Amit | Frogomo | AI 🐸

28.1K posts

Amit | Frogomo | AI 🐸 banner
Amit | Frogomo | AI 🐸

Amit | Frogomo | AI 🐸

@frog_omo

The AI & Automation guy | Real AI automation strategies for SaaS. Sharing tested AI agents + workflows | Join newsletter for exclusive insights

AI Newsletter → Katılım Aralık 2022
687 Takip Edilen3.2K Takipçiler
Sabitlenmiş Tweet
Amit | Frogomo | AI 🐸
Amit | Frogomo | AI 🐸@frog_omo·
I thought I was paying attention to AI. Then I actually looked at the data from the last 3 months. I wasn't paying attention. I was watching the surface while the ground shifted underneath. Here's what's actually happening: AI adoption hit 39% of US adults in two years. For comparison: → PCs took 12 years to reach that level → The internet took 5 years → AI did it in 2 This is the fastest-spreading technology in recorded history. And most people are treating it like a new app to try. The capabilities are moving faster than the headlines. In one year: → AI's ability to solve real coding problems jumped from 4% to 72% → Inference costs dropped 280x → Model efficiency improved 142x (same performance, fraction of the size) Sam Altman said AI costs are falling 10x per year. Faster than Moore's Law ever did. The workforce data is where it gets uncomfortable. 26% of US workers now use AI on the job. But here's the part nobody talks about: → 45-49% of them are hiding it from their managers → 52% are reluctant to admit using it for important tasks → 78% bring their own AI tools to work without employer direction Half the workforce is already adapting. Quietly. Without permission. The job shifts are happening underneath people. → Klarna cut 40% of its workforce. AI handles 2.3 million customer chats per month. → Duolingo replaced translators with GPT-4 and declared itself "AI-first" → Entry-level job postings dropped 35% since 2023 → Freelance writing gigs fell 28%. Graphic design fell 33%. These aren't predictions. These are last quarter's numbers. 41% of companies plan to reduce their workforce by 2030 due to AI. But 77% of those same companies plan to reskill existing workers. The net projection: 170 million jobs created, 92 million displaced. The math is positive. The distribution won't be. I keep thinking about this stat: ChatGPT reached 100 million users in 2 months. → TikTok took 9 months → Instagram took 2.5 years By early 2025, ChatGPT had 700 million users. Over 1.2 billion people used AI tools within 3 years of launch. And most conversations I hear still start with "I should probably try that AI thing." The gap isn't between people who use AI and people who don't. It's between people who understand what's happening and people who think they have time to figure it out. Anthropic's CEO thinks AI will be better than humans at "almost everything" within 2-3 years. Google DeepMind's CEO moved his AGI timeline from "10 years" to "3-5 years" — in the span of 3 months. These aren't random Twitter predictions. These are the people building the systems. I'm not saying the sky is falling. I'm saying the data doesn't match the vibe. Half the workforce is already adapting, mostly in secret. And the tools they're using today are the worst versions they'll ever use again. That's not fear-mongering. That's just the math.
English
13
1
23
1.2K
Amit | Frogomo | AI 🐸
There's a pattern in every SaaS ops post-mortem I've seen this year: The stack wasn't too big. The intelligence was fragmented. Predictable Revenue cut tech costs 50%, consolidating to Apollo. HubSpot all-in runs 20–30% lower TCO than Salesforce for sub-200-employee teams once you factor in add-ons, implementation, and admin overhead. Those aren't wins because of fewer tools. They're wins because there are fewer decision points where the data contradicts itself. When your enrichment tool, CRM, and revenue intelligence platform each hold a different version of the same account, that's not a data problem. That's an orchestration problem. @clay 50–90% pricing cut this week made something explicit: data enrichment is now table stakes. The differentiation lives in the workflow layer between what the data says and what actually gets done. Companies still debating consolidation vs. best-of-breed are asking the wrong question. The right question: what's your orchestration layer?
English
0
1
3
61
liamtran
liamtran@liamtrn·
Reply to this so I can follow you !
liamtran tweet media
English
1
1
3
41
BenjaminLiu
BenjaminLiu@BenjaminLiu521·
Thank you all for helping me gain so many followers so quickly. Although I still have a long way to go in terms of impressions, this has given me hope. If you also want to grow your followers quickly, leave a comment below and follow me — I’ll follow you back as soon as I can. Let’s all interact more and start earning some money from Boss Elon as soon as possible.
BenjaminLiu tweet media
English
23
1
34
651
Seggy
Seggy@seggycreations·
Wood Sculpture Making AI Video Made with @NanoBanana and @grok imagine
English
1
0
3
73
John Koes
John Koes@JohnKoesS·
My X analytics are stuck all day. Does someone have the same problem or is something wrong with my account?
English
1
0
2
252
Rault
Rault@raultotocayo·
This made me cancel my ElevenLabs subscription. Dia by Nari Labs: ultra-realistic multi-speaker dialogue, locally, for free. 19K stars. Zero API costs. Docs are sparse. The audio quality isn't. github.com/nari-labs/dia
English
1
0
2
41
Ralfs | AI Compliance
Ralfs | AI Compliance@RalffTum·
12.3 % engagement today, i guess being human actually works😅
Ralfs | AI Compliance tweet media
English
3
1
4
50
Shiblee Showkat
Shiblee Showkat@stackychan_·
I changed my logo guys. How is this new look ? Rate it out of 10
Shiblee Showkat tweet media
English
2
0
4
174
Amit | Frogomo | AI 🐸
@taheerBuilds This actually makes sense from a product strategy view. Give more usage → people rely on it → then convert. Do you think this will really push users to Max, or just increase short-term usage?
English
0
0
0
8
taheer ahmed
taheer ahmed@taheerBuilds·
This is how you get addicted and how strategically it’s timed. Everybody is screaming I have been lauding at night doing this that! Now you too Get the taste of pro /max for two weeks Once the tasting season is over the addiction urges kick in. this is strategically placed at this time when most of the user base who subbed to claude in support of the safety fiasco happening with the govt, now that pro MRR will start converting to Max Plan ARR😎 @theo thoughts ?
Claude@claudeai

A small thank you to everyone using Claude: We’re doubling usage outside our peak hours for the next two weeks.

English
1
0
0
73
Amit | Frogomo | AI 🐸
@radu_me Lol this is a real problem now, Cristian. I have mostly noticed this when I comment on bigger accounts.
English
1
0
0
14
Cristian Radu
Cristian Radu@radu_me·
I have so many Elon Musks in my replies, commenting, leaving likes... I wonder which one is the real one though. I should ask each one a question only the real Elon Musk would know the answer to ... so we can solve the mistery ...🤔
English
1
0
0
93
Tushar Nebhnani
Tushar Nebhnani@TusharNebhnani_·
A word that makes you think for hours?
English
2
0
3
41
Julien V
Julien V@julesvcode·
What happened on March 15th and 16th? X analytics seem to be really broken right now.
Julien V tweet media
English
1
0
2
116
JD
JD@codingwithjd·
AI is changing web development fast 😭 What skills should developers focus on now?
English
1
0
1
42
JD
JD@codingwithjd·
Everyone says “reply more to grow on X” But what do you actually reply? I built ReplyGuy 🚀 Paste a tweet → get better replies instantly Free: replyguy-lovat.vercel.app
GIF
English
1
0
1
54
Amit | Frogomo | AI 🐸
@flowmi_ai Definitely, this is something more people need to hear. Working on yourself changes everything over time. Do you follow any daily habits to stay consistent with this?
English
1
0
1
11
Flowmi
Flowmi@flowmi_ai·
If you want to be wealthy and happy the rest of your life, just learn this lesson well. Learn to work harder on yourself than you do on your job.
English
2
0
3
51
Amit | Frogomo | AI 🐸
@SkyezKreative Completely agree with this. Tools can support, but closing still feels very human. Have you seen any tools that actually come close to bridging that gap?
English
1
0
1
4
Amit | Frogomo | AI 🐸
@SnapKernel This is exactly how it feels. Building is fun, but debugging at odd hours is a different story. How do you handle it, Snap?
English
1
0
1
11
Snap Kernel
Snap Kernel@SnapKernel·
What AI conding tutorials show "Building a fully functional app in 10mins" actual reality at 3am 3hours fighting Nextjs and tailwind hydration bugs Vercel Ai sdk throwing API rate limit error (even thought I have plenty of credits) Wake up to reality. Keep shipping 🛠️
English
1
1
1
80
Amit | Frogomo | AI 🐸
@rayzilient @frankyecom This is interesting, Raya! Most people try to make AI content look perfect, but reality always wins. Did you notice a big difference after adding those “imperfection” prompts?
English
1
0
1
21
Raya シ
Raya シ@rayzilient·
🎬 testing out AI UGC for Fit Locker this is probably one of the main directions I’m going to take for marketing. i took @frankyecom course & it actually helped a lot, so shoutout to him 🙏 ✨biggest thing i realized: AI UGC works way better when it’s not perfect → prompting things like “filmed on iPhone” → “natural lighting” → “uneven skin / slight imperfections” makes a huge difference in how real it feels. used nano banana + sora + kling for this next step is probably investing in topaz upscaler before i start making these in bulk for fit locker
English
4
1
10
257
Amit | Frogomo | AI 🐸
@nvidia revenue ops team shared the most useful AI framework I've seen this year. Before any automation project, they ask one question: Is this workflow deterministic or probabilistic? Here's why it changes everything. A deterministic workflow has fixed rules and predictable outputs. Same input → same output. Every time. No judgment required. Examples: → Lead from a 500+ employee company + ICP domain match → route to Enterprise → Deal over $50K + no activity in 14 days → flag for manager review → New contact added → enrich with Clay → update CRM These are safe to fully automate. AI is excellent here. A probabilistic workflow requires context, nuance, and judgment. The right answer changes depending on signals that are hard to define as rules. Examples: → Is this prospect a genuine fit? → Should we escalate this support ticket? → Is this deal actually going to close? These need a human in the loop. AI here doesn't fail quietly. It fails confidently. Most AI projects fail because teams deploy AI on probabilistic workflows and expect deterministic results. The output looks reasonable. Nobody checks it carefully. Six months later, the pipeline is a mess, and nobody knows why. The fix isn't a better AI tool. It's running this check before you start: Write down the workflow step by step For each step, ask: Does this always produce the same output given the same input? If yes → safe to automate If no → human stays in the loop That's the entire framework. The companies winning with AI in 2026 aren't using better tools. They're asking better questions before they start.
English
2
0
3
36