Ciobotaru Ionut

I've spent now - what? - 15 years around ads? a long time.. Longer than I expected.. esp. since I didn't target it specifically and I didn't realize it was an ecosystem at start. My first adserver was open source and build in PHP in the early 2000s. Those were the days...

Couple of thoughts here: 1. The boring stuff takes more energy and provides less energy back / satisfaction (for most peple?!) vs the higher level tasks 2. Solving them already puts you in touch with the customer / user and start understading their pains 3. These things are less open-ended than higher level task - meaning the might be (in theory) easier to solve/verify

Everyone building AI agents is focusing on building the prefrontal cortex. Planning. Reasoning. Multi-step chains. There's value here. CEO-stuff. But also, a reframe: there is value in building the cerebellum. It's offloading boring tasks into reflex so the complex thought can focus. Your mortgage gets paid by a standing order, not a committee. The things that are not fun, not interesting, but have to be done? Done. Most agent frameworks will fail because they treat all cognition as high cognition. The winners will nail the boring stuff first.

I would not discount the article based on just that quote alone. Those are indeed inputs from my POV -> outputs should be: - increase in features delivered (per week/day) - increase in customer usage (because of said features) - increase in customer satisfaction (lagging indicator)

@_lopopolo @trybasis “token usage per developer increased more than 5x and commit velocity increased by 2.5x.” Why would these metrics mean anything at all. Pure noise

Fantastic work by the @trybasis folks on building their codebase to be owned by agents

It’s brutal out there in the Productivity category

@morcoilst Sure thing! Please DM (i just followed)

@weeb0 Hi, can we discuss about something in a DM?

out of Beta 🎉 we also offer a demo account with dummy data, if anyone wants to "try before you buy" don't hesitate to DM, happy to enable it

This is one framing; but the framing I prefer is around value creation; One engineer with AI = 3x value creation than before (just an example) - for existing customers: One sales ops = 5x value creation for client facing roles. What is the limiting factor for revenue generation? If it’s humans, or the GDP - you can optimize everything underneath but you can’t change reality, at least not that fast (some CEOs can well distort it though). And you depend on other “cogs” of the economy. Tl:dr efficiencies are measured against the harsh reality of the P&L which is basically the “laws of physics” for a business.

what about sleeping? :D I can hardly sleep since Opus 4.6 in Claude Code; #shippinganxiety

The whole podcast is really good but the end has basically my takeaways: - things that agents can't do is your job now - things that agents can do, they can probably do better than you - so be strategic about what you're actually spending time on and what I am trying to achieve myself (workwise) currently across different agents (WIP) podcasts.apple.com/us/podcast/no-…

@vedolos Did you find the Ads Agent in there? x.com/weeb0/status/2…

i just leaked the secret system prompts for claude code 🚨 anthropic literally hardcoded instructions to yell at claude if it writes boilerplate code or acts like a junior dev. their anti-bullshit rules are actually insane. a thread 🧵 (1/5)

Original post: x.com/Fried_rice/sta…

This is a tough post to write. Yesterday, Claude Code's entire source code was accidentally leaked. Like everyone in tech, we spent the evening digging through it. What we found makes HYPD obsolete. Buried in the codebase, there's an internal module called anthropic-ads-agent. It handles campaign analysis across Google and Meta. Automated performance scoring. Budget reallocation recommendations. Even creative fatigue detection. That's basically our current product plus most of our roadmap. It gets worse. We found: → A function called generatePmaxInsights() that mirrors our Routines feature almost 1:1 → A config file with the comment // TODO: better than HYPD → An internal Slack integration that sends weekly ad reports — with the exact same KPI structure we use → A hardcoded test campaign named "Ionut's Fake DTC Brand" with a 0.2 ROAS After a long call between myself, Philip and Simon last night, we've made the decision: we're open-sourcing everything. If Anthropic is building it, there's no point fighting it. And if they are looking for a faster way to expand their Ads Team, they can reach out to agents@hypd.ai.

@Fried_rice Didn't expect they would have an Ads Agent in there.. x.com/weeb0/status/2…

Claude code source code has been leaked via a map file in their npm registry! Code: …a8527898604c1bbb12468b1581d95e.r2.dev/src.zip

@via_marketing_ @amandiver @branchmetrics Yeah… 💯 - we re a small team and focus is everything so we take it channel by channel. Last week(s) have been mostly focused on outbound..

@weeb0 @amandiver @branchmetrics Being "too busy growing" to promote growth content is peak founder life irony.

Missed this podcast going out because I was so deep in GTM last week. 🎙️🚀 The irony is not lost on me, given this is a growth podcast. 🙂 Better late than never, I guess. Had lots of fun on this one with Adam and @amandiver from @branchmetrics. Felt like a casual conversation in a pub or at one of the usual adtech events. We got into mobile, adtech people, competing with Facebook on native ads, baking pains (🥨), GenAI x Ads (@hypdai), when you don’t need GenAI, and even LLM Ads in dev environments. 💻 Link below 👇

@amandiver @branchmetrics podcast links: branch.io/resources/podc…

@fin465 Guide

Now that we’re done at YCombinator, we’re revealing how we went from 0 → $10k MRR in our first 30 days, using only ONE channel (step by step). We spent less than $100 and didn’t have any paid ads, SEO, waitlist, or content marketing. Instead, we sent 50-75 highly targeted cold emails a day. Cold email is the most underrated channel because it's hard to get right, but if you figure it out you can sell ANY B2B product. Here's what we did from start to finish: STEP 1: Build an ultra‑specific customer profile at both company and person level. If you do this right, you can mess everything else up and still succeed. The goal here is to create such a perfect customer, that if they heard about your solution they would have no choice but to say "tell me more". Step 2: Build your list After you create this customer profile, find the companies that meet this criteria. Find 30–50 target companies on LinkedIn, then grab decision‑maker emails via Apollo/Wiza. STEP 3: Writing a killer email I used to run an outbound email agency and we'd send 50k+ emails/month to book b2b sales calls via cold email. Here are the basic principles of cold email writing that I always use: -Keep it 5-8 sentences. 70%+ of emails are read on mobile, so make sure they get most of it from that screen view. - Never write more than 2 sentences without breaking up the lines. People skim, and that’s the best way to keep their attention - DO NOT talk about your product’s features. - Instead, talk about the person, their company, and their pain points. STEP 4: The call I took 493 sales calls in Origami’s first 3 months. Here's what I learned: The 2 biggest goals for this call are - Figuring out the customer’s problems - Getting the customer excited about your solution Unless you already have PMF, it doesn't matter if you have a full built product. You still need to spend 90%+ of your time figuring out what the customer actually needs. In the early stages, you can even offer a full refund if they aren’t satisfied to give them maximum confidence and get your first few deals over the line. STEP 5: Closing/After Congrats! You cracked cold email. This was the exact approach we used at Origami to get our first $10k MRR, and the highest converting outbound approach I’ve seen when I ran my agency. I posted the stats in my prior tweets, but in our first 40 days we sent 3119 emails (~77 per day) and got a 5.3% response rate, resulting in demos with 64 founders at companies within our ICP. This resulted in ~$22k new MRR by the time our sales for all of these calls had closed. The best part is that once you nail this process, you can automate it. We've got our Origami AI Agents (@origamichat) finding new customers 24/7, which frees us up to explore new channels and focus on scaling. CONCLUSION This is a very short version of my guide. The full guide I posted on X last year (@fin465) hit 800k impressions and 10k+ bookmarks. If you want me to DM it you, comment GUIDE.

@posthog thank you! much appreciated

@weeb0 I'll check with the LLM analytics team.

Great example of where digital work is going.. And where much of the work in digital marketing is going too. Conversational AI/UI is so much more natural for many of the daily tasks. Plus, the Google Ads API is pretty well structured and documented and plays well with agents. Lastly, Cowork is a great unlock for tasks that don't require the full breadth and depth of Claude Code. The question is how distribution will shape up between: - native tooling (eg Google Ads Manager and their Advisor) - horizontal tooling (eg Cowork) - vertical agents (eg hypd.ai)?

@helloitsaustin first of all, thanks for sharing! are there any tasks/workflows where you still use the Google Ads manager? and I see mostly search related skills - do you run demand-gen/youtube separately?

6) my Cowork plugin also extends to Dispatch on my phone. I can pull impression share by day (something the Google Ads mobile app doesn't support, among other things lol), get a budget recommendation, and apply it without opening my laptop. basically full campaign management loops right from my phone.

if you're a performance marketer, here's how I use a custom Claude Cowork plugin to manage Google Ads at @AnthropicAI. it connects to the Google Ads API via MCP, encodes my common paid search workflows into skills, and works on desktop and Dispatch.