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10 Reasons Selling AI Tools to Developers is Challenging
Nowadays, everyone (including me) wants to sell AI-powered tools, platforms, or products. Few people (including me 6 months ago) have any idea how hard it is to approach and convince technical people for at least 10 reasons: 1 - They're constantly bombarded with messages. 2 - Everyone sells everything, so supply >>> demand. 3 - Extremely high background noise. 4 - They see an AI-generated message from 10km away (they've trolled me several times). 5 - If they have to go through a demo to try the product, they've already closed the tab. 6 - The opinions of devs, who value any glossy slide, count much more. 7 - Product trials are unforgiving; it's like being in court accused of 16 murders. If they find bugs or poor performance at that point, for them the product is broken and the window closes. 8 - They always have a plan B: I'll make it myself. Only 9 - If you don't have a solid track record (or you studied biotech like me), everything is 10x harder. 10 - Like the MasterChef judges, who used to be just chefs and now are atomic hotties, today's CTOs and top devs are stars; literally everyone wants them. It seems easier to scale a dev tool today because there are infinite tools, but in reality it's really tough. On the one hand, you have to earn the trust of technical teams through intros, messages, calls, and events; on the other, you have to scale at the speed of light because you're only six months old. Advice, ideas, scathing comments, insults? Anything goes. \*Not true
AI Skill Files: Warm Starts for Claude and Gemini Sessions
One thing that frustrates me about most AI workflows is the cold start problem. Every new session you re-explain your business, your voice, your clients. I started solving this with skill files. A skill file is a markdown document you upload to a Claude Project or paste into a Gemini Gem. It holds your context permanently so you never re-explain anything. The three I use most: brand-voice.md: defines tone, writing rules, and platform-specific formatting client-router.md: when you say a client name, Claude loads their full project context automatically seo-aeo-audit-checklist.md: structured audit that scores any website out of 100 across 7 sections including AI search visibility Anyone else using a similar system? Curious what context you keep persistent across sessions.
AI Tool Locus: Autonomous Business Operations
This sub has seen enough "AI can now do X" posts to have a finely tuned radar for what's real and what's a demo that falls apart the moment someone actually uses it. So I'll skip the hype and just tell you what we built and where the edges are. The core problem we were solving wasn't any individual capability. Generating copy is solved. Building websites is solved. Running ads is mostly solved. The unsolved problem was coherent autonomous decision making across all of those systems simultaneously without a human acting as the integration layer between them. That's what we spent most of our time on. Locus Founder takes someone from idea to fully operational business without them touching a single tool. The system scopes the business, builds the infrastructure, sources products, writes conversion optimized copy, and then runs paid acquisition across Google, Facebook and Instagram autonomously. Continuously. Not as a one time setup but as an ongoing operation that monitors performance and adjusts without being told to. The honest version of where AI actually performs well in this system and where it doesn't: It's genuinely good at the build layer. Storefront generation, copy, pricing structure, initial ad creative, coherent and fast in a way that would have been impossible two years ago. The operations layer is more complicated. Autonomous ad optimization works well within normal parameters. The judgment calls that fall outside those parameters, unusual market conditions, supplier issues, platform policy edge cases, are still the places where the system makes decisions a human would immediately recognize as wrong. That gap between capability and judgment is the most interesting unsolved problem in what we're building and probably in the agent space generally right now. We got into YCombinator this year. Opening 100 free beta spots this week before public launch. Free to use, you keep everything you make. For people in this sub specifically, less interested in the "wow AI can do that" reaction and more interested in people who want to actually stress test where the judgment breaks down. Beta form: [https://forms.gle/nW7CGN1PNBHgqrBb8](https://forms.gle/nW7CGN1PNBHgqrBb8) Where do you think autonomous business judgment actually gets solved and what does that look like?