Siyani 👨‍💻 @HLSCodes

AI Developer by day, building things nights and weekends. Building: https://t.co/n6xGYXf6Pc (waitlist), scaling: https://t.co/PEG7yqEueZ harshilsiyani.com Joined July 2020

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Siyani 👨‍💻 @HLSCodes

3 weeks ago

@businessbarista AI

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Siyani 👨‍💻 @HLSCodes

3 weeks ago

@Arnavmj Tool

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Siyani 👨‍💻 @HLSCodes

a month ago

@johnvirality Cluely

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Siyani 👨‍💻 @HLSCodes

2 months ago

@aryanXmahajan OS

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Siyani 👨‍💻 @HLSCodes

2 months ago

@vitaliidodonov MRR

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Three ways to wire up AI agents: 1. Sequential — pipeline. Each step depends on the last. 2. Parallel — fan out, aggregate. Speed and diverse opinions. 3. Loop — repeat until an exit condition flips. Most production systems nest all three. The hard bits are always the aggregator and the exit condition.

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Siyani 👨‍💻 @HLSCodes

2 months ago

Hackathons aren't for the prizes. They're how people find out what you can do. Won People's Choice at a global one last year. Led end-to-end. Built async with teams across 3 countries. The prize was a line on a CV. The reputation it built is what's still paying off.

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Siyani 👨‍💻 @HLSCodes

2 months ago

@atlasfunded .

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Siyani 👨‍💻 @HLSCodes

2 months ago

@recap_david Newsletter

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Siyani 👨‍💻 @HLSCodes

2 months ago

Wrote a script that fires 500 concurrent requests at production before launching. Waitlist signups, app creation, dashboard generation. All at once. Zero crashes across 1,300 operations. P95 latency doubles past 200 concurrent. 30 minutes of work that tells you exactly what to upgrade before peak traffic. Beats guessing at 2am when the server's on fire.

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Siyani 👨‍💻 @HLSCodes

2 months ago

25 posts on X over 65 days. Net followers: minus 3. 411 total impressions. 18 likes. 7 profile clicks. The engineering-heavy posts about agent architecture and confirmation bias? Zero profile clicks across 6 of them. The personal ones: Kenya to Melbourne, marathon training, the wife's Google Sheets question. Two thirds drove a profile click. Lesson: at under 1,000 followers, every post needs a personal hook in line one. Technical insight goes in the body. Restarting with that rule. Will report back.

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Siyani 👨‍💻 @HLSCodes

2 months ago

@tibo_maker BACKLINK

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Siyani 👨‍💻 @HLSCodes

2 months ago

@vitaliidodonov @IAmPascio MRR

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Siyani 👨‍💻 @HLSCodes

3 months ago

@businessbarista AI-native

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Siyani 👨‍💻 @HLSCodes

3 months ago

@AgodiDivin32690 Thanks for this. I did run this through Claude Design and got similar feedback where the suggestion was to talk about the pain and not what it is. Would be great to see what you come up with

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Siyani 👨‍💻 @HLSCodes

a year ago

Can I get help with someone roasting or if you’re nice :) then providing feedback on my landing page. Promptperf.dev I don’t have thousands of users to do A/B testing. Does the page provide clear messaging, explain the problem and set the right expectations?

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Siyani 👨‍💻 @HLSCodes

3 months ago

Built an ROI model across 6, 12, 18, and 24 month horizons. Presented it to finance leadership. It led to budget approval. The trick: I didn't pitch technology. I pitched business outcomes with honest risk modelling. Finance people don't care about your architecture. They care about the shape of the cost curve.

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Siyani 👨‍💻 @HLSCodes

3 months ago

Entered the Australian Defence Tech Hackathon with my brother. Most teams built hardware + software. We were software-only. Built an edge-deployed vision-language model under 2GB for real-time audio narration of video feeds. Got to 1.4 second latency, targeting sub-1 second. Didn't win. Bit of a wake-up call about what happens when hardware and software are designed together.

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Siyani 👨‍💻 @HLSCodes

3 months ago

Most AI developers test informally. "Does the output look right?" I built 200+ automated tests for a client project. 70 specifically test AI output quality. They detect when a model degrades. They gate every model switch. Before deploying a new model, the test suite proves it's better than what's in production. Boring infrastructure. Makes AI trustworthy.

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Siyani 👨‍💻 @HLSCodes

3 months ago

Thats insightful. Well usually when creating a persona it’s a demographic. So in my case teachers, small business owners, etc were my ideal customers. Instead of building 1 teacher 1 SME which doesnt truly reflect broader profession I build variations of them at different pay level, different lifestyle etc And yes the drift occurs agreed. To mitigate this, Ive been giving particular tools and data. Like connected the waitlist form, posthog mcp server so can see the analytics and demographics etc. This doesnt give the whole picture but helps me understand better

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Siyani 👨‍💻 @HLSCodes

4 months ago

I don't have real users yet. So I built 76 AI personas to simulate them. Each has a name, age, tech level, and use case. I poll them on every product decision. Zero of them said "launch now" when I asked 3 weeks ago. This is simulation, not real user research. But it's better than guessing alone. The personas have caught pricing mistakes and priority errors I would have missed.

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Siyani 👨‍💻 @HLSCodes

3 months ago

Won People's Choice at a global hackathon. After that, engineers from a completely different division reached out with AI accuracy problems. I'm an individual contributor, not a manager. But I diagnosed the root cause, improvements landed, and it led to deeper sessions with their senior team. Sometimes your reputation is your org chart.