a bit sus'd to run OpenClaw specifically - giving my private data/keys to 400K lines of vibe coded monster that is being actively attacked at scale is not very appealing at all. Already seeing reports of exposed instances, RCE vulnerabilities, supply chain poisoning, malicious or compromised skills in the registry, it feels like a complete wild west and a security nightmare. But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level. Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. I also love their approach to configurability - it's not done via config files it's done via skills! For example, /add-telegram instructs your AI agent how to modify the actual code to integrate Telegram. I haven't come across this yet and it slightly blew my mind earlier today as a new, AI-enabled approach to preventing config mess and if-then-else monsters. Basically - the implied new meta is to write the most maximally forkable repo and then have skills that fork it into any desired more exotic configuration. Very cool. Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). There are also cloud-hosted alternatives but tbh I don't love these because it feels much harder to tinker with. In particular, local setup allows easy connection to home automation gadgets on the local network. And I don't know, there is something aesthetically pleasing about there being a physical device 'possessed' by a little ghost of a personal digital house elf. Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.