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Cien Solon

Cien Solon

Secure AI agents | CEO at 🍋 LaunchLemonade

GBAISoftwareGrowth / GTM
Available to book
21.3K
Followers
510
Est. median reach
0.1%
Engagement

About

CEO | Founder @ launchlemonade

AI is already being used inside your firm, but it’s happening in the shadows. Scattered tools. Different workflows. No visibility. No control. That’s the problem we’re solving at LaunchLemonade. We help regulated firms turn fragmented AI usage into a system they can see, control, and scale. Since we launched in 2024, we've had; 20,000 AI agents built, 1,500,000 conversations. AI your regulated firm can actually rely on. Message me directly to book a walkthrough

AISoftwareGrowth / GTM

Audience & average metrics

21.3K
Followers
510
Est. median reach
10
Avg reactions
3
Avg comments
0.1%
Engagement
GB
Based in

Stats updated 28 d ago

Recent posts

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I've been training people around the world, but I’ve rarely ventured up north in the UK. Next week, I’ll be in Manchester for my first tour with Lauren Mucklow, Founder of What She Said. We’re hosting a Build and Breakfast event with some fantastic female business owners. This hands-on session will focus on building AI agents tailored for your business. Where real work makes a difference. I can’t wait to connect! Get your tickets today, ofc. The link is in the comments! 🍋

32
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The most important AI decision your business makes is to refuse to marry a single language model. I said a version of this on a panel last week and watched half the room write it down, so let me make the full case here. The "best model" race has stopped being the interesting race. In the past week alone, Moonshot released Kimi K3, which lands just behind the top proprietary models on independent rankings while costing roughly half as much to run, and Mira Murati's Thinking Machines shipped Inkling while openly saying it isn't the strongest model available, because it isn't trying to be. These labs have worked out what most buyers haven't, that "competitive at a fraction of the price" beats "best" for almost every real business task. Nobody needs the smartest model on earth to summarise a contract or draft a client report, and paying frontier prices for routine work. Yet businesses still run AI procurement like a wedding, months of evaluation to pick the one, workflows and contracts all shaped around a single lab, and then a cheaper model that's 95% as good ships eight weeks later and switching would somehow cost more than staying wrong. The companies getting significant value treat models the way they treat supplier, they are swappable, negotiable, and answerable to results. The expensive model takes care of the hard problems, the cost-effective one takes the volume, and when something better or cheaper ships, it gets tested against real work by Friday. That posture also does wonders for pricing conversations, because a lab that knows you can leave behaves very differently from one that knows you can't. Marry your standards. Date your models. All the zest, 🍋 Cien

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Last Wednesday, Mira Murati released her first AI model and told everyone it isn't the strongest one available, and I think that admission is the most interesting launch of the year. For anyone who hasn't followed her story, Murati was OpenAI's CTO until she left in 2024, founded Thinking Machines Lab, and raised $2 billion before shipping. The model is called Inkling, and it's open weight, which means you can download it, run it where you like, and finetune it around your own data rather than renting intelligence from a lab. Her bet is that businesses care less about the smartest general model than about a model they can make their own, because a firm with fifteen years of process knowledge gets more from an open model trained on how they actually work than from the cleverest black box on the market. I've been arguing a version of this for two years, so of course I agree with her. The model was never the point, and your data along with everything you wrap around it decides whether AI does real work for you or produces impressive nonsense. We built LaunchLemonade model agnostic for exactly this reason, so Inkling is live on the platform alongside the frontier models, for you to try out! Build an agent, swap the model underneath it, and see for yourself how much of the result comes from the model and how much comes from everything else. The frontier labs are betting you'll keep renting, while Murati is betting you'll eventually want to own. What I don't know yet is whether small firms realise that choice is now theirs to make.

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Before ChatGPT and Claude, I helped build an AI chatbot used by millions of people. It took somewhere between six and twelve months, a large cross-functional team, and a significant amount of infrastructure. We built the database and knowledge base, mapped customer queries, then trained the system using natural language processing and machine learning. When it launched, it improved the company’s resolution rate by double digits. Today, one person can build the first version of that chatbot in an afternoon. That does not mean the results are automatic. You still need good data, clear use cases, thoughtful design and proper testing. But the cost and complexity of getting started have collapsed. Capabilities that once required a large budget, a specialist team and months of development are now available to almost anyone. #launchlemonade #ArtificialIntelligence #AILeadership #WomenInTech

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After almost 3 years of running AI workshops, I can confirm every office contains the same five AI users, and I say this with love because I've been at least three of them. 1. There's the Secret Cyborg, who swears they don't really use AI while producing suspiciously polished reports at suspicious speed, and whose browser history would end the charade in seconds. 2. There's the Doomsday Correspondent, who has never actually opened ChatGPT but forwards every article about AI taking jobs, adding "worrying!!" as analysis. Knows more about what AI will do in 2030 than what it can do on a Tuesday. 3. There's the One Prompt Wonder, who tried it once in 2023, got a mediocre paragraph, declared the whole technology overrated, and has been dining out on that verdict ever since. 4. There's the Maximalist, who runs everything through AI including two-line emails to their own team, and whose messages now read like they were written by a Victorian butler with a marketing qualification. Enthusiasm ten, judgement pending. 5. And there's the one nobody notices, the Delegator, who doesn't talk about AI at all. They just worked out which three tasks it does well, briefed it like they'd brief a person, check everything before it ships, and leave at five. Everyone secretly wants to be come the delegator. The good news I spend most of my time delivering, is that the gap between the other four and the Delegator isn't talent or a technical brain. But it's treating AI like a hire instead of a magic trick, and that's a skill anyone who's ever managed a person already owns. Tag your Secret Cyborg. They'll deny it, which proves it. All the zest, 🍋 Cien

150

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Who likes and comments on this creator's posts, inferred from their LinkedIn titles.

By seniority
Founder / C-level86%
VP / Head / Director7%
Manager / Lead7%
By function
Founders 55%Engineering / Data 19%Marketing 13%Sales / BD 9%Product 2%HR / Talent 2%

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