You’ve seen the headline: “95% of enterprise AI pilots fail.”
… The 95% figure measures one thing: whether an AI pilot produced rapid P&L impact within six months. Not productivity. Not cost savings. Not efficiency gains. And it mostly measured pilots in sales and marketing — the lowest-ROI area in the study.
Measured that way, most projects will “fail.” A new hire doesn’t move the P&L in six months either… they often take six months or more to ramp up!
The study’s most important finding got buried: vendor-led deployments succeed 67% of the time. Internal builds succeed one-third of the time. This was always a story about strategy, not technology. This is a better takeaway for enterprises to focus on. — Read More
Daily Archives: April 19, 2026
Salesforce launches Headless 360 to support agent-first enterprise workflows
Salesforce is packaging its developer and AI tooling, including its vibe coding environment Agentforce Vibes, into a new platform named Headless 360, designed to help enterprise teams build agent-first workflows.
The CRM software provider defines agent-first workflows as enterprise processes in which software agents, rather than human users, carry out tasks by directly invoking APIs, tools, and predefined business logic.
To support this approach, Headless 360 exposes Salesforce’s underlying data, workflows, and governance controls as APIs, MCP tools, and CLI commands, via its existing offerings, such as Data 360, Customer 360, and Agentforce, Joe Inzerillo, president of AI technology at Salesforce, said during a press briefing. — Read More
Why Agentic AI Is the #1 Skill To Learn
I’m not here to tell you AI is coming for your job. You’ve heard that a hundred times already, and frankly, nobody wants to here the same thing again.
You’ve also probably read the top skills to learn in 2026. Learn Python. Learn AI. Learn prompt engineering. Sure all those are valid. But here’s the thing: everyone is saying that. And when everyone is saying the same thing, the real opportunity is usually one step ahead.
So what’s that step?
Agentic AI. And hang on, it’s not some buzzword to add to your LinkedIn bio. It’s a fundamental shift in what AI does, how it thinks, how it works, and what it’s capable of. Right now, very few people understand it deeply enough to actually build with it.
That gap is exactly where opportunity lives. — Read More
Don’t choose the WRONG career in 2026 (Data Scientist vs. ML Engineer vs. AI Engineer)
π0.7: a Steerable Model with Emergent Capabilities
We’ve trained a new model, π0.7, that exhibits a step-change in generalization. π0.7 is a general-purpose model that can perform a wide range of dexterous tasks with the same performance as fine-tuned specialists, but even more importantly, it can follow new language commands and perform tasks that were never seen in its training data. In our experiments, we see π0.7 exhibiting the first signs of compositional generalization, recombining skills from various tasks to solve new problems, like using new kitchen appliances and even enabling a new robot to fold laundry for which there is no laundry folding data.
… A true generalist model should perform all of the skills out of the box, and be able to recombine them to solve new tasks. π0.7 demonstrates initial signs of such general capability: it can perform dexterous manipulation skills like those we’ve previously shown with our RL fine-tuned π*0.6 specialist models, with the same speed and robustness, it can compose and recombine the skills it learned to solve new tasks, and it can generalize across robot platforms, scenes, and tasks more effectively than our prior models. The examples below illustrate this breadth of capability, from fine manipulation to long-horizon household behaviors all with one model, straight out of the box. — Read More
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