Dominik Mate Kovacs

From Idea to Working AI Agent in Under 5 Minutes With front End Built with Lyzr AI. Frontend with Lovable. No code. API-ready. What used to take engineering sprints and budget approvals…We just did in minutes. Here’s how we built and launched a fully functioning PR Agent: 🧠 Step 1: Built the Agent on Lyzr.ai Using Lyzr Agent Studio: We created an AI agent that can write, improve, and repurpose PR content Defined the task, chose the LLM, added memory modules Didn’t write a single line of code Optional: Connect your own API (GPT, Claude, or even local models) The best part? You can build with API or without it → No-code creators? Use built-in models. → Devs? Plug in your stack, your endpoints. 💻 Step 2: Deployed the Frontend on Lovable Lovable lets you: - Build beautiful UIs in minutes - Connect to your Lyzr agent using simple configs - Launch a fully interactive front end—no front-end dev required Within 10 minutes, we had a live agent interface running—ready to take user input, generate content, and display results instantly. 🔁 Prototype → Product ✅ Working logic ✅ Interactive UI ✅ Extendable via API ✅ Deployable anywhere You can literally go from idea → agent → interactive product in under an hour. And once tested, scale that into your actual product or workflow. 🔥 Why this matters - Founders: Validate ideas fast without engineers - Marketers: Build and automate use cases yourself - Teams: Get working POCs with security + extensibility - Enterprises: Build internal tools and expose them via secure APIs Video of how its done below. Build your own agent using Studio: https://studio.lyzr.ai/ #AI #Lyzr #Lovable

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You probably already know that: → DeepSeek is the hottest AI app, outperforming U.S. models at a fraction of the cost. → Employees are already using it, chasing efficiency. What you probably don't know is that: → DeepSeek transmits user data to servers in China, where government access is unrestricted. → AI bias is 3x higher than competitors, shaping narratives and decision-making. → Security flaws expose chat logs, credentials, and sensitive corporate data. The problem? Your employees may be unknowingly exposing your company to: → Data leaks & compliance violations → Chinese competitive intelligence → Shadow AI risks that bypass security controls Most companies focus on controlling approved AI tools. But the real risk lies in unmonitored AI adoption. Without visibility, you’re vulnerable to: - Espionage risks - Supply chain attacks - Insecure code generation Want to know who’s using DeepSeek in your org? Reco gives you real-time AI visibility.

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How funny that with infinite possibilities… …everyone still posts the same “what do you think I look like” chatGPT prompt? This is the great positioning struggle every horizontal AI company is facing. Their powerful LLMs and agents can be used for thousands of use cases. And sure, the early adopters and tinkerers love to get their hands dirty and figure out incredible ways to use it. But the AVERAGE person does not want to expend the energy to figure out ways to use your software. They are perfectly content to jump on the bandwagon and post their Studio Ghibli selfie. It’s the same with businesses. The early adopter companies want to get their hands on the risky, bleeding edge tech and figure out the best way to gain a competitive advantage. But the risk-averse mainstream wants to wait until the use cases have solidified and the edges are smoothed out. They want the thoroughly vetted solution. Yes, there’s a period where you want to leave your options open and see how different people use your extremely flexible AI software. But the moment you need to layer on sales and marketing, you will need to narrow to the core use cases. This is DOUBLY true if your product doesn’t have some element of virality (a la Lovable, Cursor, etc.) and the time to value is much slower. If your software will require hooking up to all of an enterprise’s internal systems, you’re gonna have to pick some core use cases. And this will feel like putting on a straight jacket. You’ll feel like your dreams are getting squashed (along with your TAM). But be patient! Nail the core use cases. Then when you’ve dominated those segments, hire more GTM and scale by supporting additional adjacent use cases.

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Picking an AI CRM Agent in Breakcold is like Mario Kart. At Breakcold, we got tired of boring, abstract AI agents. I wanted something that feels alive, not like another robot in a suit. So we made picking an AI CRM agent FUN. You open Breakcold → you see the new Baskets → you pick a personality. Every agent has their own look, their own animation. (Yes, I’m serious. Think Mario, Luigi, Yoshi… but for sales 😂) It’s not just a gimmick. When you pick your AI agent, you actually change the way tasks get done. Each one influences HOW your tasks are created. → No more boring “next action” lists → No more endless setup → No more “did I forget to follow up?” Instead: - Agents create tasks for you, based on your workflow - They adapt to your rules (or zero setup if you want) - You always know what comes next (no more guessing) It’s like having a video game assistant in your CRM. My co-founder and I joke we aren’t building SaaS anymore. We’re building a game for work. And you know what? Using AI for B2B should be fun. That’s the power of Breakcold’s AI agents. They don’t write all your emails or replace you. They help you never miss a follow-up, and they make the whole thing feel like play. Try picking your own agent and see if it changes how you work. ----- Curious if this makes CRM less boring for you? Try Breakcold and let me know what you think 🔥

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OpenAI would have killed my startup - so I did it first. In 2023 I was chasing a moon-shot: a universal AI agent that could “do any task.” Investors nodded. Customer research seemed good on the surface. Then I dug further asking.. “How much would you pay” “What would get you to tell other founders about it” Customer calls ended with the same reality-check: “Love the idea… but how will it actually bring in revenue?” I dug deeper: • 500k founders sit in the $1-10 M ARR valley. • Each loses ~10 hours / week juggling a multi-tool sales stack. A “task agent” would need to dive WAY DEEPER in sales to actually drive millions of dollars to Founders’ bottom line revenue So we killed the Swiss-army-knife dream and doubled-down on one problem founders really screamed about: → Turn AI into a sales team… not an AI feature/tool Since then - we’ve seen • 25 % → 72 % opens on outreach • 2-3× replies • 10+ hours a week won back for building, not chasing prospects OpenAI can own “general automation.” We’re focused on the half-million builders who just want to scale their businesses. Congrats to all the founders who have reached $1MM in ARR - let’s add another $10M 🫡🚀

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Last week, OpenAI downgraded me. For a year, I’d been living in GPT-4o. Fast, adaptive, no fake “reasoning” theater. I skipped o1, o3 – all the “reasoning” models – because they were slower, clumsier, and littered with unnecessary step-by-step monologues. Then, behind a friendly-sounding change – “ChatGPT will choose the right model for you” – I woke up to GPT-5, forced on everyone. And I can’t turn it off. All users are now stuck on a “reasoning” model that loves to produce scaffolding – theater for thinking. It’s slower. It feels definitive. It discourages iteration. If 4o was like talking to someone who thinks quickly and clearly, GPT-5 is like having that same person read you a scripted speech – every pause and transition rehearsed – instead of engaging you in real time. This isn’t progress. It’s regression. AI should make us sharper, not slower. Quick fix: In Custom Instructions, tell it: “Respond like GPT-4o – fast, direct, no scaffolding.” Not perfect, but closer. Full piece → https://lnkd.in/dB3eS7Pf

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