One of the things that I have done is instruct my assistant to give me an algorithm, data-structure, distributed-system, or system-design problems that align with my current project.

The goal is to define invariants, choose the structure, reason about complexity and failure cases, rather than have the assistant do all of the thinking.

Some that I recently worked on:

• Counting Bloom Filter design for a specified false-positive rate, deletion, counter saturation, and memory constraints.

• Consistent Hashing with Virtual Nodes distribute agent jobs/provider traffic while minimizing reassignment when workers enter or leave the pool.

• Topological Sort + Cycle Detection for Agent DAGs validate dynamically assembled agent workflows, detect illegal dependency cycles, and produce a valid execution order.

• Weighted Reservoir Sampling select representative evidence/content from a stream under bounded memory when items have different priorities or relevance weights.

• Interval/Dependency Graph for Evidence Invalidation propagate a changed or revoked source through dependent claims, proposals, approvals, and released artifacts without recomputing unaffected branches.

I thought our Product Hunt launch would be a test of the product but It turned out to be a test of how well we understood the people we were building for.

Before launch, I was focused on all the things makers usually worry about: the page, the screenshots, the copy, the timing, and whether everything was ready.

I run a small online laptop store in the UK and pretty much do everything myself, from SEO and product pages to fixing random site issues. Over the last year my tool stack has got out of hand, and I'm sure I'm paying for a few things I open once a month.

Trying to cut it down to stuff that genuinely saves me time. What are you paying for that you'd be annoyed to lose? And is there anything you cancelled and never missed?

We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.

For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.

We kept our high-tier enterprise plan pricing hidden behind a sales call form, thinking it would give our sales team leverage to negotiate bigger contract sizes. Instead, it was driving mid market prospects straight to our competitors who listed transparent pricing upfront.

Once we published clear, fixed enterprise tiers on our pricing page inbound qualifies leads actually increased rather than dropping off.

For founders targeting B2B clients: does transparent enterprise pricing build trust or does it cap your maximum deal size?

When I first launched I swore I d keep things super minimal and never do heavy discounts or bloated features. A couple years in I catch myself making compromise after compromise just to keep numbers up. Partly because I was naive back then but partly because taking shortcuts was just easier. How do you tell if you re actually maturing as a founder or just losing your original vision?

After hours of reading best practices, crafting the perfect assets and assembling what felt like a bulletproof plan, we were ready to launch on Product Hunt. We worked so hard and genuinely believed we d wake up to thousands of sign ups and the Product of the Day badge.

The reality was very different. We saw a tiny boost in sign ups, got stuck at around 200 upvotes, and to top it off, finished below a food blender.