The Second Screen Is a Graveyard of Good Intentions
Every creator and social media operator I know runs the same silent business underneath their public one: the business of client calls. You’re not just publishing; you’re pitching, onboarding, reporting, and revising. And on every one of those calls, there’s a moment where you scramble. You’ve got a dashboard open, a content calendar in another tab, and a client asking a question you know you answered in a strategy doc three weeks ago. You fumble. You say “let me circle back.” You lose a little authority.
That moment — the fumble — is the real problem in the creator economy that nobody’s SaaS is solving. We’ve got endless tools for scheduling, analytics, and repurposing, but almost nothing that helps us in the live conversation where deals and retainers actually get won or lost. Most AI meeting tools are archivists, not advisors. They sit in the corner, take notes, and hand you a summary after the call is over — which is exactly when you no longer need it. So when I saw Savvy on Product Hunt, built by Jaume Alavedra, I didn’t see another meeting recorder. I saw a tool that’s aimed at the exact gap between preparation and execution — the gap where trust gets built or broken.
This matters to you if you’ve ever taken a client call while juggling a brand deck, a metrics report, and a half-remembered promise from a kickoff meeting. It matters if you’ve ever wished your second screen were smarter than a static PDF. And it matters if you’re tired of AI tools that promise to “revolutionize your workflow” but actually just add another tab to your already-bloated browser. Savvy is a different bet: it’s not about doing more work after the call. It’s about being sharper during it.
The Problem: Every AI Meeting Tool Is an Archivist, Not an Advisor
Let me be blunt about the meeting-tool landscape, because I’ve tested most of it. Tools like Otter.ai and Fireflies.ai are great at what they do — they transcribe, they summarize, they log action items. But they’re fundamentally backward-looking. You finish a call, you get a summary, you file it away. The archive grows. The knowledge base expands. And then the next call starts, and you’re back to square one, searching through that archive for the one stat or the one commitment you made six weeks ago.
That’s the workflow failure I’ve hit repeatedly in my own client work. Last month, I was on a call with a brand where the creative director asked about our TikTok engagement rate for a specific campaign we ran in Q3. I had the number. It was in a report I’d sent her. I had even highlighted it in the email. But in the moment, with the clock ticking and the silence stretching, I couldn’t find it fast enough. I gave a vague “it was strong” and moved on. She didn’t push back, but I felt the dip in confidence. That’s the cost of an archive that doesn’t work in real time.
Savvy’s maker is pointing at this exact pain. The pitch on the Product Hunt page is that every AI meeting tool joins the call and mails you a summary afterward — that helps the archive, not the conversation. The insight here is sharp: the conversation is where value is created, and the archive is where value goes to die. Savvy’s bet is that you don’t need better notes; you need better presence. You need a tool that has read your documents, knows your client’s history, and can whisper the right answer into your ear at the exact moment you need it.
That’s a fundamentally different design philosophy. It’s not about capturing more. It’s about retrieving less. It’s about having the answer before the question finishes leaving the client’s mouth.
How Savvy Actually Works (And Why It’s Different From a Chatbot)
The mechanics matter here, because the difference between Savvy and a generic AI assistant is in the architecture. You point Savvy at a folder of documents — strategy decks, past reports, briefs, email threads you’ve exported — and it builds what the maker calls a “versioned brief per client.” This isn’t a single static knowledge base. It’s a living document that tracks how your understanding of a client has evolved over time. When you update a file, the brief updates. When you add a new report, the brief incorporates it. The versioning means you’re not getting a stale answer from a document you wrote six months ago; you’re getting the most recent, relevant context.
During the meeting, Savvy stays quiet. That’s a deliberate choice, and it’s the right one. We’ve all been on calls where an AI tool interrupts with irrelevant suggestions or, worse, hallucinates a fact that makes you look foolish in front of a client. Savvy only speaks up for three reasons, as described by the maker:
- The client asks something your brief already answers.
- Someone crosses a red line you set.
- You press the Advice button.
That’s a constrained interaction model, and constraints are what make AI tools trustworthy in high-stakes situations. The first case is the obvious win — you’ve prepared, and the tool surfaces the prepared answer. The second is more interesting: you can set guardrails for your own negotiations. If you’ve decided you won’t accept a scope change without a budget increase, Savvy can flag when the conversation drifts into that territory. That’s not just a convenience; it’s a negotiation superpower. The third is the manual override — you ask for advice, and the tool pulls from your documents to give you a grounded response.
Every card Savvy shows cites the document it came from. This is the trust feature that matters most. In my experience testing similar AI tools, the hallucination problem is real. I’ve had tools confidently assert facts that were flat wrong, and if I’d repeated them to a client, I’d have lost credibility. Savvy’s citation model means you can check the source before you say it out loud. That’s not a luxury; it’s the difference between using AI as a crutch and using it as a lever.
The privacy architecture is also worth noting. The tool runs on your Mac, and the maker states that files, indexes, and transcripts stay on your device — only excerpts and the audio stream leave it. For anyone working with confidential client data — and if you’re a growth marketer, you almost certainly are — this is a meaningful differentiator. You’re not feeding your client’s proprietary metrics into a cloud black box. You’re keeping the core of your knowledge local.
### Why TikTok Creators Should Care More Than LinkedIn Ones
Here’s where I’m going to make a somewhat contrarian argument. When I first saw Savvy, my instinct was to think of it as a tool for agency folks and consultants — the people who take formal client calls with decks and agendas. And that’s true, as far as it goes. But the creator-economy angle is broader, and it’s especially relevant for TikTok creators and Instagram creators who are moving into brand partnerships and sponsored content.
The reason is that the sales cycle for a TikTok creator is compressed and chaotic. You’re not pitching through a formal procurement process. You’re DMed by a brand manager, you hop on a quick call, and you have about fifteen minutes to convince them you understand their product, their audience, and their goals. There’s no time to search through your own content archive. There’s no time to pull up the engagement metrics from your last three sponsored posts. You either have it at your fingertips or you don’t.
LinkedIn-focused B2B creators have a different rhythm — longer sales cycles, more documentation, more time to prepare. They’re more likely to have a CRM and a formal proposal process. But the TikTok creator is operating on speed and instinct, and that’s exactly where a tool like Savvy could be a game-changer. Point it at your media kit, your past campaign results, your rate card, and your audience demographics. When the brand manager asks “what did you see with that skincare brand last quarter?” you’ve got the answer, cited, in real time.
The flip side is that TikTok creators are less likely to run a Mac-based workflow — many of them live entirely on their phones. And they’re less likely to have a folder of documents to point at. Savvy’s value scales with the depth of your documentation. If you’re operating on vibes and screenshots, you’re not the target user. But if you’re a serious creator who treats your brand partnerships like a business, the documentation exists, and Savvy gives you a way to actually use it in the moment.
The Incumbent Comparison: Why This Isn’t Just Another Meeting Recorder
To understand what Savvy is doing differently, you have to stack it against the incumbents. The meeting-AI space is crowded, and the big players have moved fast. Otter.ai has transcription and summaries. Fireflies.ai has conversation intelligence and search. Loom has async video with AI features. And then there are the scheduling and social media management tools like Buffer, Hootsuite, and Metricool — they handle the content side, but they don’t touch the live conversation.
The distinction I’d draw is between capture and activation. Otter and Fireflies are capture tools — they record and organize information for later use. Savvy is an activation tool — it puts information into play during the conversation itself. That’s a fundamentally different category, and it has different design implications. Capture tools can afford to be passive; they just need to record accurately. Activation tools have to be judgment-based; they need to decide what’s relevant right now and surface it without being annoying.
That’s a hard design problem, and it’s why most tools don’t attempt it. The risk of being annoying is high. If Savvy interrupts a call with a card that’s even slightly off-topic, the user loses trust. If it surfaces a document that’s outdated, the user loses face. The maker has mitigated this with the three-reason constraint, but the execution risk is real. I’d bet the hardest engineering work here isn’t the document indexing — that’s solved. It’s the relevance ranking — knowing when a piece of information is important enough to interrupt the flow of a human conversation.
There’s also the question of where this fits in the broader stack. For social media teams, the workflow is usually: content calendar in Later or Buffer, analytics in Sprout Social, design in Canva or CapCut. Savvy is a different layer — it’s not about the content itself, but about the business conversations around the content. It’s the tool that helps you pitch the retainer, justify the rate increase, and close the renewal. That’s a layer that’s been underserved, because it’s harder to productize. You can’t just build a calendar and call it done; you have to understand the messy, unstructured flow of client communication.
What Creators and Social Media Teams Can Borrow From Savvy (Even If They Don’t Buy It)
Here’s where I want to shift from product review to operational philosophy. Whether or not you download Savvy — and it’s open source, MIT-licensed, so you can look at the code on GitHub — there are three operational lessons embedded in this tool that every social media operator should steal.
Lesson one: Prepare context, not just content. When I schedule 30 posts across 5 platforms in a month, I’m thinking about content — what to publish, when, and where. But the calls I have with clients are about context — why we’re publishing this, what we expect from it, and how it fits into the larger strategy. Savvy’s insight is that you should prepare for the conversation the same way you prepare for the campaign. Build a brief per client that includes your goals, your metrics, your red lines. Update it religiously. That’s a habit you can adopt without any new software — just a folder and a discipline.
Lesson two: Constrain your AI. The most dangerous AI tools are the ones that answer every question with equal confidence. Savvy’s three-reason model is a masterclass in constraint. It only speaks when it has something specific and useful to say. When you’re evaluating AI tools for your own workflow — whether it’s for content generation, analytics, or meeting notes — ask yourself: does this tool have a clear sense of when to stay silent? If it doesn’t, it’s going to create noise, not signal.
Lesson three: Cite your sources. The citation feature in Savvy is not a nice-to-have; it’s the trust mechanism. In my own work, I’ve started adding source links to every client-facing metric I share. It takes an extra ten seconds, but it changes the dynamic of the conversation. Instead of “trust me, engagement is up,” it’s “engagement is up 18%, and here’s the report that shows it.” That’s a small habit with an outsized impact on client confidence.
Where the Math Breaks: Limitations and Open Questions
I’m not going to pretend Savvy is a silver bullet, because it isn’t. There are real limitations, and you should know them before you invest time in setting it up.
The documentation prerequisite is steep. Savvy only works if you have a folder of documents to point it at. If you’re a creator who keeps everything in your head, or a small team that operates out of group chats and screenshots, the tool starts with nothing. You’d have to build your briefs from scratch, and that’s a significant upfront investment. The tool is only as good as the context you feed it.
The macOS constraint is real. It runs on Apple Silicon, macOS 13+. That’s a meaningful chunk of the creator economy, but it’s not everyone. Windows users are out. And even among Mac users, the “runs on your Mac” architecture means the tool is tied to a single device. If you take calls on your laptop but prepare on your desktop, you’re going to have sync friction.
The audio stream leaves the device. The maker is transparent that while files, indexes, and transcripts stay local, “excerpts and the audio stream” leave the device. For highly confidential client work — say, a pre-IPO brand or a sensitive rebrand — that might be a dealbreaker. The local-first architecture is better than most cloud tools, but it’s not air-gapped.
The scale of the knowledge base is untested. I don’t know how Savvy handles a folder with 500 documents versus 50. I don’t know how the relevance ranking degrades as the brief gets larger. The maker hasn’t disclosed performance benchmarks, and I’m not going to invent them. My hunch — and this is my opinion, not a sourced fact — is that the tool will work best with a curated, focused folder, not a dump of everything you’ve ever touched.
Who this is NOT for: If you’re a solo creator who does everything on your phone and never takes formal client calls, skip this. If you’re a team that uses a CRM like HubSpot and has a formal sales process, you might find Savvy redundant — your CRM should already have this context. And if you’re not prepared to maintain your briefs, the tool will go stale fast. This is a tool for people who treat client relationships as a knowledge-management problem, not a vibes problem.
What I’d Watch / Test Next
If this resonates with you, here are the concrete steps I’d take this week — whether you adopt Savvy or just steal its philosophy.
First, audit your client-call prep. Before your next call, open your desktop and count how many documents you actually reference. If the answer is “zero” or “I just wing it,” that’s your gap. Start a folder per client. Drop in your strategy doc, your last three reports, and your rate card. That alone will change the quality of your calls.
Second, test Savvy on a low-stakes call. The tool is free and open source, so the cost of entry is just your time. Pick a client where you have good documentation but the relationship isn’t make-or-break. Set up a brief, define one red line, and see how the tool behaves. Pay attention to the relevance ranking — does it surface the right document at the right moment, or does it interrupt with noise? That’s the make-or-break test.
Third, build a citation habit. Even if you don’t use Savvy, start adding source links to your client communications. When you report a metric, link to the report. When you make a recommendation, link to the strategy doc. It’s a small change that signals rigor and builds trust faster than any AI tool ever will.
Fourth, watch the open-source angle. The fact that Savvy is MIT-licensed is interesting. It means the community can fork it, extend it, and integrate it with other tools. I’d bet we see integrations with Notion or Slack before long. If you’re technically inclined, the GitHub repo is worth a look — not just for the code, but for the design decisions embedded in it.
The bottom line: the creator economy is maturing, and the tools are maturing with it. We’ve solved scheduling. We’ve solved analytics. We’re starting to solve repurposing. The next frontier is the live conversation — the place where trust is built or eroded in real time. Savvy is an early bet on that frontier, and even if it’s not the final answer, it’s pointing in the right direction. The question isn’t whether AI will help us in meetings. It’s whether we’ll have the discipline to feed it the context it needs to actually help.
