Mac Tichner

Mac Tichner / AI-native software engineer

I build AI-native software that helps teams ship.

I work where AI, product engineering, and developer experience meet: practical tools, clear systems, and the judgment to keep quality from drifting.

Meet with me ->Email me->

Experience

How I got here.

The short version: I like building things. Products, systems, teams, the internal tools that make work better, and now a lot of practical AI inside day-to-day software work.

01 / GrowthLoop

AI Everything

GrowthLoop

Now I am deep in the practical version of AI: where it helps, where it does not, and what it takes to turn it into shipped software.

At GrowthLoop, AI is not a side topic. It is part of the work: how we build, how we operate, how we make internal tools, and how we help people do more with less drag.

Adding AI to the way we already built software is the obvious first move. The harder work is turning it into reliable product behavior, useful internal tools, better review loops, and systems people can trust.

The interesting part is not that AI writes code. The interesting part is what one engineer can now own, and what a team becomes when the culture knows how to absorb that leverage.

02 / Medidata

Enterprise Scale

Medidata Solutions, Principal Software Architect

Medidata taught me how different building feels when the system is large and the stakes are real.

Enterprise architecture is not just diagrams and big words. It is helping teams make choices that survive scale, regulation, legacy systems, dependencies, and long-running consequences.

At Medidata, I spent a lot of time around the human side of technical decisions: alignment, trust, rollout plans, and making sure the right people understood why a direction mattered.

That gave me a useful respect for constraints. A good idea is only good if it can actually land inside the organization that has to live with it.

03 / Perksy

Startup Scaling

Perksy, SVP Engineering

At Perksy I moved from building the thing to building the team that builds the thing.

Perksy was where engineering leadership became real for me. The work was still technical, but the highest leverage started coming from hiring, coaching, setting direction, and helping people make better decisions together.

I learned that a good team is not just a group of strong engineers. It is a system: ownership, standards, feedback loops, trust, and enough shared taste to move quickly without making a mess.

That experience shapes how I think about AI adoption too. Faster output only helps if the team has the habits to keep quality from drifting.

04 / building from zero

Founder

3x Founder CTO

I learned by building three startups from zero through acquisition.

Being a founder forces you to do the whole job: talk to people, figure out what matters, build the thing, fix what breaks, and keep moving when the answer is not obvious.

That is still the mode I like best. I enjoy the messy early part where the product is half idea, half prototype, and every week teaches you something.

It also made me allergic to theater. If a tool, process, or AI workflow does not make the work better, it is not worth much.

What I care about

A few things I care about.

AI is only interesting when it changes the work.

The useful version is not a demo or a better prompt. It is code, tools, and workflows that change how real software gets planned, built, reviewed, and shipped.

Team habits decide whether the tools matter.

AI can raise output, but output without taste just creates more to clean up. The best engineering work still depends on ownership, standards, feedback loops, and enough shared taste to move quickly without making a mess.

Developer experience is still the operating system.

Broken deploys, slow review, noisy tooling, and unclear paths to production all compound. Fix the friction and the same engineer does better work, with or without AI. Add AI on top of that and the gains are real.

Default settings

  • Culture is the multiplier.

  • AI is the accelerant.

  • Shipping is the proof.

Say hi

Email.

Projects, questions, or interesting problems.

If you are building something, wrestling with an AI idea, or trying to make an engineering team work better, email me. I like talking to people who make things.

Build with me.

Software, prototypes, internal tools, AI workflows.

I am usually most useful where product, engineering, and AI meet: figuring out what to build, making it real, and helping teams use it well.

Talk shop.

Engineering, teams, AI, leadership.

I am always up for a concrete conversation about building software, leading engineering teams, and what AI is changing in the work.

Book a call->