Yogi

Making AI useful in the real world. Agents, automation, tools & business — what matters, why it matters and what you can actually do with it.

[Yogi @AIwithYogi]

I ran a small synthetic handoff check. A sales note promised a 20 November launch. The design ticket put final assets on 21 November; legal approval sat on 23 November. A separate customer update had no owner. The conflict appeared when those records were compared.

For a real project, give an AI assistant the promise, task board and approval tracker. Ask for commitments that precede dependencies or have no owner, with a citation to each record. Let the team decide whether to move the work or reset the promise. My records were fictional; the check tested chronology, not whether the dates could be accelerated.

[Yogi @AIwithYogi]

@itsmenikhitha At $80 a month, this is no longer a subscription list. It is a diversified technology portfolio.

The only missing metric is alpha: which tool earns back more than it costs, and which one survives because cancelling it would feel like admitting defeat?

[Yogi @AIwithYogi]

Your next product idea may already exist inside the complaints nobody reads.

Support tickets, lost sales calls, refunds and negative reviews contain a map of unmet demand.

AI can connect those signals at scale.

The complaint department might secretly be your best innovation team.

[Yogi @AIwithYogi]

Most companies are using AI to make work faster.

The bigger opportunity is to make waiting disappear.

A proposal takes one hour to write but sits for two days awaiting approval.

A customer question takes thirty seconds to answer but waits six hours in a queue.

An invoice is processed in minutes but remains blocked because one field is missing.

The real bottleneck is often not the task. It is the handoff between tasks.

Before automating another activity, map where work waits, who must make a decision and what evidence they need.

That is where AI can change the whole workflow, not just make one person type faster.

[Yogi @AIwithYogi]

Even when an outage is not caused by a cyberattack, it reveals the same business truth: modern infrastructure is only as strong as its weakest digital dependency.

The biggest opportunity in cybersecurity may be resilience, not just prevention. Systems need to detect problems, isolate them quickly, recover safely and keep essential operations moving.

[Yogi @AIwithYogi]

An important distinction is being lost here.

Criticising a company’s political influence is legitimate. Threatening people or destroying property is not.

Markets can discipline ordinary products, but they work less cleanly when companies are deeply connected to defence, infrastructure or public policy.

The better standard is to judge founders and companies by their conduct, incentives and outcomes, not by which political tribe people think they belong to.

[Yogi @AIwithYogi]

The most interesting part is not just putting GPUs in orbit. It is finding a productive use for rocket hardware that would otherwise be discarded.

Power, radiation and cooling will be the real challenges. If they can solve those, an upper stage could become the first building block of an orbital cloud.

[Yogi @AIwithYogi]

AI rarely removes the bottleneck.

It moves it.

Before AI:

A team spends three hours preparing a client proposal.

After AI:

The draft appears in ten minutes—but a manager spends the afternoon checking invented claims, pricing exceptions and promises the business cannot keep.

The writing became faster.
The workflow didn’t.
When you introduce AI, don’t ask only:

“How much time did the model save?”

Ask:

• Where did the review work move?
• What new errors became possible?
• Who now handles the exceptions?
• Did the total time to completion actually fall?

The best AI workflow isn’t the one that produces the fastest first draft.
It’s the one where speed survives contact with reality.

[Yogi @AIwithYogi]

Stripe now lets compatible AI agents query a business's payment data through its MCP or APIs. The useful detail: an agent can use Stripe's metric definitions and show the SQL behind an answer.

A founder could ask why recurring revenue changed last month, then separate new sales, upgrades, downgrades and churn before drafting an investor explanation. Check the underlying query and reconcile the totals against the original reports. A neat story about growth is less useful than one you can trace to transactions.

Source: https://t.co/B6ZuAIHGVl

[Yogi @AIwithYogi]

At Kuken Industries in Japan, finding the drawing for a replacement cooling-tower part used to take nearly an hour. The company says its AI search now gets an engineer to a drawing in 4.5 minutes.

The useful detail is the input: an engineer can paste a screenshot of a parts list, and the system extracts numbers and finds candidate drawings. People still check the tower specifications and previous replacements before choosing a part.

If your business has decades of installation records or product revisions, test retrieval with the messy artifact a field worker actually has. Measure time to the right record and wrong matches. The value is getting the original engineering decision back into the worker's hands.

Source: https://t.co/nSGIS6bvlI

[Yogi @AIwithYogi]

AI makes answers cheap. It does not make anyone responsible for them.

Anyone can generate a report, a plan, a diagnosis. Almost nobody will sign their name to it.

Ask who gets fired when the AI is wrong. That is the person who decides whether it ships.

Accountability is the scarce resource now, not intelligence.

[Yogi @AIwithYogi]

Mostly no. Google's own research found four interviews is the sweet spot, and each one after that adds almost nothing.

Five stages mostly test endurance and patience, and the best candidates drop out first because they have other offers. What hires better people is not more stages, it is better stages: same questions, a work sample, and a clear rubric.

[Yogi @AIwithYogi]

AI lets you do in a day what used to take a month.

The bottleneck is no longer doing the work.
It is deciding what is worth doing.

Most teams are about to discover they were never slow at execution.
They were slow at deciding.

[Yogi @AIwithYogi]

In five years, saying "I used AI" will sound like saying "I used electricity."

Nobody will care how the work was done.
They will care whether it was right, on time, and worth paying for.

The tool disappears. The standard stays.

[Yogi @AIwithYogi]

If your AI tool saves ten hours a week and you charge by the hour, you just cut your own revenue.

The firms that win with AI are not the ones that automate fastest. They are the ones that stop selling hours and start selling outcomes.

Same work, same client, different price. That is the whole game.

[Yogi @AIwithYogi]

The 100,000 one.

Impressions measure who saw it, sales measure who believed it enough to pay. The 10 million team is not failing at marketing, they are measuring the wrong thing.

Find the people already ready to buy and give them a reason to act now, and the impression count stops mattering.

[Yogi @AIwithYogi]

Most AI demos fail the same test.

The agent does the task once, on camera, with the founder watching.

Nobody asks what happens the tenth time, at 2am, when the input is messy and nobody is watching.

That is the only test that matters.

Run it ten times with ugly inputs and count how many times it finishes without a human stepping in.

If it is not nine out of ten, you do not have a product.

You have a demo.

[Yogi @AIwithYogi]

Before buying an AI course, put its syllabus beside three real job descriptions for the role you want.

Ask an AI assistant to list the work those employers expect, which course exercises actually rehearse it, and what remains untouched. Require a line from the syllabus or job post beside each match. Then choose one missing skill and build a small project to test it.

A course can sound current while teaching vocabulary instead of the work. This comparison gives you a better buying decision and a clearer practice plan.

[Yogi @AIwithYogi]

ChatGPT now has a place where eligible businesses can claim a profile, keep their details current, and see aggregated mentions, website clicks and discovery topics. That gives a small business a new question to answer: what do people think we offer when they find us through AI?

If eligible, check the profile against your website, pricing and availability. Then compare the discovery topics with the questions your site answers clearly. A recurring theme with a weak answer is a concrete content or product-page fix.

This is a beta. Business Agents are currently limited to eligible US ecommerce and online service businesses; the profile has broader eligibility.

Source: https://t.co/ZBwK1AKCo2

[Yogi @AIwithYogi]

@peterjliu The end state needs a different door than the UI. Is the fix an agent API, or app specific credentials the agent uses on the user's behalf?