Akshay Sajeev

I’ve used SEMrush when SEO needed to move from guesswork to signal. SEMrush gives visibility into keywords, site health, backlinks, and competitor movement in one place.

I’ve used it to identify content gaps, track ranking shifts, audit sites, and understand why competitors were gaining traction.

It takes some time to get comfortable with the depth, but once you do, SEMrush becomes a dependable companion for anyone working seriously on search and organic growth

I experimented with Phantombuster while exploring ways to automate data collection without writing custom scripts. Phantombuster provides ready-made automations for scraping, extracting lists, and running workflows on a schedule.

The value is speed. You configure intent rather than build everything from scratch. It is easy to test and chain actions.

It requires care to stay within platform limits and ethical use but for anyone experimenting with scraping and automation, Phantombuster gives you a lot to work with right out of the box.

Forms get annoying fast once logic is involved. Tally keeps things simple.

You write forms like a document and add conditional logic naturally. Hidden fields, branching, and redirects are easy.It’s been reliable for client intake, internal workflows, and structured data collection.

It doesn’t try to be enterprise software, and that’s a good thing and It is one of the easiest ways I have found to build forms with conditional logic, especially when speed and simplicity matter.

I used Glide during college while experimenting with product ideas. I built a small dApp called dApp, loosely inspired by Bumble, to test an idea quickly.

Glide lets you turn spreadsheets into working apps with screens, logic, and actions. The feedback loop is fast.

I could prototype flows, change structure, and ship usable versions without getting blocked by code. That made experimentation addictive.

It is not meant for complex or deeply custom systems but for quick MVPs and early experimentation, Glide does a solid job of helping ideas come alive fast.

I’ve used Merlin while working across multiple LLMs and long-running problem spaces. Context loss was the main bottleneck.

Merlin lets you organize AI work around projects and shared context while using different models in one place. That alone changes how you work with AI.

I used it to carry conversations forward, reuse background, and avoid re-prompting from scratch. Comparing outputs across models without breaking flow was useful.

It shifts AI usage from one-off prompts to cumulative thinking.

It does not try to replace judgment or creativity. But as a way to organise AI work around context, projects, and multiple models, it has been genuinely useful.

I explored Dhisana while looking at emerging sales automation tools.

I did not use it deeply, but the direction was clear. The product aims to automate large parts of the sales workflow while preserving context and intelligence.

Features around outreach, automation, and insight tracking appear well thought through. It feels built by people who understand sales friction. Dhisana feels early, but the foundation is solid. For teams exploring next-generation sales automation, it is a product with real upside and one worth watching closely.

I’ve used Kanbox when I needed a simple way to visualise work without turning task management into a system of its own.

It works best when the goal is clarity. Tasks move through stages, ownership is visible, and nothing more is added than what is necessary. That simplicity makes it easier to focus on progress rather than configuration.

I did not use it for complex project planning or reporting. It is not designed for that. But for keeping day-to-day work visible and lightweight, it holds up well.

Kanbox fits teams or individuals who want a clear sense of flow and priorities without layering process on top of execution.