Trendkill Systems
AI made your team faster at writing code. Not better at shipping software. We embed with your org for a month, write the action plan it actually needs, and implement it with you until the quality holds on its own.
01 · Services
Probably not another vendor. Twenty years of engineering leadership, brought in fractionally. AI is where most teams need that leadership right now, so that's where a lot of the work lands. The job underneath hasn't changed: build a team that ships good software.
A VP of Engineering in the room when it matters. Hiring plans that survive contact with reality. A roadmap your investors and team actually believe.
Your engineering org bought the tools and skipped the operating model. That's backwards. We install the standards that make LLMs and coding agents compound instead of corrode: review gates that hold, guardrails that mean something, and adoption you can measure in shipped work. Not tokens spent and LOC.
02 · Adoption
Your engineers figured this out months ago. Meanwhile finance is still copying numbers between spreadsheets and HR answers the same policy question forty times a week. The fix isn't another SaaS seat. It's an engineer sitting next to the people doing the work. Palantir calls them forward deployed engineers. We embed as the first one, ship something real, then build the function so your team keeps going without us.
Every department has a wish list. Most of it is noise. We watch how the work actually happens and find the handful of workflows where automation pays for itself almost immediately. The rest gets cut.
An engineer sits with finance or HR and builds the thing. Their tools, their real data, their desk. No requirements doc thrown over a wall. The people with the problem watch it get solved.
Your staff already paste company data into consumer chatbots. In a regulated environment that isn't a policy problem, it's a breach with a delay timer. Give people sanctioned tools that are genuinely better and the shadow stuff dies on its own.
03 · Domain
Healthtech, where AI adoption collides with HIPAA. Plenty of consultants will hand you a compliance binder. Compliance should be an engineering constraint and built into your tooling, because a policy document nobody reads has never protected a single patient record.
Clear rules for what LLMs and agents can touch. Which repos, which datasets, which environments and company applications.
Audit trails, access boundaries, and review gates that keep your auditors happy without strangling delivery. Yes, you can have both.
Straight answers about AI vendors. Who signs a BAA. Where your data actually goes. Which tools have no business being anywhere near patient records.
04 · Process
A month embedded in your team. Code, process, people. You get a blunt, written action plan for what's actually slowing you down and what's getting ready to bite you. You're probably doing a lot right as well, which is rad. We'll talk about that, too.
Execute the action plan with your team. Standards, rituals, tooling, all held to one bar: solid, compliant engineering that accelerates delivery. Everything is documented, owned by your people, and built to outlive our time together.
An ongoing fractional cadence keeps the bar where we set it. Leadership in your weekly rhythm while the team grows. As your own leaders step up, we step back.
05 · Fit
Not everyone. The engagements that go badly are the ones that should never have started, so here's the honest filter.
06 · Principal
Trendkill Systems is Terry Harmon. Hi! I have over twenty years building tech companies, from back-of-the-napkin ideas to exit. Most recently I led engineering at Kismet Health from early stage to exit, which is why healthtech is home turf here. Hard problems are fun.
My range runs wide. Eye tracking. Vocal Biomarkers and Live Vital Signs. Ecommerce. Enterprise software Fortune 100 companies rely on. CTO of a venture studio that launched over 70 start ups. Early engineer at an AI audio company building state-of-the-art text-to-speech tools for enterprise. Built one of the first AI Gateways for scaling LLMs in production. Engineering teams scaled from 2 to 30. I've been around the block.
The name is a promise. We kill the trend-chasing so your team can do the work that actually moves the business.
07 · Writing
Every engineering org has an AI strategy deck. Almost none have working agreements for how AI-written code gets reviewed, tested, and owned. Guess where the value leaks out.
Maybe you need senior engineering leadership. Maybe you need an AI operating model that isn't theater. Either way, let's talk.
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