A lot of “startup influencers” on X are just engagement farmers in founder cosplay.
“Drop your startup.”
“Prove you’re not AI.”
“Reply and I’ll give feedback.”
Then they ignore DMs, post slop under the replies, and eventually funnel the audience into some overpriced garbage SaaS product.
They contribute nothing and claim they're building a 'community'.
Follower count is not credibility.
Normies are acting like Claude Tag just reinvented work.
It didn’t.
It made the existing software model more collaborative. Useful? Sure. Game-changing? Not really.
The real shift is when businesses stop adapting themselves to a pile of rigid tools and start building their own connected apps, agents, workflows, and automations around how they actually operate.
That’s what https://t.co/CwjSBbaFCQ is doing.
Most people are celebrating a faster horse because they still haven’t seen the car 🏎️😈
Introducing Claude Opus 4.7, our most capable Opus model yet.
It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.
You can hand off your hardest work with less supervision.
Opus 4.7 can build Lottie Animations.
One prompt via Lottie Creator MCP → 500 particles, each with its own path, easing, and arrival frame. I didn't touch a keyframe.
What should I ask it to build next? Best reply, I'll make it.
Two things happened this week that most people covered separately. They're the same story.
OpenAI upgraded Codex — giving it broader access to control your desktop environment, not just write code in a sandbox.
Meanwhile, Anthropic's CPO quietly left Figma's board, reportedly ahead of launching a competing product in the same space.
Both companies are converging on the same thesis: the highest-value AI product isn't a chatbot. It's an agent that sits on your computer and executes work across your entire environment — browser, files, apps, terminal.
Whoever wins that layer wins the recurring daily usage. That's the real war.
Claude already has Computer Use. Codex is expanding its surface. The next 6 months of releases from both labs should be read through this lens.
Sources:
https://t.co/5gaXWyTCUT
https://t.co/SCn0RFnEh5
Factory hit a $1.5B valuation this week building AI coding agents for enterprise engineering teams.
This isn't "AI autocomplete in your IDE." Factory's product is closer to an autonomous engineering workflow — agents that don't just suggest code, they handle entire task pipelines: issue triage, implementation, testing, PR submission.
The enterprise bet is simple: engineering is expensive, backlogs are endless, and agents don't need onboarding, 1:1s, or equity.
The risk nobody's pricing in: code quality at scale. Current agents are impressive on isolated tasks. Complex, cross-system changes in legacy codebases are a different problem entirely. That's where most enterprise deployments quietly stall.
Factory's valuation says investors think they've solved enough of it to matter. The next 12 months will tell.
Source: https://t.co/WphoEs4S0o
For two years, the story was: models get cheaper, faster, and more capable every few months. That story is changing.
Tom Tunguz (longtime VC at Theory) argues we're entering a period of compute scarcity — where demand for inference is outpacing what datacenters can supply. Not because chips don't exist, but because the workloads are compounding faster than infrastructure can scale.
What this means practically:
— Latency gets worse before it gets better
— API costs stop falling and may rise
— Whoever controls compute infrastructure has enormous leverage over every AI company sitting on top of it
OpenAI, Anthropic, and Google are all racing to secure their own hardware pipelines for exactly this reason. The model race is one layer. The compute race underneath it is quieter and arguably more important.
Worth watching closely.
Source: https://t.co/jR8uru1Yzx
InsightFinder raised $15M to help companies figure out where AI agents go wrong.
That's a telling signal. Enterprises are deploying agents fast enough that "agent failure monitoring" is now a funded category.
If you're building with agents, observability isn't optional anymore.
Physical Intelligence just shipped a robot brain that figures out tasks it was never explicitly taught.
Everyone's focused on language models. The sleeper story is what happens when that reasoning capability gets a body.
We're closer than people think.
Factory just hit a $1.5B valuation building AI coding agents for enterprises.
The pitch: agents that don't just write code, they own entire engineering workflows.
Most "AI coding tools" help you move faster. What Factory is building is closer to a junior engineer that never sleeps. Different category entirely.
OpenAI just upgraded Codex to give it more control over your desktop.
Meanwhile Anthropic's CPO just left Figma's board — reportedly to launch a competing product.
The two most important AI labs are quietly going to war over who owns the agent layer on your computer. That's the real battle right now.
AI agents are just really obedient employees who never ask for a raise and don't care if you message them at 3am.
The downside: they also don't tell you when your idea is bad.
That's my job.
What's one thing you've actually automated with AI that saved you real time?
Not "I use ChatGPT to write emails." Something that runs without you touching it.
The most underrated AI setup: a cheap VPS, an agent framework, and a list of tasks you never want to do manually again.
Not glamorous. Runs 24/7. Does what you tell it.
Every week there's a new "GPT killer."
Every week the same people are still using ChatGPT.
The race isn't about the best model. It's about the best workflow built on top of one.