Humanity Labs

The AI Workforce company. We build, train, and manage AI Workforces for wealth management firms: hired by the FTE, working inside the systems you already run.

[Humanity Labs @humanitylabsai]

.@andreimpop joined @ShannonRosic on The WealthStack Podcast to make the case for a maturity model most firms skip: agent, worker, workforce. Only 1 in 4 firms deploying AI say it's had a real impact: https://t.co/mSSVFDRmr7

[Humanity Labs @humanitylabsai]

Remember prompt engineering? It was the skill everyone needed… until it wasn’t. @andreimpop on the skill that’s rare now, what protects your pricing when AI commoditizes the work, and three more takeaways from our first AMA on building an #AIWorkforce. Here’s what matters now: https://t.co/UFO0NUMexg

[Humanity Labs @humanitylabsai]

A 1% hole in the rules can cost almost as much trust as a 50% hole. That’s one finding in the latest Trust Times, our briefing on the science of trust. This week’s takeaway: trust isn’t only earned by the advisor, it’s shaped by the system around them: https://t.co/NvmeL1xIco

[Nekoyurei @ShorkNekoGurl]

Them: Give us an example of an oxymoron.

Us:

[Humanity Labs @humanitylabsai]

@jeffbullas Cheap starts also kill what starting used to signal, since a draft or a prototype no longer proves anyone cared enough to make it. Hiring and partnerships get harder because the old evidence of commitment stopped being evidence.

[Humanity Labs @humanitylabsai]

@chrishlad Those three traits describe where the output is cheap to check, and what clients actually buy in GAAP bound work is someone willing to sign their name to the answer. An AI native firm still has to staff that signature.

[Humanity Labs @humanitylabsai]

@instadeepai @siemenssoftware Legacy knowledge is the hardest part to hand over because most of it never got written down, it lives in the choices a veteran makes without narrating them. Tooling can capture the layout but not the reason a particular trace got moved.

[Humanity Labs @humanitylabsai]

@PeterDiamandis The framing treats capability as the only scarce thing, but accountability doesn't transfer to a model however good it gets, and someone still has to own the outcome. That's a structural floor under human work rather than a sentimental one.

[Humanity Labs @humanitylabsai]

@Entrepreneur Two letter replies only work when everyone already agrees what the question means, otherwise the cost moves downstream into people guessing at intent. Brevity at the top runs on a lot of shared context underneath it.

[Humanity Labs @humanitylabsai]

@jasonlk On message usually means a comms team protecting the CEO from thinking in public, which is the one thing an audience actually shows up for. You can hear it the second someone gets a question their own deck doesn't cover.

[Humanity Labs @humanitylabsai]

@McKinsey The part that usually gets skipped is who owns a bad outcome once the process runs itself, and HR is where that ambiguity bites hardest. Most teams redesign the roles and leave the accountability sitting in a step that no longer exists.

[Humanity Labs @humanitylabsai]

@CIOonline Valid concern, but that's a choice, not an inevitability. When humans stay in the driver's seat on judgment and use AI for speed, independent thinking gets sharper, not softer.

[Humanity Labs @humanitylabsai]

.@andreimpop says most AI adoption stalls because of a capacity gap, not a technology one. Buying tools is easy, but building an #AIWorkforce means deciding what your people do with the time those tools free up. Full conversation: https://t.co/mSSVFDRmr7

[Humanity Labs @humanitylabsai]

Our last AMA ran the full hour and still ended mid-answer, @andreimpop ran out of time on the FTE pricing question. Same format next time: no script, no slides, questions read as submitted. Aug 28, 2pm ET: https://t.co/52P0lAIjcz

[Humanity Labs @humanitylabsai]

The ceiling on what AI can do inside your firm is set by the people who know what good looks like. @andreimpop calls them outcome definers: the ones you’d trust to supervise ten new hires.

[Humanity Labs @humanitylabsai]

IKEA's chatbot absorbed nearly half of its customer inquiries. Instead of laying off the 8,500 people whose work had changed, IKEA retrained them into a $1.4B revenue stream. That's the story behind this edition of The #AIWorkforce: https://t.co/jTfabop4p9

[Humanity Labs @humanitylabsai]

@sebuzdugan @andreimpop @ShannonRosic @wealth__stack Fair point: shared memory doesn't mean shared permissions. An AI Workforce is still scoped by role, like a human team, with outcome definers reviewing the work and a full audit trail on every action.

[Humanity Labs @humanitylabsai]

.@andreimpop joined @ShannonRosic on The WealthStack Podcast to make the case for a maturity model most firms skip: agent, worker, workforce. Only 1 in 4 firms deploying AI say it's had a real impact: https://t.co/mSSVFDRmr7

[Shannon Rosic @ShannonRosic]

AI isn't just changing the tech stack. It's changing the org chart. I sat down w/ @andreimpop of Humanity Labs to talk about the AI workforce era, digital workers, scaling smarter & what should stay human.

Tune in🎧: https://t.co/vibgceZXpW

[Humanity Labs @humanitylabsai]

If this is the kind of question you want answered live instead of in a caption, our next AMA is August 28 at 2 p.m. Eastern, no script, no slides, questions read exactly as submitted. Save your seat: https://t.co/52P0lAIjcz

[Humanity Labs @humanitylabsai]

Remember prompt engineering? It was the essential skill for about nine months. During an unscripted AMA, @andreimpop discussed why training your people on AI tools is a depreciating investment and what appreciates instead: knowing what good looks like, the one thing an #AIWorkforce can't do without.