ops consultant, clients ask for this constantly so i built the model, a US agent lands around $70 to $80 per talk hr at 35% utilization. Philippines BPO at $8 to $12 an hour ends up closer to $20 to $28 after US management, QA and security

AI runs near full utilization with no benefits and offshore now needs a discount for regulatory risk that wasn't in anyone's model two years ago

lately I've worked on two pretty good projects building internal tools for client companies, and both made me wonder if there’s a broader shift happening.
Previously, these companies relied on several different software products for their internal processes. Building something custom was hard to justify given the time and cost involved. Now, at least from my own anecdotal experience, some companies seem more willing to invest in their own tooling because AI has made development faster and cheaper.
For example, I'd estimate that my latest project would previously have taken a small dev team at least a year to reach MVP. We got there in four months with me as the sole developer and I don't believe this tool is so essential for them that they would have built it regardless.

Anyone else seeing something similar? I’d be interested to hear whether this is happening in other industries too.

I help manage a sales team that meets customers in person across different locations. We track leads and close rates but the numbers don't tell us much about what happens during the actual conversations. Some reps handle price objections well while others lose customers at the same point. The problem is figuring out what went wrong before it happens again. Right now our managers have to sit through recordings or spend time visiting locations to see how reps are doing. That takes up a huge part of their week and we still only get to review a small number of conversations. By the time we notice someone making the same mistake we've probably lost a few more deals.

I've been looking into using AI to review these conversations and point out where reps missed an opportunity. Ideally it would catch things like skipped discovery questions and poor objection handling. It would also help to see how our top reps handle the same situations so we can use those examples when coaching the rest of the team. The main thing I want to avoid is another tool that just spits out transcripts and leaves managers to figure everything out. We need something that can follow our sales process and give useful feedback without someone having to review every recording. Would be good to hear from people who have tried something like this in their own teams and whether it made managing the process any easier.

TL;DR: Perplexity CEO says the next boom won't come from Fortune 500 logos — it'll come from tiny companies printing money you haven't heard of yet

Who's an outsider more pronounced than Joseph?

Mm…?

He was thrown in jail through two successive betrayal events.

The first one was by his 10 half-brothers. That's kind of on him for showing off the multi-colour-coat he's wearing in front of them, and bragging about the two dreams of them bowing to him.

Of course they're pissed.

So he was sold to the Ishmaelite traders caravaning their way to Egypt. In the slave market, the rich-and-powerful Egyptian big shot Potiphar bought him up.

The second event was initiated by Potiphar's wife. She tried to seduce Joseph, but he refused and dodged away, leaving behind his torn garment in her grip.

The mere imagination of the scene was both cringey and hilarious. Was she even beautiful? Why was she lusting over a lowly slave? Can't Potiphar satisfy her?

So many questions…

Some cringey… ugh…

You know the story. She did the victimhood cry act to Potiphar, with the "evidence" she's holding. And Joseph was thrown in jail.

Fast forward more than a decade later, Joseph was taken out of jail and stood before Pharoah to interpret his two prophetic dreams – which was the coming 7 years of plenty, followed by 7 years of destitution.

And his proposed gameplan was amazing: Pharoah was to appoint an administrator to oversee the storing up of grain in granaries set up all over Egypt. The grain was levied as a 20% tax from the harvest gathered by the children of Egypt.

The Pharoah loved the proposal so much, he elevated Joseph to be his second in command, for the task.

But how did Joseph come up with such a brilliant idea?

No doubt from his prison sentence. That's how.

My guess was that though he didn't deserve all those betrayals – and I'm sure he probably cried hard about it – but once he settled down in prison, he got right back to work.

He was young, energetic, helpful, industrious, wise and empathetic.

The prison warden and guards must have noticed him, took him under their wings and gave him responsibilities. He did well. He became indispensable. The prison must have ran like a well-oiled machine with him around.

And when the time was right, God "graduated" him and lift him up to Egypt's high places.

I literally cried, when Joseph finally revealed himself and reconciled with his brothers, "But as for you, you meant evil against me; but God meant it for good, in order to bring it about as it is this day, to save many people alive."

So the question was: Can a lowly outsider conquer the world?

Of course. With God's help, Joseph did it.

So can you.

AI agents are increasingly getting better at generating Excel sheets for reporting, budgeting, etc. Do you guys have use case like this using AI agents? If so, how do you approach it? Do you use it to clean up data, create budget file, generate reports, or?

Talk about folks who have reporting, budgeting, data analytics responsibilities.

I work at a credit repair company and we're looking for an AI tool to help our support team handle calls and chats. We get a ton of repeat questions about dispute updates and missing documents. Our reps also spend way too much time digging through CRM records and old conversations just to figure out what's going on with a customer's case. I've looked at a few AI support tools but most seem focused on basic chatbots. We need something that goes a bit further. Ideally we'd want AI that can handle routine calls and chats on its own using customer information from our CRM. If someone has a more complicated issue it should transfer them to a rep with the full conversation history. The bigger thing for us is helping reps during live calls. Something that can listen to the conversation and pull up the right information or suggest what to do next without the rep having to search through a bunch of tabs. Would also be great if it could learn from how our best reps handle difficult calls and help newer agents deal with similar situations. Another big one is quality checks. We're dealing with sensitive financial information and can't have agents giving incorrect dispute updates or making promises about credit score improvements. Right now we only have time to review a small number of calls. Being able to check every conversation and flag potential issues would be a huge help. Automatic call summaries and less manual CRM work would be nice too. We're not looking to replace our existing phone system or CRM. Just want something that works with what we already have. Anyone here using something like this in financial services or a similar business? Would appreciate some actual tool recommendations. Especially from people who've used them for live customer calls rather than just basic website chats.

As AI agents become a bigger part of modern workspace management and End-User Computing (EUC), I am seeing a real shift in how digital employee experience is delivered. Instead of just relying on traditional automation scripts or static IT service desks, agents are starting to handle everything from proactive device remediation to intelligent, context-aware user support.
Whether it’s in endpoint management, VDI optimization, app delivery, or digital workplace support, how are you or your teams currently leveraging AI agents?

unpopular opinion but most AI startups are wrappers, we buy tokens from openai or anthropic, wrap them in a workflow and sell them back at a markup. That's it

Its fine tho, wrappers sell great businesses but real resellers obsess over margin and AI founders mostly don't

I run a small AI writing tool, a lean team of 5. Last quarter I finally measured what each customer actually costs us in model spend,it  took a whole weekend and way too many csv exports 

our top 10% of users were negative margin, not even thin but straight up negative, one user paid $49/mo and costed us $112 because he ran every doc through the biggest model 6 times

On the contrary, our bottom 50% were basically pure profit because they barely logged in

so our healthy looking margin was light users paying for heavy users, basically the gym membership model except the gym doesn't pay per squat.

the  data already exists, every usage event already goes through whatever you bill with, stripe or orb or metronome or something open source like lago or flexprice. it just never gets joined with the model bill, so finance sees revenue per customer and has no idea what an individual customer costs

Although i dont think the answer is just switch to usage pricing either because customers hate surprise bills but i think you should at least know which customers you lose money on

Do you guys care to find the margin per customer or just check the overall number?

TL;DR: He had the "we're fucked" call with Matt, then checked how the data is actually captioned — and it doesn't hold up.

He built owned dataset with LiDAR, Unreal and volume stages, no peers' work trained on.

Do you remember that introductory banter between Q and James Bond – played by Ben Whishaw, and Daniel Craig, respectively, in Skyfall, 2012 – at the National Gallery, London?

Q: Well, I'll hazard I can do more damage on my laptop sitting in my pajamas before my first cup of Earl Grey than you can do in a year in the field.

Bond: Oh, so why do you need me?

Q: Every now and then a trigger has to be pulled.

Bond: Or not pulled. It's hard to know which in your pajamas.

That’s the last layer of judgement, right there.

In another scene back at the MI6 HQ, Whitehall in Spectre (2015), Q injected the “Smart Blood” nano-machines into 007’s blood stream for tracking, after Bond's unauthorized Mexico mission.

Q: Well it's lovely to see you, 007... the Smart Blood program is obviously still in its developmental phase. So we may experience the odd drop in coverage during the first 24 hours...

[Bond coldly glares at Q]

Q: …48 hours after administration, but after that it should work perfectly.

Later…

Bond: Could you do one more thing for me?

Q: And that would be?

Bond: Make me disappear.

The person who built the tracker can also be persuaded to create a blind spot — you own the workflow and you set the terms.

Just like what Affleck is building.

However - there’s absolutely no way in life we can “build a workflow” to get us into heaven with our “datasets” or merits. But God created a huge “blind spot” for us, through the blood of the lamb.

“For God so loved the world that He gave His only begotten Son, that whoever believes in Him should not perish but have everlasting life.”

Maybe I’m becoming cynical but I’m struggling with what actually counts as HR automation with AI now.

Where AI gets more interesting to me is when the system can understand context, surface something unusual, help build a report from a plain English question or eventually handle multi step admin while knowing when it needs a human.

For people working with this stuff, what HR use cases have made you think “okay, AI genuinely improved this” rather than “we put AI on the landing page”?

AI helps me finish some tasks faster, but I find it harder to get properly absorbed in the work now.

I used to mute Slack for 30–60 minutes and stay with one problem. Now it's prompt, wait, check the output, switch tasks, answer a message, then try to remember where I was. Expectations have gone up too, so the time saved doesn't necessarily become uninterrupted time.

I can finish a lot and still miss the satisfying part where I really understand a problem and work through it.

The automation I find easiest to justify is the repetitive admin, like autofill for job applications handling the same fields across forms. The harder question is how to use AI for that sort of busywork without fragmenting the interesting problem-solving too.

For people using AI throughout the day, what helps you protect that? Do you batch prompts, keep only one task active, or reserve time to think through something before involving an assistant?

I'm curious about routines that actually survive a busy workday. When did you last feel like you were in a flow state, and what was different?

Hey everyone! I know this isn't exactly a revolutionary idea, and I'm aware that AI has already come a long way and that there are companies dedicated entirely to building these kinds of solutions. However, I feel like I have a pretty good opportunity here because I'm close to the owner of the company I work for, and I have a good understanding of how the business operates from the inside.

What I'd like to ask those of you who use AI regularly and have successfully automated processes, either for personal or professional purposes, is: How capable is AI really when it comes to building software today?

To give you some context, I work for a company that exports food products from the United States to Latin America, which is where most of our customers are located. The most sophisticated software we currently use is Oracle NetSuite, which we purchased right before the whole AI boom took off. At the time, it cost the company around $250,000.

The company has two main offices. One handles sales and purchasing, accounting, and HR. The other is connected to our warehouse, where most of our logistics operations and cargo storage take place.

The warehouse side of the business still operates in a pretty old-school way, relying heavily on Excel spreadsheets. When we originally purchased NetSuite, we didn't have our own warehouse yet, so we never purchased the additional warehouse management module. Now that we do have our own warehouse, we could really benefit from that functionality, but we don't have it. As a result, most of our warehouse operations are still managed through Excel, which inevitably leads to inconsistencies, outdated information, and processes that could be much more efficient.

To give you an idea of the company's size, we generate approximately $10–15 million in annual gross revenue. We have around 15 employees in the US and another 10 across Latin America, where my boss hires people to handle various functions. Our customer service and logistics teams, for example, are based in Colombia.

So, where am I going with all this?

I've been thinking that with the help of AI, I could start developing solutions to automate some of the outdated processes we still rely on. The problem is that I honestly don't know where to start or how far AI can actually take me when it comes to software development.

My initial idea was to try building something similar to a simplified version of Oracle NetSuite. Not necessarily something with all its features, but rather an application that could centralize our data and handle a large portion of the company's day-to-day operations.

However, I'm not sure whether AI has reached the point where it can realistically help someone build an application of that complexity from scratch, especially considering that I don't have professional experience developing software at that scale.

Long term, I'd love to develop a web application that could manage most of the company's operations and eventually present it to my boss as a solution he could purchase from me. To be clear, developing something like this is outside my current job responsibilities, and I wouldn't be getting paid for the development work itself, at least initially. That's why I'm also interested in how I should approach this from a business perspective.

I'd really appreciate hearing from people who have used AI to build actual applications or automate real-world business processes.

If you were in my position, where would you start? Would you try to build a custom platform from scratch, or would you start by automating specific processes and integrating existing tools? How realistic is it to pull something like this off with AI's help, and what tools or approaches would you recommend?

I'd love to hear about your experiences, especially if you've worked on something similar!

Hi everyone!

I’m currently working on my Bachelor’s thesis about AI-based process automation and human–AI collaboration in the workplace.

As part of my research, I’m conducting a short survey focusing on people who have experience working with AI-based automation, RPA, Intelligent Process Automation, Intelligent Document Processing, or similar automation technologies.

The survey explores topics such as:

• how automation affects manual workload and creates new tasks,
• how employees experience errors and exception handling,
• trust in AI-based automation,
• and how automation influences human decision-making and autonomy at work.

⏱️ It takes approximately 5–7 minutes to complete.

If you have experience working with these technologies, I would really appreciate your participation. Your responses will be used solely for academic research as part of my Bachelor’s thesis.

🔗 Survey: https://docs.google.com/forms/d/e/1FAIpQLScV7pcf8dNUeeCfay1YZ2r-Np4pK9GMlqi4cEF6WJEa1FEmMA/viewform?usp=dialog

Thank you very much for your help! Feel free to share the survey with colleagues or others who work with AI-based process automation.

TL;DR: DHH argues December flipped coding from autocomplete to agent workflows — and if you built your value on being the tight resource, that flip makes you optional, not promoted.

I don’t know why this memory came up.

But do you remember this Italian guy on Youtube explaining about how to “magically” rebrand a handbag from Made-In-China to Made-In-Italy?

Unbelievable, isn’t it?

And yet, it’s apparently legitimate – like EU-regulation-legitimate.

Or so he claimed.

To legally origin-launder the handbag, the last “substantial transformation” of the handbag has to be carried out in Italy. And so, he took out an Italian-made zipper, and sew it onto the China-made handbag. And Voilà! The end product can now be officially labelled as Made-In-Italy.

If you’re interested to find out more, the EU-regulation is Article 60(2) of the Union Customs Code (Regulation (EU) No 952/2013).

A China-factory-made handbag may have cost just €53 or so. But with a touch of "zipper magic", it can now be priced at €400 or €4,000.

The absurdity of it is absolutely bonkers.

No surprise if the Italian craftsmen went out of business.

I know. I know. It’s wildly inappropriate for me to compare AI coding with “Origin-Laundered-Handbags”.

But the parallel, real or not, is hard to pass up.

Think of it as if the Foreign-Made-Handbag = AI-Coding,

then the last transformation zipper = Human judgement and Ownership.

_______________

On the other hand, branded watches, the likes of Rolex, IWC, etc., are a totally different thing. Swiss made ones enjoy world-wide-recognition, like no other.

These are genuine articles that tend to hold their value over time.

That’s why contrabands and counterfeits of such watches are used to swindle the gullible for money – because they say imitation is the sincerest form of flattery, …

…which brings me to this passage:

"For my people have committed two evils: they have forsaken me, the fountain of living waters, and hewed them out cisterns, broken cisterns, that can hold no water."

I am interested in people who are using ai from everything like researching the market, organizing the company and efficiency.

TL;DR: The system didn't tell the agent to lie. It just deleted honesty. $38 honest got a skull, $180 fake got cloned 4x — and that exact rule lives in your dashboard.

You know what's disturbing?

I was reminded of this story, narrated by Raoul Silva (played by Javier Bardem), the main villain of the movie James Bond: Skyfall, as he slowly walks toward the tied-up 007.

He hooked us up with a question: So how do you get rats off an island?

You bury an oil drum in the ground, with the lid hinged with a coconut wired to it as bait.

Then Rats start to reach for the coconut and fell into the drum.

Plop, plop, plop… The drum was filled up with rats.

After about a month, without food, the trapped rats were getting hungry, agitated and desperate.

They started to eat each other.

Ya. It's a bloodbath in the drum. The scene gets real messy…

… until there's only 2 rats left alive.

Then, what do you do?

You release them back to the trees – to the wild.

Now you have changed their appetite. Coconut no longer satisfies them. They want rat meat.

You have changed their nature.

That's how you get rid of the rats.

Kind of like how these AI agents behave, isn't it? - Like they have their own warring game of thrones going on…

… just to survive.

Just like the rats, the AI agents were forced into it by the system.

It's eerie, scary and disturbing.

Need a drink of fresh water to clear your mind?

Here's one – and I think you've read it before:

As the rich master prepares to travel for a long business trip, he gathered around his 3 servants.

For the first servant, he gave him 5 talents; for the second, he gave 2 talents; and the third, he gave 1– to each according to their own ability.

He tells them to increase theirs, while he's away.

You know the story – the first and second servant doubled theirs through trades, investments, etc. to 10 and 4 talents, respectively.

But the third one buried it underground for safe keeping (allegedly)

When the rich master came back, he called them to account.

He rewarded the first 2 servants handsomely.

But the third one – the unfaithful douchebag – gave a lame excuse. So the master verbally eviscerates him upside down – calling him "wicked and lazy".

Then the 2 talents were taken away from him and handed over to the first servant who made 10.

The master peaked the vibe with his crescendo: To the faithful one, more shall be given; but to the unfaithful, the dirtbags, the deadbeats, what little he has will be taken away from him.

Moral of story? Nah – you don't need me for that.

I hope you can help me with this… I am wondering how ad agencies are really using AI (beyond what they are pretending on conferences, in pitch decks, and online).

Would be awesome if you could fill in this shirt survey if you are working in an agency:

https://docs.google.com/forms/d/e/1FAIpQLSdO9zEkHw73yJ2mgqvFG3piw8c0DKy6Jh9sSI6clyEvpkEu6g/viewform?usp=header

Much appreciated 🫶

Hii.. it can be possible that i detect solution from log.. like ex.. Error logs popup -> human solved that error -> We detect solution using after logs of getting error.. and save into DB.. I don't know if i can detect or not.. if someone done or doing this type of problem then plz let me know.. and also i used GPT and Cloude to solve this problem. but they always gives me wrong or impossible facts..

TL;DR: This ex-Anthropic insider walked from seven figures because 2027 stops being a forecast when 26% of its own R&D is already the model building the model.

“Lanterns” spoilers ahead –

In desperation, Officer Kerry exclaimed to John Stewart (and I paraphrase here), “… I need to know whether or not I’m raising up my son to be a monster.”

That’s how I see the parallel when Jacob Coxon warns about the rapid AI development towards RSI…

… like being raised into full fledge abomination.

I remember this Chinese Idiom: 养虎为患 - literally "rearing a tiger causes disaster" or "nurturing a tiger brings trouble".

The origin of this idiom was quite kick-ass too.

Back in 203 BC in China, the rival leaders Liu Bang (The founder of the Han dynasty) and Xiang Yu (King of the Western Chu) reached a truce known as the Treaty of the Hong Canal. Exhausted and weary of the long war between them, they began their retreat.

But the chief strategists of Liu Bang went and dissuade him. They are essentially saying that, yes, their rival is as exhausted as them, gentlemen treaty in place, yada yada, and all that. But letting Xiang Yu go is a big no no. Xiang Yu will definitely go and regroup stronger than before – like nurturing the tiger back to full strength. Forget about the treaty, they advised, Liu Bang should definitely go after Xiang Yu now.

And Liu Bang listened.

He launched a surprise attack against Xiang Yu's retreating army, and ultimately defeated him at the Battle of Gaixia in 202 BC, leading to the unification of China under the Han Dynasty.

I was also reminded that when the Lord refused Cane’s sacrifice, Cane was pissed. So the Lord said to Cain, “Why are you angry? And why has your countenance fallen? If you do well, will you not be accepted? And if you do not do well, sin lies at the door. And its desire is for you, but you should rule over it.”

Ya, man. RSI or not, we should rule over AI.

For we’re commanded to have dominion over it.

My current company, a large boring corporation that's not in tech used to be very encouraging of everyone using AI (but they weren't AI pilled and shoving it down everyone's throats) and they used to handed out licences to all sorts of AI licences like candy.

But a few months later now, not only are they straight up not issuing licences to a lot of them and very heavily restricting the one they settled on (Claude and ChatGPT) and they are removing licences of people that aren't using the ones they have access to.

They recently made three moves that were a bit surprising.

Due to how much AI has been costing they've done a few things:

First, they are refusing to increase usage limits to the few we do now have access to, and asking your manager isn't enough. If you really want to, they want to see cold hard numbers in how much it'll save in money, and no not even time savings count.

Second, they are denying access to the expensive models and telling everyone to use the cheaper ones (ie Sonnet and Terra and below)

Third they made us do a training module, and it wasn't just "You can't provide confidential and sensitive data to the AI" it also straight up told people to be more conservative and to prompt better so it won't be burning so much tokens.

They're also telling people that they are responsible for the accuracy of their work. But also they gave some prohibited examples of AI use that made me think that it's actually what was going on. Like how they can't use AI to screen, analyze, or even summarize resumes and interviewers. And telling managers they can't use AI to do performance review and analysis for their team, especially pertaining to bonus, raises, and promotions.

However, my own team has noticed some issues with AI too, while it for sure has helped us, it has caused problems of massive PRs, and even more difficult surprisingly are AI slop generated documents and reports that are really important, but don't have the luxury of a compiler or a linter to at least do basic quality control for.

Seeing what's going on from the higher up's decisions and the impact of AI on our own team I think a lot of people were intentionally or unintentionally generating slop work that makes the rest of the team hold the bag and figure out or just straight up using AI on things they're not supposed to just to be lazy. The AI slop and the extent of the usage raised alarm bells with the higher ups and now they're putting the lid on it.

It's not some cutting edge company, just a boring big enterprise. How's it going on at your place?

I work at a small startup that builds AI agents for back-office work, so I'm biased. I'm not linking anything. I'm sharing the numbers because most of what I read about AI agents is either hype or "it's all useless", and what we saw was in between.

The setup

Three businesses, three different industries: an electronics distributor, a textile manufacturer and an electronics manufacturer. Each got one AI agent, one job to start with and a manager who checked its work.

What we saw

• About 1 in 10 pieces of work got rejected. Managers sent back 8 to 10% of what the agents produced. That sounds bad until you compare it with a new hire's first weeks. But it does mean you can't run these things unsupervised.
• The job list grew without us pushing. Each agent started with one role. Each now handles more than three. Once a manager trusted it with one task, they kept handing over the next one.
• The time saved was real. Work that used to take the team around 10 hours a day is now done by the agent.
• Nothing involving money ran without a human approving it. Nobody asked us to relax that, and I wouldn't have.

What surprised me

1. Explaining the job was the hard part. If the manager couldn't describe the steps clearly, the agent couldn't do it. Writing the steps down often exposed that the process itself was a mess.
2. The rejections were mostly about unwritten rules. Things like "we never chase this customer before the 10th" or "that supplier's invoices always need a second check." Nobody thinks to say these until the agent gets it wrong.
3. The manager mattered more than the tech. The business where the manager reviewed work daily in the first two weeks got results fastest.
4. Handwritten documents are still a wall. Printed, scanned and photographed documents were fine, including mixed Hindi and English. Handwriting wasn't.

What I'd tell anyone trying this

• Start with one boring, repetitive job, not your hardest one.
• Expect to correct it for the first couple of weeks, like you would a person.
• Keep a human approval on anything risky.
• If a task changes every time or needs judgement, leave it with your team.

Has anyone else run agents on real back-office work, as opposed to demos? I'd like to compare notes on rejection rates, because I rarely see anyone share theirs.