by eduardo cruz · fractional cto

Your AI assistant
can do better.

You already pay for a capable agent. It just doesn't know your business. Throughline fixes that — continuously — so the assistant you use every day gets sharper every week.

the honest version

Agents are reactive. That's the whole problem.

Every model release gets smarter. Your assistant doesn't get smarter about you. It waits for a prompt, answers from a blank slate, and forgets the moment the conversation ends. You spend your day re-explaining the same context — your goals, your stack, your rules, last week's decision — over and over.

The bottleneck was never the model. It's context. A brilliant agent with no context behaves like a great contractor on their first day — every single day.

the insight

You don't need a better model.
You need to teach the one you have.

01

Context compounds.

Models reset. Knowledge about your business should accumulate. Every decision, guideline, and conversation makes the next answer better than the last.

02

Education beats configuration.

Not a settings panel you fill out once. An ongoing curriculum your agent actually learns from — kept current as the business moves.

03

Pay to educate, not to replace.

You already have Claude. Throughline is the cheapest leverage you've got: invest in the agent's understanding of your company, not in yet another tool.

what it looks like

One picture keeps everyone honest.

Every Throughline starts with a radar: six outcomes that actually move a business, scored 0–10. The solid shape is where you are now; the dashed shape is where this year's goal points. The gap between them is the work.

Outcome radar — where the business is now vs where the year's goal points Revenue 5 Product 7 Customers 6 Growth 4 Team & Ops 6 Focus 8
current year-end target

The radar hangs off one goal ladder. Each level narrows the focus until it's something your agent can actually act on this week.

YearReach the target shape. The one outcome the whole year is about.
QuarterWhich axes move first, and by how much.
MonthThe concrete push for these four weeks.
WeekWhat you — and the agent — do now. Every task points at a spoke.

Open it in any meeting and the conversation has nowhere to hide: here's where we are, here's where we said we'd be, here's this week's move.

what it actually is

A continuous education layer for your agent.

Throughline turns how your business actually runs into context your agent can use — goals, working rules, real decisions, the things you'd otherwise re-explain — and feeds it to Claude Desktop and Claude Code. Every session starts informed instead of cold.

It arrives as a pull request.

Changes to your agent's knowledge come as a PR — readable, reviewable, versioned. You approve what your agent learns, the same way you approve code.

And a short weekly digest.

One email: what your agent learned this week, what changed, what it's now better at. That's the whole interface. No dashboard to babysit, no tab to keep open.

Most AI products bury you in another dashboard. The right interface for an agent that's learning your business is a diff and an email.

who's behind it

Built by someone in the trenches, daily.

I'm Eduardo Cruz. I've been a working fractional CTO and senior Laravel engineer for over a decade, and I ship production AI agents and MCP servers as my day job — not in theory, in real businesses, every week.

Throughline came out of a problem I kept hitting myself: the agent was capable, but starting every conversation from zero. So I built the thing I needed. Now I'm opening it to a few founders who feel the same.

10+ yrs Laravel · production agents & MCP servers · fractional CTO

I'm taking a few founders to start.

Founding 5. If teaching your AI agent about your business sounds like the thing you've been missing, leave your email. No pitch, no auto-responder — I read every one and reply personally.

No newsletter. Just a personal reply when there's a seat.