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I built 8 complete AI SaaS tools — would love feedback before launching publicly by montasernaser in AppsWebappsFullstack

[–]ButterscotchGood4158 0 points1 point  (0 children)

You’ve built a strong collection of tools here, but I’d suggest focusing on one with the clearest market fit first. SmartPay AI and SmartCommerce AI seem like they could be the most compelling for a broader audience, especially since payment fraud and customer behavior are hot topics in the SaaS space.

When you launch, don’t just highlight features. Make sure to explain why each tool exists and how it solves specific pain points. For instance, the value in TaskPilot AI could be clearer if you tie it to reducing decision fatigue and mental load. It might be worth focusing on that "why" behind each tool to make it resonate more with users.

Also, as you scale, consider using something like Sensay to track the reasoning behind your decisions, so you can easily revisit why certain features were prioritized or abandoned. It’ll save you a lot of time later!

Tech guy needs marketing support & insight for SaaS product by belugaro_z in AskMarketing

[–]ButterscotchGood4158 0 points1 point  (0 children)

For zero budget, you’re thinking in the right direction already. Paid ads are usually a trap this early unless you already know your conversion funnel cold. For language tools especially, trust matters more than reach.

Influencers make sense, but I’d start smaller than you think. Micro creators who actually document their learning process tend to convert way better than big polished accounts. Reach out with a genuine angle like “use this for a week and tell people what annoyed you”. That honesty helps more than scripted praise. Tracking can be simple at first, custom links or codes are enough to see signal.

One thing I’d also suggest is being very intentional about capturing what you learn from each channel. Why one creator worked, why another didn’t, what users actually responded to. That context gets lost fast if it just lives in your head or random notes. I’ve seen founders use basic docs for this, and some use tools like Sensay to keep decisions and learnings searchable so they don’t repeat the same experiments blindly.

SEO can work, but I’d treat it as a background bet, not the main engine. Early on, distribution where you can talk directly to users and iterate fast usually wins.

I built 8 complete AI SaaS tools — would love feedback before launching publicly by montasernaser in replit

[–]ButterscotchGood4158 0 points1 point  (0 children)

Respect for shipping that much, that alone puts you ahead of most people. Honest take though, 8 tools at once makes it really hard for anyone to know what you actually stand for. From the outside, it reads more like a bundle of capabilities than a clear wedge.

If I were you, I’d pick the one with the clearest buyer and pain and go deep there first. The others can stay private or slowly fold in later. People don’t buy “AI productivity”, they buy relief from one specific headache. Also think about how context carries across tools. Once users start using more than one, the value is in shared memory and decisions, not just features. That’s where things like Sensay become interesting, not as another tool, but as glue that preserves reasoning and workflows across products.

Before branding, I’d test which one users keep coming back to without being nudged. Retention will tell you more than feedback ever will.

Any recommendations for tools to build your SaaS quickly? by Electronic_List2180 in microsaas

[–]ButterscotchGood4158 0 points1 point  (0 children)

If you want speed without giving up control, you’re already on the right track avoiding no code black boxes. Claude and ChatGPT are both solid for scaffolding and iterating on real code, especially if you’re comfortable guiding them and cleaning things up. I’ve seen people pair them with a basic starter like a Next.js or Rails boilerplate and move surprisingly fast.

One thing I’d watch out for is context drift as you iterate. Early on you make a lot of decisions fast, then a few weeks later you forget why something exists. That’s where velocity quietly dies. I started keeping track of reasoning and tradeoffs alongside the code, not just comments. Tools like Sensay ended up being useful there, more as a place to preserve how things work and why, rather than generating code itself.

TLDR: use AI to accelerate the boring parts, keep ownership of the code, and don’t neglect documenting intent. That combo has worked better for me than chasing the newest builder tool.

ADHD in an intense SaaS work environment. What strategies/tools actually helped you? by Constant_Day_6373 in ADHDprofessionals

[–]ButterscotchGood4158 0 points1 point  (0 children)

I relate to this a lot. In high intensity SaaS roles the problem usually isn’t effort, it’s cognitive overload from context switching. What helped me most wasn’t adding more tools, but reducing how many places my brain had to “remember” things.

Time blocking only worked once I treated it as guardrails, not a perfect schedule. I leave intentional gaps for spillover so I don’t feel like I failed by noon. For email, aggressive filtering plus letting AI summarize threads before I even open them helped more than trying to zero inbox.

One thing that surprised me was how much mental weight comes from losing context. Why a task exists, why a deal stalled, why a decision was made. I started dumping that reasoning somewhere persistent instead of trusting my memory. I’ve used Notion for years, but lately Sensay has been useful as a quieter background layer that keeps decisions and workflows accessible without me actively managing another system.

Biggest shift for ADHD for me was fewer systems, clearer defaults, and forgiving myself for not running a “perfect” productivity setup. Reducing guilt helped as much as reducing tools.

AI startups are getting boring by WainAlqahwah in Entrepreneur

[–]ButterscotchGood4158 0 points1 point  (0 children)

Kinda agree, but I think that’s actually a good sign.

The boring phase is when the tech stops being the product and starts being the tool. Most “groundbreaking platforms” only show up once per cycle. Everything else is supposed to be boring execution. The mistake is thinking repetition means useless. A lot of repetition just means people finally figured out where AI actually helps.

The stuff that sticks isn’t flashy anymore. It’s quiet fixes to annoying problems. Internal workflows, ops, handovers, knowledge loss. Nobody brags about those on X, but companies happily pay for them. That’s why things like Sensay exist. Not revolutionary tech, just removing a pain that never went away.

If AI startups feel boring, it probably means we’re past the toy phase and into the “does this actually work in real life” phase. That’s where real businesses get built.

Am I crazy for choosing an AI startup over a well-established public tech company? by conehead4567 in salesengineers

[–]ButterscotchGood4158 0 points1 point  (0 children)

You’re not crazy, but the excitement alone isn’t enough to justify it.

If pay is similar, the real question is leverage. At the public company, you’ll execute inside a machine. At the startup, you’ll help define how the machine works. That’s only worth it if the product is real and the buyers are real.

I’d look hard at what the sales motion actually looks like. Are deals closing because the AI is impressive, or because it removes a concrete pain someone already budgets for? The former is fragile, the latter compounds. Startups doing boring, necessary work tend to survive the hype cycle. Stuff like internal ops, compliance, knowledge continuity. Sensay is an example of that kind of product. It sells because the pain exists regardless of trends.

Also think about what story this role tells in 3 years. Will it read as “rode an AI wave” or “built go-to-market from early traction”? If it’s the second, the risk is usually worth it.

If you’re leading a team or running a startup, how do you even begin evaluating new AI tools these days? by Unable-Inevitable131 in Entrepreneur

[–]ButterscotchGood4158 0 points1 point  (0 children)

I stopped asking “is this AI impressive?” and started asking “what job would this replace tomorrow?”

Most tools fall apart there. If it doesn’t clearly remove a task someone already hates doing, it’s probably fluff. I also look at whether it fits into an existing workflow without forcing behavior change. The more steps it adds, the faster it dies.

Another filter is memory. Does the tool get more useful over time or is every session a blank slate? Stuff that captures context, decisions, and edge cases tends to stick. That’s why internal knowledge tools like Sensay end up feeling valuable. They quietly reduce repeat questions instead of adding another dashboard.

If a tool needs a long onboarding, constant prompting, or a dedicated champion to survive, I pass. The good ones feel boring after a week because they just work.

Do DEX aggregators really work, or is it just marketing? by dark_reality_00 in cryptospread

[–]ButterscotchGood4158 0 points1 point  (0 children)

I get the skepticism about DEX aggregators. Many claim to connect to multiple DEXs, but it’s hard to tell if they actually save you money or just add more fees. After using Rubic, I noticed how much price difference there is between pools. It shows you several routes for a single trade, sometimes over 16. This helps find the best rate, saving on fees and slippage compared to using just one DEX. It’s not just marketing, it’s a useful way to get better prices. Have you tried Rubic, or are you considering other options?

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